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Applied Science 

Volume 4, Issue 4 

December 2011 

PREPARATION AND CHARACTERIZATION OF CHEMICAL BATH DEPOSITED NiSe THIN FILMS 

ANUAR KASSIM, HO SOON MIN, TAN WEE TEE and YAZID ROSLI 

PRELIMINARY REPORTS ON MIDDLE MIOCENE – EARLY PLEISTOCENE DINOFLAGELLATE CYSTS 

FROM THE WESTERN NIGER DELTA, NIGERIA 

DURUGBO ERNEST UZODIMMA 

ESTIMATED SHRINKAGE OF ONE-STAGE OF COBB-DOUGLAS PRODUCTION FUNCTION 

ADEEB AHMAD ALI ALRAHAMNEH and OMAR HAWAMDEH 

ASPECTS OF STRATIGRAPHY AND FACIES PROFILE OF CLASTIC DEPOSITS IN DOMA FIELD, 

NIGER DELTA 

ROTIMI OLUWATOSIN JOHN, ADEOYE OLUSHOLA TAIYE, OFOMOLA MERRIOUS OVIRI 

IN STRATEGIC DECISION AND MOTIVATION IN JORDANIAN BANKING INDUSTRY 

MARWAN AL-NSOUR

Ozean Journal of 


A PEER REVIEVED INTERNATIONAL JOURNAL 

------------------------------------------------------------------------------------------------------------------------- 

Volume 4, Issue 4, December 2011 

ONLINE ISSN 1943-2542 PRINTED ISSN: 1943-2429 

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Managing Editor 

Ali Ozel, Dumlupinar University 

Publication Coordinator 

Taskin Inan, Dumlupinar University 

Editorial Board 

Gerald S. Greenberg, Ohio State University, USA 

Hakki Yazici, Afyon Kocatepe University, Turkey 

Hayati Akyol, Gazi University, Turkey 

Hayati Doganay, Ataturk University, Turkey 

Laurie Katz, Ohio State University, USA 

Lisandra Pedraza, University of Puerto Rico in 

Rio Piedras, Puerto Rico 

Lutfi Ozav, Usak University, Turkey 

Mihai Maxim, Bucharest University, Romania 

Ibrahim Atalay, Dokuz Eylul University, Turkey 

Ibrahim S. Rahim, National Research Center, Egypt 

Janet Rivera, NOVA University, USA 

Ramazan Ozey, Marmara University, Turkey 

Samara Madrid, Northern Illinois University, USA 

Samia Abdel Aziz-Ahmed Sayed, National Research 

Center, Egypt 

Web: http://www.ozelacademy.com E-mail: editorejes@gmail.com 

Copyright © 2008 Ozean Publication, 2141 Baneberry Ct. 43235, Columbus, Ohio, US

Ozean Journal of 


A PEER REVIEVED INTERNATIONAL JOURNAL 

--------------------------------------------------------------------------------------------------------------------------- 

Volume 4, Issue 4, December 2011 


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PREPARATION AND CHARACTERIZATION OF CHEMICAL BATH DEPOSITED NiSe THIN FILMS 

ANUAR KASSIM, HO SOON MIN, TAN WEE TEE and YAZID ROSLI 

PRELIMINARY REPORTS ON MIDDLE MIOCENE – EARLY PLEISTOCENE DINOFLAGELLATE CYSTS FROM THE WESTERN NIGER DELTA, 

NIGERIA 


ESTIMATED SHRINKAGE OF ONE-STAGE OF COBB-DOUGLAS PRODUCTION FUNCTION 

ADEEB AHMAD ALI ALRAHAMNEH and OMAR HAWAMDEH 

ASPECTS OF STRATIGRAPHY AND FACIES PROFILE OF CLASTIC DEPOSITS IN DOMA FIELD, NIGER DELTA 

ROTIMI OLUWATOSIN JOHN, ADEOYE OLUSHOLA TAIYE, OFOMOLA MERRIOUS OVIRI 

IN STRATEGIC DECISION AND MOTIVATION IN JORDANIAN BANKING INDUSTRY 

MARWAN AL-NSOUR 

Web: http://www.ozelacademy.com E-mail: editorejes@gmail.com 

Copyright © 2008 Ozean Publication, 2141 Baneberry Ct. 43235, Columbus, Ohio, USA

A peer revieved international journal 


http://ozelacademy.com/ojas.htm

Ozean Journal of Applied Sciences 4(4), 2011 


ISSN 1943-2429 

© 2009 Ozean Publication 

PREPARATION AND CHARACTERIZATION OF CHEMICAL BATH DEPOSITED 

NiSe THIN FILMS 

ANUAR KASSIM*, HO SOON MIN, TAN WEE TEE and YAZID ROSLI 

Department of Chemistry, Faculty of Science, University Putra, Malaysia 

*E-mail address for correspondence: anuar@science.upm.edu.my 

_________________________________________________________________________________________ 

Abstract: Nickel selenide thin films were deposited on microscope glass substrates using the chemical bath 

deposition method. The deposition was carried out using nickel sulphate as a Ni 2+ ion source and sodium 

selenite as a Se 2- ion source in the presence of Na 2 EDTA as a complexing agent. The structural and 

morphological properties of NiSe films obtained were investigated using X-ray diffraction and atomic force 

microscopy. X-ray diffraction patterns indicated that the films were polycrystalline NiSe with hexagonal 

structure. Based on the atomic force microscopy analysis, all the samples showed complete coverage of the 

substrate surface with the thickness of the films about 156-664 nm. When the bath temperature was increased 

from 55 to 75 °C, the grain size was increased but the band gap was decreased from 1.89 to 1.80 eV. 

Keywords: nickel selenide, chemical bath deposition, thin films, complexing agent 

__________________________________________________________________________________________ 

INTRODUCTION 

The thin films technology becomes more and more attractive for the researchers. The interest for chalcogenide 

semiconductor materials is based on their potential applications such as solar cells, sensor and laser materials. 

Thin films can be prepared by various methods such as spray pyrolysis (Badera et al., 2008), pulsed laser 

deposition (Shen et al., 2008), vacuum evaporation (Murali et al., 2004), electrodeposition method (Anuar et al., 

2009), electron beam evaporation (Ahamed et al., 2010) and chemical bath deposition (Ezema et al., 2007). The 

preparation of thin films by the chemical bath deposition (Joshi et al., 2004; Chaudhari et al., 2008; Song et al., 

2009; Anuar et al., 2011; Gopakumar et al., 2010; Raniero et al., 2010; Ubale 2010; Babu et al., 2011) is 

currently attracting a great deal of attention due to simple, no requirement of sophisticated instruments, 

minimum material wastage and easy coating of large surfaces. This method is based on the controlled release of 

the metal ions and chalcogenide ions in an aqueous bath into which the substrates are immersed. 

In this paper, we prepare NiSe thin films by chemical bath deposition method and study the effects of bath 

temperature on the properties of these materials. So far, we have not seen any literature review for the 

deposition of NiSe films in the presence of Na 2 EDTA as a complexing agent in acidic medium. 

363


EXPERIMENTAL 

Microscope glass slides were used as the substrate during the deposition process. The substrates were first 

cleaned in ethanol solution and subsequently ultrasonically washed with distilled water. Substrates were then 

dried in an oven at 90 °C. Nickel sulphate, sodium selenite, disodium ethylenediaminetetraacetate and 

hydrochloric acid of analytical reagent grade were used as received. Aqueous solutions of nickel sulphate, 

sodium selenite and disodium ethylenediaminetetraacetate were separately prepared before experiment. 25 mL 

of nickel sulphate (0.2 M) and 25 mL of disodium ethylenediaminetetraacetate (0.2 M) were mixed in a beaker. 

Then, 25 mL of sodium selenite (0.2 M) was added and the pH of the solution was adjusted to 2.5 by addition of 

hydrochloric acid. Substrates were immersed vertically in the beaker. Then, the beaker was placed in water bath 

at desired temperature (55, 65 and 75 °C). The beaker was not stirred during the thin films deposition. After 

completion of films deposition (150 min), the deposited films were then washed with distilled water and dried in 

air at room temperature. 

X-ray diffraction (XRD) analysis was carried out using a Philips PM 11730 diffractometer for the 2θ ranging 

from 25° to 60° with CuKα (λ=1.5418 Å) radiation. The surface morphology and thickness were examined by 

recording atomic force microscopy (AFM) images with a Q-Scope 250 in contact mode with a commercial 

Si 3 N 4 cantilever. The elemental composition of the films was studied by scanning the electron microscope 

(JEOL JSM 6400) attached with energy dispersive analysis of the X-ray (EDAX) analyzer. 

Photoelectrochemical experiments were performed in [Fe(CN) 6 ] 3- /[Fe(CN) 6 ] 4- redox system, by running linear 

sweep voltammetry between -400 to -900 mV versus Ag/AgCl (silver-silver chloride). The halogen lamp (100 

W) was used for illuminating the electrode. The film-coated microscope glass slide was placed across the 

sample radiation pathway while the uncoated microscope glass slide was put across the reference path. Thus, the 

absorbance measurement included only the contribution from NiSe thin films. From the analysis of absorption 

spectrum, the band gap energy was determined. 

RESULTS AND DISCUSSION 

X-ray diffraction patterns recorded for the chemical bath deposited NiSe films on microscope glass slide at 

various bath temperatures (55, 65 and 75 °C) are shown in Fig. 1. The studies showed that the films of NiSe are 

polycrystalline in nature with hexagonal structure with lattice constant (a=3.66Å, b=3.66Å, c=5.33Å). For the 

films deposited at lower bath temperature, the presence of two peaks at 2=28.3 and 32.6 corresponds to the 

(100) and (101) planes, respectively can be seen in Fig. 1a. The different peaks in the XRD patterns were 

indexed and the corresponding values of d-spacing values were compared with the standard d-spacing values 

(JCPDS reference No.: 01-075-0610). It is observed that the height of prominent peaks (100) of NiSe increases 

and some new peaks of NiSe start to appear while increasing bath temperature from 55 to 75 °C. As the bath 

temperature was increased to 65 and 75 °C, the NiSe peaks increased to three and finally four, respectively. 

Overall we can conclude that the XRD patterns confirm the presence of NiSe in the films, the only other peaks 

such as (112), (103), (121), (211) and (220) planes being those of the SiO 2 (JCPDS reference No.: 01-074-0201) 

(Weiss and Weiss, 1954) substrate. 

Atomic force microscopy (AFM) images of NiSe thin films deposited under various bath temperatures are 

shown in Fig. 2. Based on the atomic force microscopy images, all the samples show a distribution of grain 

which covers the surface of the substrate completely. The films deposited at lower bath temperature (55 °C), 

show less particles compared to the other films. These films are consisting of smaller grain with the size of 0.8-1 

μm. For the films deposited at 65 °C, the samples appear more homogeneous which have a grain size of 1.5 μm. 

As the bath temperature is increased up to 75 °C, the grain size increased compared to the films deposited at 

lower bath temperature. The irregular shape of the grains can be seen as shown in Fig. 2c. Several crystallites 

grouped together to form larger grains. The average size of grains is in the range between 2 and 3 μm. The 

thickness of thin films was investigated using AFM images. The thickness values obtained are 156, 322 and 664 

nm for the films deposited at 55, 65 and 75 C, respectively. These results conclude that an increase in bath 

temperature allow more materials to be deposited onto the substrate and thicker films to be formed. 

Band gap energy and transition type can be derived from mathematical treatment of data obtained from optical 

absorbance versus wavelength with Stern relationship of near-edge absorption: 

364


A 

[ k ( hv E 

hv 

g 

) 

n / 2 

…(1) 

where v is the frequency, h is the Planck’s constant, k equals a constant while n carries the value of either 1 or 4. 

The value of n is 1 and 4 for the direct transition and indirect transition, respectively. According to equation (1), 

(Ahv) 2 linearly depends upon the photon energy (eV). This fact is confirmed by the curves presented in Fig. 3. 

The values of band gap were determined by extrapolating the linear portions of the respective curves to 

(Ahv) 2 =0. A direct band gap of 1.80, 1.86 and 1.89 eV was found for the films deposited at 75, 65 and 55 °C, 

respectively. These band gap values are in good agreement with the values reported earlier (Hankare et al., 

2010; Moloto et al., 2009). 

The composition of the films has been studied from energy dispersive analysis of X-rays (EDAX). The typical 

EDAX result (Fig. 4) revealed that the following composition in atomic percentage (%): Ni(51.36 %) and Se 

(48.64 %) for a films deposited at 65 °C. The atomic ratio of Ni:Se is 1:1. This result is consistent with XRD 

analysis of the sample with phase corresponding to NiSe. 

Fig. 5 indicates the photoresponse of the deposited films (which prepared at 65 °C) in contact with Fe 2+ /Fe 3+ 

redox couple. The figure shows the resulted changes in the current as the films have been illuminated 

intermittently. We observed that the photocurrent occur on the negative potential shows that the films prepared 

are p-type. The same bahavior has been reported for the NiSe films deposited by electrodeposition method 

(Zainal et al., 2005 and chemical vapour deposition technique (Panneerselvam et al., 2008). 

CONCLUSIONS 

NiSe thin films were deposited on microscope glass substrate by chemical bath deposition method. Deposition 

was carried at different bath temperatures from 55 to 75 C in the presence of Na 2 EDTA as a complexing agent. 

The XRD patterns showed polycrystalline films of hexagonal phase with (100) preferential orientation. 

According to the atomic force microscopy analysis, all the films showed complete coverage of the substrate 

surface with the thickness of the films about 156-664 nm. As the bath temperature was increased from 55 to 75 

°C, the grain size was increased but band gap was decreased from 1.89 to 1.80 eV. 

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acidic chemical bath. Applied Surface Science, 239, 1-4. 

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Figure 1: X-ray diffraction patterns of NiSe thin films deposited at different bath temperatures (a) 55 °C (b) 65 

°C (c) 75°C ( ♦ NiSe; ◊ SiO 2 ) 

367


(a) 

(b) 

368


(c) 

Figure 2: Atomic force microscopy images of NiSe thin films deposited at different bath temperatures (a) 55 °C 

(b) 65 °C (c) 75°C 

369


(a) 

(b) 

370


(c) 

Figure 3: Plots of (Ahv) 2 versus hv of NiSe thin films deposited at different bath temperatures (a) 55 °C (b) 65 

°C (c) 75°C 

Figure 4: Typical EDAX spectrum of NiSe thin films deposited at 65 C 

371


Figure 5: Typical photosensitivity of NiSe thin films deposited at 65 °C 

372



ISSN 1943-2429 


PRELIMINARY REPORTS ON MIDDLE MIOCENE – EARLY PLEISTOCENE 

DINOFLAGELLATE CYSTS FROM THE WESTERN NIGER DELTA, NIGERIA 


Department of Biological Sciences, Redeemer’s University, Nigeria 

E-mail address for correspondence: ernestduru@yahoo.com 

___________________________________________________________________________________________ 

Abstract: Few published records of dinoflagellate cysts from the Middle Miocene – Early Pleistocene of the 

Niger Delta exist. Dinoflagellate cysts events could contribute to a wider use of palynological schemes. Their 

use in combination with pollen and spores will produce meaningful biostratigraphical schemes which will be 

useful where the other microfossils are scarce. Appreciable numbers of well preserved organic walled 

dinoflagellate cysts comprising 53 genera and 93 species were recovered from the analysis of 104, 100, 96 and 

89 ditch cuttings of wells BA, BB, BC and BD from part of the Western Niger Delta. The ages ranged from 

Middle Miocene to Early Pleistocene (c.a 15.0Ma – 1.3Ma) based on the behaviour of pollen and spore marker 

species and confirmed with foraminiferal data. The samples were characterized by common records of 

peridiniaceans, especially in the Middle –Late Miocene. These occurred in association with common 

gonyaulacaceans such as Nematosphaeropsis labyrinthus, N. lemniscata, Sumatradinium spp., Lingulodinium 

machaerophorum, Operculodinium centrocarpum, Spiniferites ramosus, Spiniferites mirabilis, 

Hystrichokolpoma rigaudiae, Polysphaeridium zoharyi, Achomosphaera ramulifera, Achomosphaera 

andalousiensis, Tuberculodinium vancampoae, Impagidinium spp., Homotryblium spp., and spot occurrences 

of the older forms Dinogymnium eucalense, Muderongia spp., Odontochitina cf. costata, Wallodinium spp., 

Paleocystodinium golzowenze, Glaphyrocysta spp., and the acritarch Ascostomocystis potane indicating 

reworking. The occurrence of Achomosphaera andalousiensis is documented for the first time in the Niger 

Delta and its LDO close to the 11.6Ma promises to be notable event. 

Key words: Miocene-Pleistocene, Peridiniaceans, Gonyaulacealens, Western Niger Delta,Nigeria. 

____________________________________________________________________________________________ 

INTRODUCTION 

The studied area is located within part of the Western Niger Delta (Fig. 1). The Tertiary Niger Delta covers an 

area of about 7500 square kilometers and is composed of an overall regressive clastic sequence, which reaches 

a maximum thickness of 9,000 – 12,000m (30,000- 40,000ft). Its development has been dependent on the 

balance between the rate of sedimentary and the rate of subsidence. This balance and resulting sedimentary 

patterns appear to have been influenced by the structural configuration and tectonics of the basement. (Evamy 

et al.1978). Three lithographic units are recognized, namely the Akata Formation, Agbada Formation, and the 

Benin Formation (Short and Stauble, 1967; Doust and Omatsola, 1990. 

373


N 

WELLS BA and BB 

WELLS BC and BD 

Figure 1: Map of the Niger Delta showing the studied wells (After Doust & Omatsola, 1990). 

Figure 1: Map of the Niger Delta showing the location of studied wells. 

According to Doust and Omatsola (1990), the Akata shales contain a few streaks of sand, possibly of turbiditic 

origin which were deposited in holomarine (delta front to deeper marine) environments. These marine shales 

range from Paleocene to Holocene in age. On the other hand, the Agbada formation is overlain by a paralic 

sequence of inter-bedded sand and shales, 300 – 4500m (984 – 14766ft) thick. It consists of alternating 

sandstones and shales of deltaic front, distributary’s channel and deltaic plain origins. The alternating sequence 

of sandstones and shales of the Agbada formation has been shown by Weber (1971) to be a cyclic sequence of 

marine and fluvial deposits, determined from electric-log patterns, well, cores and dipmeter data. Furthermore, 

the topmost unit (the Benin Formation) consists of fluviatile gravels and sand occurring from the contemporary 

delta surface to depths of about 2134m (7,000ft). It consists predominantly of massive, highly porous, fresh 

water bearing sandstones, with local thin shale inter-beds, which are considered to be of braided stream origin. 

The lithofacies analysis and the well log responses suggest that only one of the formally recognized 

lithostratigraphic units in the Niger Delta Basin viz: the Agbada Formation (Short and Stauble, 1967; 

Whiteman, 1982) was penetrated in all the four wells. This is a paralic sequence consisting of alternations of 

sands/silts and shales/mudstones, with shales predominating at the lower section and sands predominating upsection. 

Earlier dinoflagellate cysts investigations from the Gulf of Guinea 

Generally, in the Southern Hemisphere which encompasses the Niger Delta/Gulf of Guinea among others, 

dinoflagellate studies are very scanty when compared to the numerous research that have been done in the 

Northern Hemisphere(Antholinez , 1999, Antholinez et al., 2004, Biffi and Grignani, 1983, Brinkhuis et al., 

2003, Jan du Chêne, 1987, Marret and So-Young, 2009, McMinn,1992, 1994, Morzadec-Kerfourn,1992,Oboh- 

Ikuenobe et al., 1999, Sluijs et al., 2003). It is for this reason that this study was undertaken. These recovered 

dinoflagellates will contribute to the global records of which only few have been documented from the Niger 

374


Delta, Gulf of Guinea and the Southern Hemisphere and ultimately a dinoflagellate zonation would be erected 

for the Middle Miocene-Early Pleistocene of the Niger Delta. Marine events are generally more global as 

revealed by the use of nannofossils and foraminiferal zonation schemes (Hardenbol et al., 1998, Bergreen et 

al., 1995, Blow 1969,1979, Martini, 1971, among others). Again, Haq et al., (1987), Grandstein et al., (2004) 

had both incorporated dinoflagellate events in their Global cycle charts thereby highlighting their potentials. 

Dinoflagellate cysts could contribute to a wider use of the existing palynological schemes which are solely 

based on pollen and spore marker species. The incorporation of dinocyst events in combination with pollen and 

spores will produce meaningful biostratigraphical schemes which will be useful where the other microfossils 

are scarce. The study of Niger Delta dinocysts will help refine correlations between deep sequences, condensed 

sections and shelfally deposited strata. This will provide for meaningful correlations with the Mesozoic- 

Cenozoic depositional sequences of Haq et al., (1988) as modified by Hardenbol et al., (1998) and updated by 

Grandstein et al., (2004). 

The few records of dinoflagellate studies in the Gulf of Guinea include those of Biffi and Grignani (1983) who 

studied Oligocene sediments from fifteen boreholes of subsurface Tertiary sediments in the Niger Delta which 

yielded rich dinoflagellate cyst assemblages characterized by abundant Peridinioids particularly Lejeunacysta, 

Phelodinium and Selenopemphix species. They described seven new species of Lejeunacysta (L. brassiensis, L. 

communis, L. pulchra, L. beninensis, L. globosa, L. lata, L. granosa ); two new species of Phelodinium (P. 

nigericum and P. africanum) and one of Selenopemphix (S. warriensis). They further emended some species of 

Lejeunacysta. 

Jan du Chêne, (1987), having studied Danian sediments from Senegal reported the occurrences of such 

dinoflagellate species as Fibrocysta axialis, Muratodinium fimbriatum, Danea californica, Xenicodinium 

lubricum, Spinidinium densispinatum, Kallosphaeridium yorubaense, Diphyes colligerum, Senegalinium spp., 

Phelodinium spp., Ifecysta spp., Senegalinium ( S. orei), Hafniasphaera (H. septata), Spiniferites mirabilis and 

Florentinia spp. 

Oloto (1989) did a comprehensive study of dinoflagellate cysts from the Maastrichtian section of the Nkporo 

shale of the Gbekebo-1 well from the coastal Benin Flank of the Niger Delta. He recovered 16 genera and 37 

species of dinocysts together with 6 genera and 6 species of pollen and spores from which he recognized six 

dinoflagellate zones and four pollen/spore zones which he used for palaeoenvironmental and palaeoclimatic 

interpretations. Oloto (1990) further studied some core samples from the Danian section of the Gbekebo-1 well. 

He recorded dinoflagellate cysts, pollen, spores and associated elements such as algae, fungal spores and 

chitinous microfaraminiferal test linings. He used the relative diversity and abundance of the dinocysts, pollen 

and spores for the age determination of the sediments. Again, the dinocyst zones he recognized were based on 

the use of first occurrences of two or more species. 

Morzadec – Kerfourn (1992) had studied the presence of estuarine dinoflagellate cysts among Oceanic 

assemblages of Pleistocene deep – sea sediments from the West African margin (Guinea, Ivory Coast). She 

opined that the importance of these estuarine cysts in oceanic assemblages depended on the configuration of the 

continental shelf and currents. Again, the evolution of the littoral environment she inferred to be a function of 

climatic changes and variations in sea level. She reported a considerable assemblage of dinoflagellate cyst 

species diversity in which many estuarine cysts and terrigenous supplies were brought into the oceanic domain 

together. Cysts characteristic of the Oceanic and Oceano – Neritic environment, as defined by Wall et 

al.(1977), revealed information about the surface water temperature. She suggested that estuarine cysts 

dispersed in the oceanic domain furnish information about environmental changes in the coastal zone and that 

Polysphaeridium zoharyi a species adapted to very saline waters had indicated an arid phase. On the other 

hand, she noted that Tuberculodinium vancampoae was tolerant of freshwater supplies and therefore an 

indicator of a more humid phase. 

Oboh (1992) in her study of Middle Miocene paleoenvironments from the Niger Delta had ascribed prodelta 

environments to the core of her well 27 which yielded 8-11% microforaminiferal test linings and five 

specimens of dinoflagellate cysts with low diversity of benthic foraminifera and an assemblage composed of 

nearly 99% agglutinated species. 

Oboh-Ikuenobe et al. (1999) working with Upper Oligocene-Early Miocene strata dated by the presence of the 

pollen types Retibrevitricolporites obodoensis and Magnoliapollenites spp., from the Côte D’Ivoire –Ghana 

Transform Margin observed a cyclic alternation of the dominant dinoflagellate cysts between gonyaulacaleans 

and peridinialeans with Spiniferites mirabilis and Hystrichokolpoma spp.(H. cinctum) as the commonest 

gonyaulacoids. Nematosphaeropsis labyrinthus was dominant in one sample, while the other gonyaulacoids 

were Cordosphaeridium cantharellum, Homotryblium tenuispinosum, and Achillodinium biformoides. Large 

numbers of Protoperidinioids characterized the Peridinialean dominated sections. They found the abundances 

of these dinocysts, together with calcareous and siliceous microfossils to be controlled by organic matter 

375


distribution which they opined were indicative of changes in the water mass and paleoproductivity. The pollen 

and spores were scarce with many showing evidence of reworking. Apart from those mentioned earlier, other 

recovered pollen and spores were Peregrinipollis nigericus, Spirosyncolpites bruni, and Grimsdalea sp. in 

association with long ranging dinocysts which were unsuitable for age designation. 

Antolinez (1999) having analyzed forty four samples from the early Paleogene interval of Alo-1 well in 

Anambra State, Nigeria and ODP Hole 959D (Leg 159) in the Côte d'Ivoire-Ghana Transform Margin for 

dinocysts, recovered good to moderate, and well preserved specimens. He compared the stratigraphic and 

quantitative data with detailed and well calibrated dinocyst distributions from north-western Europe and the 

southern Hemisphere, Tasmania and New Zealand. He erected five informal zones (A to E). Zone A was the 

stratigraphically oldest which was characterized by the consistent occurrences of Areoligera senonensis, 

Areoligera coronata, Palaeocystodinium bulliforme, and Hafniasphaera septata. In Zone B were 

Damassadinium cf. D. heterospinosum in combination with abundant Fibrocysta/Lanternosphaeridium spp., 

and Cordosphaeridium spp. The dinocyst assemblages in zone C was characterized by the co-occurrence of 

abundant Apectodinium spp., and Adnatosphaeridium spp. Zone D consisted of common Glaphyrocysta 

ordinata, Glaphyrocysta divaricata, Polysphaeridium subtile, Spiniferites microceras, and Adnatosphaeridium 

spp. The youngest Zone E was characterized by the occurrences of Homotryblium abreviatum, Homotryblium 

cf. H. oceanicum, and H. pallidum. These results, he reasoned, could have great impacts on hydrocarbon 

exploration in tropical areas such as southeastern Nigeria and the Equatorial Atlantic where important 

hydrocarbon reservoirs occur in Paleocene and Eocene continental and marginal marine rocks. Again, 

subsidence curves, thermal maturation histories and timing of oil migration rely heavily on ages directly 

derived from palynological zones in these areas. 

Sluijs et al. (2003) had also studied the dinoflagellate cysts from the Eocene-Oligocene Transition in the 

Southern Ocean (ODP Leg 189). Though the transition was barren of calcareous microfossils, they recovered 

abundant marine organic walled dinoflagellate cysts and diatom assemblages. These, they opined, were suitable 

for detailed biostratigraphic and paleoenvironmental analysis. They listed twenty species among which were 

Aireiana verrucosa, Alterbidinium distinctum, Brigantedinium spp., Deflandrea spp.(D. antarctica, D. 

phosphoritica), Enneadocysta, Gelatia inflate, Octodinium askiniae, Paucisphaeridium spp. Schematophora 

speciosa, Spinidinium colemanii, Spinidinium luciae, Spinidinium macmurdoense, Stoveracysta kakanuiensis, 

Turbiosphaera filosa and Vozzhennikovia spp. 

Furthermore, Demchuk and Morley (2004) reported the occurrence of dinoflagellate cysts which they 

encountered in their study of some Nigerian deep offshore strata. These occurred in association with diverse 

assemblages of tropical pollen, spores, and sporadic abundances of freshwater algae. They had used 

quantitative palynological events in their chronostratigraphic deductions and indicated their use in delineating 

and confirming sequence stratigraphic systems tracts together with cumulative dinoflagellate cysts. The 

chronostratigraphically useful taxa whose First Appearances/or Extinctions they utilized were 

Retibrevitricolporites obodoensis/protrudens, Psialtricolporites crassus, Racemonocolpites hians, Belskipollis 

elegans, Verrutricolporites rotundiporus and Cyperaceae spp. They further found the quantitative occurrences 

of Monoporites annulatus, Zonocostites ramonae, Magnastriatites howardi, Praedapollis flexibilis, 

Multiareolites formosus (Acanthaceae spp.), Celtis spp., and cumulative freshwater algae (Botryococcus 

braunii and Pediastrum) also useful. 

Moreover, Durugbo (2010) had also documented peridiniaceans from the Middle Miocene of the western Niger 

Delta which he opined resembled those recovered from the Gulf of Mexico by Wrenn and Kokinos(1986). The 

commonest species he recorded were Lejeunacysta communis, L. lata, L. diversiforma, Apteodinium spp. 

Multispinula quanta, M. minuta, Xandarodinium cf. xanthum, Selenopemphix nephroides, S. warriensis, S. 

coronata, S. armata, Selenopemphix sp. E similar to (Plate 1 # 11) of Duffield and Stein (1986), and 

Spiniferites mirabilis similar to S. mirabilis (Plate 6 # 4) of Wrenn and Kokinos (1986). 

However, there have been several dinoflagellate studies in other parts of Nigeria such as the Cretaceous Upper 

Benue Trough (Lawal and Moullade, 1986), the Nkporo shale on the Calabar Flank of South eastern Nigeria 

(Edet and Nyong, 1994), the Maastrichtian-Lutenian succession of the Benin-1 well from the Western Anambra 

Basin flank of Southern Nigeria (Asadu and Lucas, 2006), the Paleocene - lowermost Eocene successions in 

the Alo-1 well from the Anambra Basin, Southeast Nigeria(Antolinez and Oboh-Ikuenobe, 2007), the Oshosun 

Formation in the Sagamu quarry, Dahomey Basin, South-Western Nigeria (Bankole et al., 2006), and the 

Upper Cretaceous Patti Formation, Southeastern Bida Basin Nigeria (Ojo and Akande, 2006). 

From the foregoing, the paucity of dinoflagellate studies in the Niger Delta becomes very glaring thereby 

revealing the need for research such as this to add to the global records, and also refine existing palynological 

schemes through the erection of dinoflagellate zonation schemes which would promote better use of 

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palynological events in age dating and correlation of wells, as well as paleoenvironmental inferences in 

combination with pollen and spore species. 

MATERIAL AND METHODS 

For this research, 104,100, 96 and 89 ditch cuttings of the wells BA, BB, BC and BD from the offshore 

Western Niger Delta spanning the intervals (1800-11790 feet), (1000-10570 feet), (1980- 10570 feet) and 

(1920-9860 feet) were donated for the investigation by Chevron Nigeria Ltd in January 2005. Standard 

palynological techniques involving treatments with HCL and HF were applied. Full details of the laboratory 

procedure are given in Durugbo et al. (2010). One microscope slide stained with Safranin O was studied and all 

the palynomorphs present were enumerated. The well, sample depth and associated England Finder localities of 

each dinoflagellates are given (Plates 1-6), and transmitted light photomicrographs were taken at 

magnifications of 400 and 1000 on a Leitz Dialux 20 EB microscope with an attached Motic 2.0 camera at the 

Paleobotanical laboratory of the University of Lagos. The identification of the dinoflagellates and other marine 

elements were based on the monographs of Brinkhuis et al. (2003), Bujak et al. (1980), Fensome et al., (1993), 

Head and Wrenn (1992), Lentin and Williams(1989), Marret and Zonneveld (2003), Powell (1992), Rochon, et 

al.(1999), Sluijs et al. (2003), and Wrenn et al, (1986). Generally, species nomenclature for dinoflagellate cysts 

followed Fensome and Williams (2004). 

The slides, residues, unprocessed samples, CD copies and duplicate prints are in the palynological collections of 

the Biological Sciences Department, Redeemer’s University, Mowe, Ogun State, Nigeria. 

Chronostratigraphic Ages 

The chronostratigraphic ages were provided by age diagnostic foraminifera together with pollen and spore 

markers species according to the zonation schemes of Evamy et al., (1978) and Legoux (1978). The ages 

ranged from 15.0 Ma to 5.0 Ma for wells BA and BB (Blow 1969,1979; Hardenbol et al., 1998; Bergreen et al., 

1995) which coincided with the P720-P860 Niger Delta palynological Zones of Evamy et al. (1978). In wells 

BA and BB, the upper sections were dated 5.0Ma based on the Base occurrence of the Niger Delta 

palynological Miocene/Pliocene boundary marker species Retistephanocolpites gracilis (aff. Borreria 

verticillata) at 2160 feet and 1800 which were close to the FDO: Eggerella scabra/ FDO: Cyclammina minima 

recorded at1150 feet and 1990 feet respectively. Furthermore, the basal sections were of Early Middle Miocene 

age due to the FDO: Eponides eshira / LDO: Orbulina universa at 11070 feet and 10060 feet. Within these 

sections were common records of Crassoretitriletes vanraadshooveni and Magnastriatites howardi recorded 

below the base occurrence of Belskipollis elegans (Evamy et al., 1978, SHELL, 1998) confirming the age 

assignments. Furthermore, the ages of the wells BC and BD sediments ranged from 1.3 Ma to 5.8 Ma which 

aligned with the P900-P860 Niger Delta palynological Zones of Evamy et al. (1978). The upper sections were 

dated 1.3Ma based on the FDO: Globorotalia tosaensis picked at 2070 feet in both wells, while the 5.0Ma were 

marked at 8570 and 8880 feet respectively defined by the FDO: Cyclammina minima. 

RESULTS 

The Well BA Dinoflagellate cysts record 

Moderate records of dinoflagellate cysts characterized the well BA (Table 1). Well BA yielded 483 

dinoflagellate cysts made up of 34 genera and 55 species with 64 indeterminable dinocysts. These occurred in 

association with 58 marine accessories (microforaminiferal wall linings, Leiosphaeridia, other acritarchs and 

Tasmanites spp.) These dinoflagellate cysts peaked at some horizons (3690-4500; 4770-5220; 8010-8460; and 

10980-11160 feet) suggesting possible candidates for condensed sections and their associated maximum 

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flooding surfaces (Monteil, 1993, Vail and Wornardt, 1990). The dominant species were Lingulodinium 

machaerophorum, Nematosphaeropsis labyrinthus, Polysphaeridium zoharyi, Operculodinium centrocarpum, 

Sumatradinium spp., Selenopemphix nephroides, Selenopemphix spp., and Spiniferites ramosus. Also recorded 

were Tuberculodinium vancampoae, Achomosphaera ramulifera, Achomosphaera andalousiensis, 

Hystrichokolpoma rigaudiae, Lejeunecysta communis, L. hyalina, L. diversiforma, Batiacasphaera spp., 

Invertocysta spp., Thallassiphora spp., spot records of Homotryblium floripes, Homotryblium pallidum, 

Spiniferites pseudofurcatus, Systematophora spp., Surculosphaeridium spp., Paleocystodinium golzowenze, 

Cordosphaeridium cantherellum, and Glaphyrocysta spp., which co-occurred with common records of the 

acritarch Leiosphaeridia spp. 

The Well BB Dinoflagellate cysts record 

Well BB yielded a 411 dinoflagellate cysts composed of 27 genera and 52 species together with 107 marine 

accessories and 87 unidentifiable dinocysts. The commonest species encountered were Nematosphaerospsis 

labyrinthus, Sumatradinium spp., Operculodinium centrocarpum, Spiniferites ramosus, Lingulodinium 

machaerophorum, Selenopemphix nephroides, Selenopemphix warriensis, Selenopemphix quanta, 

Hystrichokolpoma rigaudiae, Polysphaeridium zoharyi, Spiniferites membranaceuss, S. mirabilis, , S. 

pseudofurcatus, Homotryblium floripes, H. pallidum, H. vallum, Achomosphaera andalousiensis, 

Achomosphaera ramulifera, Achomosphaera spp., Impagidinium spp., Lejeunecysta communis, Brigantedinium 

spp., and common records of the acritarch Leiosphaeridia spp., with spot records of Ascostomocystis potane 

(Table 2). 

The Well BC Dinoflagellate cysts record 

The recovered dinoflagellate cysts and accessories in well BC revealed a total of 1101 dinoflagellate cysts from 

36 genera and 64 species with 136 marine elements (Table 3). The peaks are possible candidates for maximum 

flooding surfaces (Monteil, 1993, Vail and Wornardt, 1990). The dominant species were Operculodinium 

centrocarpum and Polysphaeridium zoharyi accounting for 11.15% and 10.14% respectively. Other common 

species include Spiniferites ramosus, Achomosphaera ramulifera, Achomosphaera andalousiensis, 

Hystrichokolpoma rigaudiae, Spiniferites spp. (delicatus, bulloideus, elongatus etc), Achomosphaera spp., 

Selenopemphix nephroides, Selenopemphix spp., and the acritarch Leiosphaeridia spp. Some other remarkable 

dinocysts events in the well BC, were the records of Spiniferites elongatus, S. frigidus, and S. hyperacanthus. 

Also noteworthy was the abundance of Achomosphaera ramulifera at 9500 feet (Late Miocene). The oceanic 

forms, Impagidinium spp., Nematosphaeropsis labytinthus, and N. lemniscata all occurred in spots. Reworking 

is indicated by the records of Dinogymnium euclaense, Odontichitina cf. costata, Muderongia spp., and 

Paleocystodinium golzowense. The clusters of high dinocyst counts, with corresponding high diversities at 

1980-2670; 4470-5190; 5550-6450; 6540-7260 and 9500-9950 feet are suggestive of condensed sections. 

These intervals suggest well defined periods of marine transgressions. The highest dinocysts count of 99 was 

recorded at 9500 feet. 

The Well BD Dinoflagellate cysts record 

A total of 420 dinocysts of which 41 could not be placed in genera/ species levels in addition to 71 marine 

elements were recorded in well BD (Table 4). The dinocysts comprise 15 genera and 32 species. The few peaks 

were at (2700, 3240, 3690, 4590, 5490, 5760, and 7650 feet). These are also possible candidates for maximum 

flooding surfaces (Monteil, 1993,Vail and Wornardt, 1990). The commonest species include Protoperidinium 

spp., Operculodinium centrocarpum, Polysphaeridium zoharyi, Spiniferites ramosus, and Invertocysta spp. 

Other common forms were Selenopemphix nephroides, Hystrichokolpoma rigaudiae, Spiniferites delicatus, S. 

bulloideus, S. hyperacanthus S. bentori, S. elongatus, Achomosphaera ramulifera, Achomosphaera spp., 

Selenopemphix spp., Brigantedinium spp. The common records of Leiosphaeridia spp., is attributed to a 

dominantly shallow environment. The Oceanic forms, Impagidinium spp., Nematosphaeropsis labytinthus, and 

N. lemniscata again occurred in spots here again. There were few clusters of high dinocyst counts with 

corresponding high diversities suggesting brief periods of marine transgressions. The major peaks were 

recorded at 3600, 3690 4590, 5760 and 7650 feet. The most unique condensed section occurred between 3240- 

3690 feet. 

378


DISCUSSION 

These results have increased the dinoflagellate records from the Gulf of Guinea and broadened our knowledge 

of Middle Miocene – Early Pleistocene dinoflagellate cysts biostratigraphy. Again, it highlighted the oceanic 

productivity within the Middle Miocene to Early Pleistocene paleoenvironments in the western Niger Delta. 

Comparing the Middle –Late Miocene and Early Pliocene to Early Pleistocene revealed a more saline Early 

Pliocene to Early Pleistocene and a colder and more humid Middle –Late Miocene. The dinoflagellate cysts 

abundance was higher in the younger wells especially BC, yielding 1099 dinoflagellate cysts which was almost 

twice the records of either well BA or BB. Though the Selenopemphix sp. B which Wrenn and Kokinos (1986) 

had earlier reported were recovered by Stein and Duffield from offshore West Africa, the species was not 

encountered in this present investigation, an assessment of the total assemblage revealed a close similarity 

between the Western Niger Delta sediments and those from the Gulf of Mexico. The record of Selenopemphix 

sp. E of Wrenn and Kokinos (1986) in well BB and Lejeunecysta diversiforma in well BA (Durugbo 2010), 

coupled with Sumatradinium spp., Spiniferites mirabilis with thick membrane similar to plate 6 # 4 of Wrenn 

and Kokinos (1986), and Melitasphaeridium choanaphorum (Plate 4 # 8) in this study suggests that the same 

conditions must have prevailed during sedimentation in both areas. Moreover, the records of Lejeunecysta lata, 

L. communis, , L. hyalina, Homotryblium plectilum, H. floripes, H. pallidum in the present study are in contrast 

to the Gulf of Mexico samples that yielded Homotryblium vallum, H. oceanicum, H. tenuispinosum, 

Cordosphaeridium gracile, C. fibrospinosum, Phelodinium spp., and numerous reworked older dinoflagellate 

cysts such as Oligosphaeridium pulcherrimum, O. complex, Florentinia deanei, F. ferox, Odontochitina 

costata, O. operculata, O. porifera, Chatangiella spp., Ceratiopsis spp. etc. The reworked dinocysts from the 

western Niger delta wells BA and BB were Wallodinium spp, Areoligera spp.,Surculosphaeridium spp., 

Glaphyrocysta spp., while spot records of Dinogymnium euclaense, Muderongia sp. and Odontochitina cf. 

costata were recorded in wells BC and BD. Wrenn and Kokinos (1986) had opined that glacial/interglacial 

cycles had controlled these pre-Miocene reworked dinocysts which were derived from terrestrial deposits 

transported seawards in suspension with clay and silt-sized clasts during periods of sea level low stands. 

Furthermore, Oboh-Ikuenobe et al., (1999) had studied Upper Oligocene-Early Miocene strata from the Côte 

D’Ivoire–Ghana Transform Margin. She noted the presence of such species as Spiniferites mirabilis, 

Hystrichokolpoma spp. (H. cinctum), Nematosphaeropsis labyrinthus and Cordosphaeridium cantharellum, 

together with common Peridiniaceans. The recovery of these species in the present study suggests similar 

environmental conditions which probably prevailed into the Middle Miocene around the Gulf of Guinea. They 

had attributed the abundances of these dinocysts together with calcareous and siliceous microfossils to organic 

matter distribution which, they opined, were indicative of changes in the water mass and paleoproductivity. The 

pollen and spores records in wells BA and BB were moderate as compared to their scanty records indicating 

more terrigenous input brought about by high temperatures. 

The recovery of Apteodinium spp. in the Miocene sections of wells BA and BB (Durugbo 2010, plate 1, fig. 9) 

appears to concur with the reports of Mudie (1987) who documented A. spiridoides and A. tectatum from the 

lower Miocene of the Norwegian Sea. Going by these results from the Niger Delta, this genus possibly ranges 

up to the Middle Miocene. 

The oceanic genus Impagidinium species poorly represented in the four wells from the western Niger Delta 

were more common in the Gulf of Mexico samples possibly because of the inferred cold climate for these 

sediments brought about by high rainfall (Morley 1995). This is further supported by the abundant records of 

the mangrove pollen species Zonocostites ramonae co-occurring with abundant freshwater swamp, brackish 

water swamp and palm species with common freshwater algae (Durugbo et al., 2010). This concurs with the 

report of Morzadec-Kerfourn (1992) who had worked on estuarine dinoflagellate cysts in the West African 

Margin about this species which she opined preferred warm waters. However, the common records of 

Nematosphaeropsis labyrinthus the cold water indicators especially in wells BA and BB agrees with the 

inferred wet and cold climate suggested by (Durugbo et al., 2010). On the other hand, Spiniferites elongatus 

were low in occurrence or absent in the wells (Wall et al., 1977, Vesteegh, 1994). 

The documentation of Homotryblium floripes (Deflandre and Cookson) Stover in these Middle –Late Miocene 

western Niger Delta sediments agrees with its reported occurrence in other parts of the world. Again, Haq et 

al., (1987) had included the FADs of species such as Homotryblium plectilum, Systematophora placacantha, 

Unipontidinium aquaeductum, Cordosphaeridium cantharellum within the Late Early – Late Miocene some of 

which were recovered in the present study. Furthermore, Powell (1992) had also incorporated Achomosphaera 

andalousiensis, Unipontidinium aquaeductum among others in his Miocene zonation schemes. Generally, 

except for Achomosphaera andalousiensis, the other dinocysts were long ranging and unsuitable for age 

379


designation. The assemblages of wells BA and BB appear similar to dinoflagellage suites from Miocene epochs 

in Japan, Denmark, Germany, northwestern Europe, Canada and the Atlantic coast of North America (Lenoir 

and Hart, 1986). 

Peridiniaceans dominated the wells BA and BB assemblages (Durugbo, 2010), while gonyaulaceleans 

dominated the organic walled microfossils in wells BC and BD. The assemblages were dominated by 

Polysphaeridium zoharyi and Operculodinium centrocarpum which were concentrated at some intervals. 

Durugbo et al. (2010) had associated this dominance of the two species to lowered sea levels resulting from 

glacial maxima. This concurs with the reports of Schepper (2009) who having worked with Pliocene- 

Pleistocene sediments from DSDP Hole 610A Eastern North Atlantic reported the dominance of 

gonyaulacoids, while the abundance of peridinoids was low. Possibly the same conditions prevailed from the 

North down to the South Atlantic during the Early Pliocene to Early Pleistocene. The paucity of peridiniaceans 

in the wells BC and BD could have arisen from the high salinity levels associated with lowered sea levels 

(Udeze and Oboh-Ikuenobe, 2005). This lowered sea level was further corroborated by the common records of 

the acritarch Leiosphaeridia spp. which Dorning, (1980) and Guerra, (1996) had associated with shallow 

waters. 

This study highlights the first documented occurrence of Achomosphaera andalousiensis in the Niger Delta. 

The LDO of this species in the palynological zone P780 in the wells BA and BB close to the 11.6Ma, is 

noteworthy. Wrenn and Kokinos (1986) had also reported its presence in the Gulf of Mexico Neogene. Head 

and Wrenn (1992) had attributed a preference for warmer waters to A. andalousiensis based on these reports of 

Wrenn and Kokinos (1986) and its rarity within this period in the Labrador sea (Head et al., 1989). The 

common records of Achomosphaera andalousiensis appears to concur with the earlier suggestions of Head et 

al. (1989a) that it prefers relatively warm waters based on the reports of de Vernal and Mudie (1989a) who 

associated it with warm interglacial isotopic intervals in the Labrador Sea though Harland (1988) had linked it 

to cold glacial stages in the offshore. It was more common in the wells BC and BD and had spot records in the 

Middle-Late Miocene sections of wells BA and BB. Mudie (1987) had reported its abundance in the relatively 

warm latest Miocene and earliest Pliocene sediments in the North Atlantic which agrees with the results from 

the Western Niger Delta. Again, the Early Pliocene – Early Pleistocene sections of wells BC and BD were 

characterized by common records of Spiniferites spp.(S. bentorii, S. ramosus, S. elongatus, S. mirabilis, S. 

hyperacanthus), Operculodinium spp., Achomosphaera andalousiensis, A. ramulifera, Tuberculodinium 

vancampoae, Brigantedinium spp., Bitectatodinium spp., Tectatodinium pellitum, Hystrichokolpoma rigaudiae, 

Impagidinium spp., Batiacasphaera spp., and Invertocysta lacrymosa, which appeared among those listed by 

Schepper and Head (2009) in their review of Plio-Pleistocene assemblages from different parts of the world. 

The other species not encountered in the Western Niger delta could have arisen from environmental differences 

brought about by the review of sediments from varying latitudes. 

Generally, the Miocene sections of the Western Niger Delta assemblage appear similar to that reported for the 

Lower Tagus Basin in Portugal by Castro et al. (2008). Although in the older Early Miocene (Burdigalian) 

sections they recovered Polysphaeridium zoharyi, Cleistosphaeridium placacanthum, and Cribroperidinium 

tenuitabulatum. In the Langhian they reported abundant records of C. tenuitabulatum with common 

Polysphaeridium zoharyi and Operculodinium israelianum, while in the Serravallian, they encountered 

frequent Spiniferites spp., Spiniferites/Achomosphaera, O. Israelianum, Hystrichosphaeropsis obscura, and 

Lingulodinium machaerophorum. Furthermore, in the Tortonian, Spiniferites/Achomosphaera, S. 

pseudofurcatus, L. machaerophorum Homotryblium spp. were common. These all occurred with common 

peridinoids (Selenopemphix nephroides, S. brevispinosa and Lejeunecysta sp.) with the acritarchs Cyclopsiella 

granosa and Quadrina sp. All these species especially from the Langhian to the Tortonian were similar to those 

recovered in this study, especially in wells BA and BB except for the acritarchs Cyclopsiella granosa and 

Quadrina sp. 

CONCLUSIONS 

The dinoflagellate cysts recovered from this study offers the promise of erecting a dinocyst biozation for the 

Western Niger Delta after further studies. Achomosphaera andalousiensis documented for the first time in the 

Niger Delta whose LDO occurred close to the 11.6Ma in wells BA and well BB, appeared a notable event that 

needs further confirmation together with the occurrences of the Homotryblium species in the Middle Miocene 

380


of the Niger Delta. There is therefore an urgent need for more intensive studies which together with the 

conventional pollen and spores would be useful where the other microfossil groups are scarce. 

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384


LIST OF FIGURES, PLATES AND TABLES 

Fig. 1. Map of the Niger Delta showing the location of studied wells after Doust and Omatsola, 1990. 

Plates 1-6. Photomicrography of the dinoflagellate cysts recovered in the studied wells with the Authority, well 

sample and England Finder coordinates of the dinoflagellate cysts. 

All magnifications X400, Except Plate 2 # 10 = X1000 

TABLES 1 - 4 

Table 1: Distribution of dinoflagellate cysts and marine elemnts by sample depths in Well BA 

Table 2: Distribution of dinoflagellate cysts and marine elemnts by sample depths in Well BB 

Table 3: Distribution of dinoflagellate cysts and marine elemnts by sample depths in Well BC 

Table 4: Distribution of dinoflagellate cysts and marine elemnts by sample depths in Well BD 

PLATE 1 

1 2 

3 

4 

5 6 7 8 

385


9 

10 11 12 

13 

14 

15 16 

PLATE 2 

1 2 

3 

4 

386


5 6 

7 

8 

9 

10 

11 

12 

13 14 

15 

16 

PLATE 3 

1 2 

3 

4 

387


5 

6 

7 

8 

9 

10 

11 

12 

13 

14 

15 

16 

PLATE 4 

1 2 

3 

4 

388


5 6 

7 

8 

9 

10 

11 12 

13 

14 

15 

16 

PLATE 5 

1 2 

3 

4 

389


5 

6 

7 

8 

9 

10 11 12 

13 

14 

15 

16 

PLATE 6 

390


1 

2 

3 

4 

5 

6 

7 

8 

9 

10 

0 

11 

12 

13 

14 

15 

16 

10µm 

Names of the dinoflagellate cysts recovered in the wells showing well, sample depth and England Finder location 

PLATE 1 

1. Nematosphaeropsis labyrinthus (Ostenfeld 1903); Reid 1974); Well BB(5050-5140) Q22/3 

2. Microforaminiferal Wall Linings Well BB (5500-5590)V38/2 

391


3. Tuberculodinium vancampoae (Rossignol,1964);Well BC(5910-6020ft) D32/4 

4. Dinogymnium euclaense (Evitt, Clark and Verdier 1967); Well BC (6000-6090ft) G29/0 

5. Lingulodinium machaerophorum (Deflandre and Cookson 1955); Well BA( 10980-11070ft) G28/4 

6. Systematophora cf. ancryea (Cookson and Eisenack 1965); Well BC(3660-3750ft) T33/2 

7. Spiniferites ramosus(Deflandre and Cookson,1955)Cookson and Eisenack 1974;Well BC 

(4650-4740ft) T43/4 

8. Sumatradinium sp.Well BA(4050-4140ft) K19/4 

9. Tasmanites sp. Well BB (4960-5050ft) N31/2 

10. Cordosphaeridium cantharellum(Brosius,1963); Well BB(4960-5050ft) R46/0 

11. Achomosphaera sp. Well BC (9860-9950ft) P45/2 

12. Operculodinium centrocarpum (Deflandre and Cookson,1955) Wall 1967;Well BB(4960-5050ft) D43/2 

13. Polysphaeridium zoharyi (Rossignol 1964); Well BC (1980-2040ft) O34/4 

14. Lingulodinium machaerophorum (Deflandre and Cookson 1955); Well BC (6090-6180) F38/4 

15. Achomosphaera andalousiensis(Jan du Chêne, 1977) emend Jan du Chêne and Londeix,1988; 

Well BC(4650-4740ft) K33/3 

16. Muderongia sp. Well BC (8160-8250ft) T37/4 

PLATE 2 

1. Achomosphaera ramulifera (Deflandre, 1937) Evitt 1963; Well BB (4690-4780ft) C35/4 

2. Impagidinium sp. (Stover and Evitt, 1978, Harland,1983);Well BC(6180-6270ft) O42/1 

3. Lingulodinium cf. sadoense (Deflandre and Cookson 1955): Well BD(7650-7740FT)V34/4 

4. Hystrichokolpoma rigaudiae (Deflandre and Cookson 1955); Well BA(9460-9550ft)G33/1 

5. Achomosphaera ramulifera (Deflandre 1937) Evitt 1963;Well BD( 3780-3870ft) P27/3 

6. Hystrichokolpoma cf. cinctum (Deflandre and Cookson, 1955); Well BA(6750-6840ft)C34/1 

7. Spiniferites hyperacanthus (Deflandre and Cookson,1955) Cookson and Eisenack 1974; 

Well BD(5400-5490ft)C31/4 

8. Homotryblium pallidum (Davey and Williams 1955); Well BA(10530-10620ft) Q43/1 

9. Spiniferites mirabilis (Rossignol 1963) Sarjeant 1970; Well BA (3960- 4050ft) J38/2 

10. Spiniferites mirabilis showing the extension 

11. Microforaminiferal Wall Linings Well BB (5500-5590ft) H24/1 

12. Achomosphaera andalousiensis (Jan du Chêne, 1977) emend Jan du Chêne and Londeix,1988; 

Well BA (3880-3970ft) F29/1 

13. Operculodinium israelianum(Rossignol,1962) Wall 1967; Well BC(1980-2040) J41/0 

14. Tuberculodinium vancampoae (Rossignol,1964); Well BC(1980-2040ft) G32/1 

15. Brigantedinium cf. cariacoense (Wall) Reid 1977; well BC (5100-5190 ft) K31/4 

16. Polysphaeridium zoharyi(Rossignol 1964); well BD (8370-8460 ft) C36/4 

PLATE 3 

1. Hystrichokolpoma rigaudiae (Deflandre and Cookson, 1955); Well BA(9630-9720ft) E38/2 

2. Sumatradinium spp. Well BA(7390-7480ft) N30/2 

3. Homotryblium cf. vallum(Drugg and Loeblich,Jr. 1967) Well BA(4590-4680) M44/3 

4. Nematosphaeropsis labyrinthus (Ostenfeld 1903); Reid 1974); Well BA(7830-7920 ft) E41/3 

5. Cf .Unipontidinium aquaeductum Well BA(11160 -11250ft) P23/2 

6. Polysphaeridium zoharyi (Rossignol 1964) Well BB(4960-5050ft) D43/2 

7. Lingulodinium machaerophorum(Deflandre and Cookson 1955)Well BA(10440-10530ft)N29/1 

8. Operculodinium centrocarpum (Deflandre and Cookson,1955) Wall 1967;Well BA(10800-10890 ft) Y32/2 

9. Homotryblium plectilum((Drugg and Loeblich,Jr. 1967) Well BA(7830-7920)Q48/1 

10. Sumatradinium sp. Well BB(4690-4780ft)D40/2 

11. Operculodinium israelianum (Rossignol,1962) Wall 1967;Well BD(3690-3780 ft) R30/0 

12. Tectatodinium pellitum(Wall 1967); Well BC(5460- 5550ft)O19/1 

13. Spiniferites bulloideus (Deflandre & Cookson 1955) Sarjeant 1970;Well BD(5400-5490) C19/4 

14. Spiniferites bulloideus (Deflandre & Cookson 1955) Sarjeant 1970; Well BD(4860-4950) J37/2 

15. Impagidinium sp. (Stover & Evitt, 1978, Harland,1983); well BC (5640-5730ft) G27/2 

16. Spiniferites sp. Well BA (11770- 11790 ft) R17/4 

PLATE 4 

392


1.Spiniferites hyperacanthus (Deflandre & Cookson,1955) Cookson & Eisenack 1974; 

Well BD(4590-4680) N25/4 

2.Impagidinium sp. (Stover & Evitt, 1978, Harland,1983); Well BD(4590-4680) L39/4 

3.Spiniferites bentorii (Rossignol 1964) Wall & Dale 1970; Well BD(5170-5260) M28/2 

4.Nematosphaeropsis labyrinthus (Ostenfeld 1903, Reid 1974) Well BD(5760-5850) O31/3 

5.Tuberculodinium vancampoae(Rossignol,1964); well BD(4680-4770) M44/1 

6.Spiniferites hyperacanthus(Deflandre & Cookson,1955) Cookson & Eisenack 1974); 

Well BD (4770-4860) W22/3 

7.Impagidinium sp. (Stover & Evitt, 1978, Harland,1983); Well BD(7830-7920) P22/3 

8.Melitasphaeridium choanophorum (Deflandre & Cookson,1955) Harland and Hill, 1979; 

Well BB(4960-5050) R46/0 

9.Spiniferites cf. rubinus Well BC(3970-4060) K33/1 

10. Impagidinium sp. (Stover & Evitt, 1978, Harland,1983); Well 

11. Operculodinium centrocarpum(Deflandre & Cookson,1955) Wall 1967; Well BD(3780-3870) S38/3 

12. Tuberculodinium vancampoae(Rossignol 1964); Well BC(5730-5820) U32/2 

13. Spiniferites delicatus(Reid 1974); Well BD(3780-3870) T39/1 

14. Polysphaeridium zoharyi(Rossignol 1964); well BC(5010-5100) S20/4 

15. Spiniferites hyperacanthus (Deflandre & Cookson,1955) Cookson & Eisenack 1974; 

Well BC (5100-5190) K31/4 

16. Systematophora sp. Well BA(7920-8010ft) R50/4 

PLATE 5 

1. Hystrichokolpoma rigaudiae (Deflandre and Cookson, 1955) Meren-66(9630-9720) E38/2 

2. Impagidinium sp. (Stover & Evitt, 1978, Harland,1983);Well BD(5670-5760ft)T45/3 

3. Operculodinium centrocarpum (Deflandre & Cookson,1955) Wall 1967; well BA 

(10980-11070 ft)L38/4 

4. Achomsphaera ramulifera (Deflandre 1937) Evitt 1963; Well BC(4650-4740ft)T19/1 

5. Spiniferites bentorii (Rossignol 1964) Wall & Dale 1970;well BD(7650-7740) P30/1 

6. Homotryblium cf. plectilum( Drugg and Loeblich,Jr. 1967) Well BA(4590-4680) M44/3 

7. Spiniferites ramosus (Ehrenberg,1838) Mantell, 1854);well BC(6630-6720)G33/3 

8. Spiniferites cf. tripodes (Morzadec-Kerfourn 1966) Lentin & Williams 1973; 

Well BA (11610-11700) F24/3 

9. Hystrichokolpoma rigaudiae (Deflandre and Cookson, 1955); Well BA(11700-11770) P39/1 

10. Spiniferites cf. pseudofurcatus (Klumpp1953) Sarjeant 1970; Well BA(11520-11610 ft) V35/1 

11. Tuberculodinium vancampoae(Rossignol,1964); Well BA(4050-4140ft) L21/2 

12. Achomosphaera sp. well BA (10440-10530 ft) C36/4 

13. Wallodiniuum sp. Well BA(8100-8190) W41/1 

14. Spiniferites cf bentorii Well BC(10400-10490ft) M28/4 

15. Odontochitina cf. costata Well BC(3160-3250ft) K33/1 

16. Homotryblium cf. vallum(Drugg and Loeblich,Jr. 1967) Well BA(4590-4680ft) M44/3 

PLATE 6 

1. Nematosphaeropsis lemniscata(Bujak 1984 emend Wrenn 1988); Well BD(3780-3870ft) R19/2 

2. Cf. Operculodinium cenrocarpum (Deflandre & Cookson,1955) Wall 1967;Well BC 

(1980-2040ft) N26/1 

3. Spiniferites sp. Well BC(1980-2040ft) L21/2 

4. Polysphaeridium zoharyi(Rossignol 1964); Well BD (8370-8460 ft) C36/4 

5. Spiniferites bentori (Deflandre & Cookson,1955) Wall 1967; Well BD(3290-3380ft) N47/2 

6. Spiniferites delicatus (Ehrenberg,1838) Mantell 1854);Well BD ( 3780-3870ft) T39/1 

7. Spiniferites mirabilis (Rossignol 1963) Sarjeant 1970; Well BC(5640-5730ft) K37/4 

8. Lingulodinium machaerophorum(Deflandre and Cookson 1955);Well BC (7080-7170) U18/3 

9. Leiosphaeridia sp. Well BC(6000-6090ft) H31/4 

10. Spiniferites membranaceus (Rossignol 1963) Sarjeant 1970; Well BC(6090-6180ft) L37/4 

11. Spiniferites ramosus (Ehrenberg,1838) Mantell, 1854); Well BD(4140-4200 ft) X39/2 

12. Systematophora sp. Well BA(11340-11430) 024/1 

13. Glaphyrocysta sp. Well BA(11070-11160) T36/3 

14. Polysphaeridium zoharyi(Rossignol 1964); 

393


15. Systematophora sp. Well BA(10980-11070ft) F18/2 

16. Protoperidinium sp. well BA(6630-6720) Y43/3 

All magnifications X400, Except Plate 2 # 10 = X1000 

394



ISSN 1943-2429 


ESTIMATED SHRINKAGE OF ONE-STAGE OF COBB-DOUGLAS PRODUCTION 

FUNCTION 

ADEEB AHMAD ALI ALRAHAMNEH* and OMAR HAWAMDEH 

Faculty of Planning & Management / Al-Balqa Applied University 

*Email address for correspondence: moheeb9820052@yahoo.co.uk 

_________________________________________________________________________________________ 

Abstract: This study aims at calculating the amount of bias for the estimated shrinkage ( ~ ) and the estimated 

shrinkage ( ~ ), calculating the Mean of Squares Error( MSE ) for estimator shrinkage ( ~ , ~ ) , and calculating 

the Relative Efficiency ( RE ) for the estimated ( ~ ) and ( ~ ) with respect to the two estimated ~ and the ~ 

~ 

and finally finding K value that makes MSE ( ) and MSE (~ 

) minimization , the study find that the 

~ 

relative efficiency for the estimated ( , 

~ ) 

have a high relative efficiency with respect to the mixed estimation 

method , and it suggests a way to produced the lowest Mean Squares Error , the study gives a the lowest 

MSE and the biggest relative compared with the mixed estimation method . 

~ 

Key Words: Estimated Shrinkage ( ( , 

~ ) , Mean Square Error, Mixed Estimation, One-stage of Cobb-Douglas 

Production Function, Relative Efficiency. 

__________________________________________________________________________________________ 

INTRODUCTION 

All research in the production functions based on the proposition that the production operations can be made 

better using the a homogenous linear function and by the elasticity of replacing some of the elements, this is the 

first trial in 1916 don by the economic (K.Wickesll) (6) who use the mathematical function that represent the 

relationship between inputs and outputs. This function takes the name when the mathematical scientist (Coob 

1928) and the economic scientist (Douglas 1928). 

David Dumad (1937) precedes the application of the formula which was created by Zellner ,A.(1961, p. ) and 

Wu, DE-MIN (1975) : 

Q 

2 

1 

ut 

t 

0 

Lt 

Kt 

e 

… (1) 

Set: 

Q t: The amount or the value of the production in a specific period. 

L t: The labor measured by the average of the of workers in a specific period 

K t: The fixed capital measured by the total value of the fixed asset in a specific period 

395


0 : Efficient Coefficient 

1 : The production elasticity with proportion to the labor element 

2 : The production elasticity with proportion to the capital element 

u 

2 

t : The random error that distributed normally with a zero mean and u variance. 

The estimated shrinkage with one stage calculated by the following formula (4, 5) : 

~ 

( ˆ) ˆ [1 

( ˆ)] 0 

… (2) 

ˆ : An estimated calculated from a small sample by one of the classical ways 

: Represent prior information about parameter which must estimated as Initial Value 

0 

(ˆ) : A balanced shrinkage function can be constant or variable 0 

( ˆ) 1 

~ : An estimated shrinkage has one stage and it is a linear formula contains the initial 

information 0 and the classical estimatorˆ . 

Objective of the study: The study aims to calculating the following: 

1. Calculating the amount of bias for the estimated shrinkage ( ~ ). 

2. Calculating the amount of bias for the estimated shrinkage ( ~ ). 

3. Calculating the mean error squares for estimator shrinkage ( ~ ). 

4. Calculating the mean error squares for estimator shrinkage ( ~ ). 

5. Calculating the relative efficient for the estimated ( ~ ) and ( ~ ) with respect to the two estimated ~ 

and the ~ which can be calculated by (RLS) method . 

~ 

6. Finding K value that make MSE( 

) and (~ 

) 

The mathematical explanation: 

If the estimated shrinkage functions ) 

~ 

 

Set: 

K ˆ (1 K) 

 

… (3) 

0 

MSE at the least. 

(ˆ fixed functions have amount K, which0 K 1 

then: 

K: Represents the balanced fixed shrinkage function, it’s amount of confidence from the classical estimated ˆ , 

(K-1) represent the amount of confidence from the prior information 

0 

1 ( ˆ) 1 K , ( 

ˆ ) 

K 

for the parameter which mean (4,5) : 

For estimating the function parameter ( 1and 2 ) it must convert the (1) function to the leaner form by 

finding (Ln) for both function sides: 

LnQ 

t 

Ln ( 0 ) 1 Ln Lt 

2 Ln Kt 

ut 

……. (4) 

Propose: 

Ln 0 Ln 

, 1 

, 2 

 

The function (4) can be written as the following: 

LnQ 

t 

Ln 

Ln Lt 

Ln Kt 

ut 

… (5) 

396


The amount of shrinkage with one stage for parameter as the following: 

~ 

 

~ 

 

ˆ 

K 

(1 K) 

0 

… (6) 

K ( ˆ 0 ) 0 

… (7) 

The solution steps as the following: 

1. Estimating regression model parameter and using the ordinary least squares (OLS) and adopting it as 

an initial values , ) . 

( 0 0 

2. Estimating regression model parameter and using the mixed estimation method (MEM) and adopting it 

as initial values , ) . 

( 0 0 

Mixed Estimation Metho )MEM( : 

The Mixed Estimation Method is one of the restricted regression models which will be explained to employee 

the initial information is an Inequality Restriction. This way include the combination between the initial 

information or that devised from out the sample and it provided from the secondary data or from the economic 

theories. The most important thing in the (MEM) (9,10) use is that it is primary or the spatial information gives a 

specific range that specified by the biggest probability that include the real value of the requested parameter, 

taking that this range is compatible with the economic theory kind for the studied phenomenon (8) : 

The estimation wave (b mem ) can be calculated as the following (1, 2, 3) : 

2 

T T 1 

1 

2 

T T 1 

b [ X X R G R] 

[ X Y R G r] 

… (8) 

mem 

Set: 

r : a known vector has the (j x 1) rank. 

R: constrains matrix has the (j x (k +1)) rank. 

: The parameter vector that has [(k + 1) x 1] rank. 

V: The random error vector has (j x 1) rank. 

And: 

E( 

v) 

0 , E( 

vv ) G 

Set: 

T 

G: The variance and the combined variance matrix for the previous estimators. 

To explains that we suppose the previous information include tow unbiased estimators (b 1 ,b 2 ) for ( 1 , 2) 

respectively, if the variance of this estimators S 11 ,S 22 and the combined variance S 12 , it will be as the 

following (1,2,37,11) : 

b1 

 

r 

b2 

 

S 

G 

S 

11 

12 

1 

, R 

0 

S12 

 

S 

 

22 

0 

1 

0 

0 

. 

. 

. 

. 

0 

0 

 

 

397


1. Calculating one stage shrinkage estimator using a fixed shrinkage function as the following: 

~ 

( ˆ 

~ K 0 

… (9) 

K ( ˆ 

… (10) 

Set: 

0 ) 

0 ) 

ˆ ~ N [ , 

Var( 

ˆ)] 

ˆ ~ N [ , Var( 

ˆ) ] 

0 

For calculating the bias of estimated shrinkage ~ : 

~ 

~ 

Bias ( ) E ( ) 

~ 

ˆ 

Bias ( ) E [ K( 

0 ) 0 ] 

~ 

ˆ 

Bias ( ) K E( 

0 ) E( 

0 

) 

 

 

K ( ˆ ) ( ˆ) ˆ ( ) ( ˆ) ˆ 

0 f d 

0 f d 

… (11) 

 

 

 

1 ˆ 2 

ˆ 

( ) 

 

K ( ). 

. 

ˆ 

0 Exp 

d 

 

2Var( 

ˆ) 

K 

 

 

 

 

( ) 

 

K 

 

 

 

2 

V ( ˆ) 

1 ˆ 2 

( ) 

Exp 

2 

Var( 

ˆ) 2Var 

( ˆ) 

 

 

 

0 d 

( ˆ ). 

 

 

ˆ 

… (12) 

 

ˆ 2 

1 

( ) 

 

Exp 

2 

Var ( ˆ) 

2Var 

( ˆ) 

0 d 

 

1 ˆ 2 

( ) 

 

ˆ 

( 0 ). 

Exp 

d 

 

2 

Var ( ˆ) 2Var 

( ˆ) 

 

 

… (13) 

 

 

( ˆ ). 

1 ˆ 2 

( ) 

Exp d ˆ K 

2 

Var ( ˆ) 

2Var 

( ˆ) 

 

1 ˆ 2 

( ) 

Exp d ˆ 

2 

Var ( ˆ) 

2Var 

( ˆ) 

 

ˆ 2 

( ) 

Exp d ˆ 

2Var 

( ˆ) 

 

...(15) 

 

 

 

( ). 

ˆ 2 

( ) 

Exp d ˆ ...(14) 

2Var 

( ˆ) 

 

 

1 ˆ 2 

ˆ 

( ) 

K ( ). 

ˆ 

 

Exp d 

( K 1) 

2 

Var( 

ˆ) 

2Var 

( ˆ) 

 

0 

 

 

 

( ) 

1 

0 

2 

Var ( ˆ) 

 

 

 

( ) 

0 

ˆ 

1 

2 

Var( 

ˆ) 

398


Suppose: 

Z 

 

Then: 

ˆ 

Var ( ˆ) 

, Z 

~ 

N(0,1) 

Z Var ( ˆ) ˆ 

Var ( ˆ) dZ d ˆ 

Suppose: 

 

 

0 

Var ( ˆ) 

Then: 

~ 

Bias ( ) K Var ( ˆ) 

( K 1) 

( K 1) 

Var ( ˆ) 

Var ( ˆ) 

 

 

 

~ 


 

 

 

~ 


. 

 

 

 

ˆ 

ˆ 2 

( ) 1 

( ) 

. 

Exp d ˆ 

Var ( ˆ) 2 

Var ( ˆ) 

2Var 

( ˆ) 

 

ˆ 2 

( ) 1 

0 

( ) 

. 

Exp d ˆ ...(16) 

Var ( ˆ) 2 

Var( 

ˆ) 

2Var 

( ˆ) 

 

 

 

 

 

 

 

Z 

2 

1 

Exp 

Var( 

ˆ) 

1 

Exp 

2 

Var( 

ˆ) 

1 

Z e 

2 

2/ 2 

Z 

 

Z 

2 / 2 

 

Var( 

ˆ) dZ 

2 

 

Z 2 / Var( 

ˆ) dZ ...(17) 

dZ ( K 1) 

Var ( ˆ) 

~ 

Bias( ) K Var ( ˆ) E( 

Z) 

( K 1) 

Var ( ˆ) 

~ 

Bias( ) ( K 1) 

Var( 

ˆ) 

… (19) 

 

 

 

1 

e 

2 

2/ 2 

Z 

dZ 

...(18) 

By the same way the bias for estimator ~ : 

Bias ( ~ ) ( K 1) 

Var ( ˆ) 

- 

… (20) 

- To calculate the mean error squares for estimator shrinkage ( ~ ) 

~ ~ 2 

MSE ( ) E( 

) 

~ 

MSE ( ) EK 

( ˆ 2 

0 ) 0 

 

~ 

MSE ( ) EK 

( ˆ 

2 

0 ) ( 0 

) 

~ 2 

2 

( ) K E( 

ˆ ) 2KE( 

ˆ )( ) E( 

 

2 

MSE 0 

0 0 

0 ) … (21) 

399


400 

2 

0 

0 

0 

2 

0 

2 

) 

( 

) 

ˆ 

( 

) 

( 

2 

) 

ˆ 

( 

) 

~ 

( 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

E 

E 

K 

E 

K 

MSE 

2 

0 

2 

0 

0 

0 

2 

2 

0 

2 

2 

) 

( 

) 

( 

2 

) 

ˆ 

( 

) 

( 

2 

) 

)( 

ˆ 

( 

2 

) 

( 

) 

ˆ 

( 

) 

~ 

( 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

E 

KE 

E 

K 

E 

K 

E 

K 

K E 

MSE 

2 

2 

0 

2 

2 

0 

2 

) 

ˆ 

( 

) 

ˆ 

( 

). 

)( 

2 

(2 

) 

( 

1) 

2 

( 

) 

~ 

( 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

E 

K 

E 

K 

K 

E 

K 

K 

MSE 

2 

2 

0 

2 

0 

2 

) 

ˆ 

( 

) 

ˆ 

( 

) 

1)( 

( 

2 

) 

( 

1) 

( 

) 

~ 

( 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

E 

K 

E 

K 

K 

E 

K 

MSE 

 

 

 

 

 

 

 

 

 

 

 

 

ˆ 

ˆ) 

( 

) 

( 

) 

( 

2 

0 

2 

0 d 

f 

E … (22) 

 

 

 

 

 

 

 

 

 

 

ˆ 

ˆ) 

( 

2 

) 

ˆ 

( 

ˆ) 

( 

2 

1 

. 

) 

( 

) 

( 

2 

2 

0 

2 

0 d 

Var 

Exp 

Var 

E 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

… (23) 

 

 

 

 

 

 

 

 

 

 

 

 

ˆ 

ˆ) 

( 

2 

) 

ˆ 

( 

ˆ) 

( 

2 

1 

. 

ˆ) 

( 

) 

( 

ˆ) 

( 

) 

( 

2 

2 

0 

2 

0 d 

Var 

Exp 

Var 

Var 

Var 

E 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

dZ 

Var 

e 

Var 

Var 

E 

Z 

 

 

 

 

 

) 

ˆ 

( 

ˆ) 

( 

1 

2 

1 

ˆ) 

( 

) 

( 

2 

2/ 

2 

2 

0 

 

 

 

 

 

 

 

 

 

 

 

 

dZ 

e 

Var 

E 

Z 2 

2/ 

2 

1 

ˆ) 

( 

) 

( 

2 

2 

0 

 

 

 

 

 

ˆ) 

( 

) 

( 

2 

2 

0 

 

 

 

Var 

E 

 

… (24) 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

ˆ 

ˆ) 

( 

) 

)( 

ˆ 

( 

) 

)( 

ˆ 

( 0 

0 d 

f 

E … (25) 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

ˆ 

ˆ) 

( 

2 

) 

ˆ 

( 

ˆ) 

( 

2 

1 

) 

)( 

ˆ 

( 

) 

)( 

ˆ 

( 

2 

0 

0 d 

Var 

Exp 

Var 

E 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

ˆ 

ˆ) 

( 

2 

ˆ) 

( 

ˆ) 

( 

2 

1 

ˆ) 

( 

) 

( 

ˆ) 

( 

) 

ˆ 

( 

ˆ) 

( 

) 

)( 

ˆ 

( 

2 

0 

0 d 

Var 

Exp 

Var 

Var 

Var 

Var 

E 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

dZ 

Var 

e 

Var 

Z 

Var 

E 

Z 

 

 

 

 

 

 

) 

ˆ 

( 

ˆ) 

( 

1 

2 

1 

ˆ) 

( 

) 

)( 

ˆ 

( 

2 

2 / 

0 

 

 

 

 

 

 

 

 

dZ 

e 

Z 

Var 

E 

Z 

 

 

 

 

 

 

 

2 

2/ 

2 

1 

ˆ) 

( 

) 

)( 

ˆ 

( 0 

 

 

 

 

 

 

 

Zero 

Z 

E 

Var 

E 

 

 

 

) 

( 

ˆ) 

( 

) 

)( 

ˆ 

( 0 

 

 

 

 

… (26) 

 

 

 

 

 

 

 

 

 

 

 

 

ˆ 

ˆ) 

( 

) 

ˆ 

( 

) 

ˆ 

( 

2 

2 

d 

f 

E 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

ˆ 

ˆ) 

( 

2 

) 

ˆ 

( 

ˆ) 

( 

2 

1 

) 

ˆ 

( 

) 

ˆ 

( 

2 

2 

2 

d 

Var 

Exp 

Var 

E … (27)


E ( ˆ ) 

2 

Var( 

ˆ) 

 

 

 

 

 

 

( ˆ ) 

Var ( ˆ) 

2 

2 

1 

( ˆ ) 

Exp 

Var( 

ˆ) 

2Var( 

ˆ) 

E ˆ 2 

2 1 1 Z 

2 / 2 

( ) Var( 

ˆ) Z 

e Var( 

ˆ ) dZ 

2 

Var( 

ˆ) 

E( 

ˆ ) 

2 

Var( 

ˆ) 

 

 

 

Z 

2 

1 

e 

2 

Z 

2 / 2 

dZ 

ˆ 2 

2 

E( 

) 

Var ( ˆ) E( 

Z ) Var( 

ˆ) 

~ 

2 2 

MSE( 

) ( K 1) 

Var( 

ˆ) 2K( 

K 1)( 

Zero) 

K 

~ 

2 2 

2 

MSE( 

) ( K 1) 

Var( 

ˆ) K Var( 

ˆ) 

~ 

2 2 2 

MSE( ) Var( 

ˆ) ( K 1) 

K 

… (28) 

 

 

2 

Var( 

ˆ) 

… (29) 

2 

 

d ˆ 

 

By the same way the mean error squares for estimator shrinkage ( ~ ) can be yielded by the following function: 

MSE( ~ ) 

K 

 

2 2 2 

Var( ~ ) ( K 1) 

 

… (30) 

 

The relative efficient for the estimated ~ and ~ for the estimators ˆ and ˆ which can be calculated by 

Restricted Least Square method (RLS): 

~ MSE( ˆ) 

R. 

E( 

) ~ 

MSE( 

) 

~ Var( 

ˆ) 

R. 

E( 

) 

2 2 

Var( 

ˆ) ( 

K 1) 

K 

~ 

2 2 2 

R. 

E( 

) ( 

K 1) 

K 1 

( ˆ) 

( ~ MSE 

R. 

E ) 

MSE( ~ ) 

( ˆ) 

( ~ Var 

R. 

E ) 

2 2 

Var( ~ ) ( K 1) 

K 

R. 

E( ~ ) 

2 

 

… (31) 

 

2 2 2 

( 

K 1) 

K 1 

2 

 

… (32) 

To calculate K value that make ( ) 

squares calculated for K and equaling it to 0: 

~ 

MSE and (~ 

) 

MSE the least, the first derivative for the mean error 

~ 

MSE( ) 

2 

2( K 1) 

Var( 

ˆ) 2K Var( 

ˆ) 

K 

~ 

MSE( 

) 

0 

K 

401


2 

2( K 1) 

Var( 

ˆ) 2KVar( 

ˆ) 0 

2 

2 

K 

Var( 

ˆ) KVar( 

ˆ) Var( 

ˆ) 

2 

ˆ 2 

K 

K Var 

Var( 

ˆ ) 

2 

K ( 1) 

 

2 

2 

K … (33) 

 

 

 

2 

1 

2 ~ 

MSE( ) 2 

2 

Var( 

ˆ) 2Var( 

ˆ) 0 

2 

K 

Is minimization 

RESULTS AND RECOMMENDATION 

Table (1) and (2) show the following: 

~ 

1. The unbiased values for the one stage shrinkage estimator ( , 

~ ) increase and then start decreasing until 

the real value of the parameter equals or closed to equal the initial value. 

~ 

2. The mean square error (MSE) for the one stage shrinkage estimator ( , 

~ ) decrease until the real value of 

parameter equals or closed to initial value and the mean standard error increase as a result the parameter 

real value shifting away from the initial value. 

~ 

3. The proposed real efficient (R.E) for the one stage shrinkage estimator ( , 

~ ) have a high proportion 

efficiency for the mixed estimation method, and the proposed method results the lowest mean square error 

and the highest relative efficiency compared with the mixed estimation method. 

4. The study recommends the use of one stage shrinkage estimator in the Coob-Douglas functions for 

calculating the utilization proportion of labor and the fixed capital percent in the production functions 

analysis generally. 

REFERENCES 

Al Salihi .F.Zeanab (1992). The Equality and Inequality Constrains in the regression analysis: Applied 

study for the consumption function in Iraq, Master thesis. Baghdad University. 

Al-Dowiri. M. Yasean(1989). The use of Mixed Method in the Production Estimation :Applied study in the 

Iraq Transformation Industry .Master thesis. Baghdad University. 

Al-hasnawi, Shleabih, and Amouri H. Kathem.(2002)The Advance Economical Scaling, Donya Library. 

Bagdad. 

Alknani,I.Hasan,(2000). The One and Tow Stage Estimated Shrinkage for the Regression Analysis. 

Doctoral Dissertation. Baghdad University. 

Al-Obiedee, A. Abed Alrazaq.(2000). The Use of Estimated Shrinkage for Solving Problems in The 

Heterogeneous Variance of Linear Regression. Master thesis. Baghdad University. 

Mohalhil.M.Abas. (1983).The Union Economic Theory, Dar Al-Mareak, Al-Read. 

Fadeal.R. Hasan(1985) .Using of Estimation Restricted Models for Expenditure Functions In Iraq.Master 

thesis. Baghdad University. 

402


Koutsoyinnis A.Theory of Econometrics. The Macmillan Press, London, 1979. 

Lajda P.(1981) “Short Term Operation Planning Electric Power System J. of Operation Resr, Vol.32. 

Nagar A.L. & KaKwani, N.C (1964) “The bias and moment matrix of a mixed regression estimators, 

Econometrica. 

Theil, H.(1971) “ Principles of Econometrics” –15, New York, Wiley. 

Wu, DE-MIN (1975),” Estimation of Cobb-Douglas production function Econometrica” Vol. 43, No. 4. 

Zellner ,A.(1961), “ Linear Regression with (37) inequality Constraints an the Coefficients: an application 

of quadratic programming and linear decision rules” .Report Group International Center for 

Management Science, Rotterdam. 

APPENDIX 

Table 1: The estimator ( ~ ), the BIAS ( ~ ), the M.S.E ( ~ ), R.E ( ~ ) 

β Β 0 

ˆ S.E( ˆ ) ~ K BIAS( ~ ) M.S.E( ~ ) R.E( ~ ) 

0.01 0.677 0.523 0.2317 -2.87872 0.89232 0.53958 0.07182 0.047904 1.12067 

0.02 0.677 0.523 0.2317 -2.83556 0.88939 0.54003 0.072674 0.047747 1.124372 

0.03 0.677 0.523 0.2317 -2.7924 0.88633 0.5405 0.073543 0.047583 1.128246 

0.04 0.677 0.523 0.2317 -2.74924 0.88315 0.54099 0.07443 0.047412 1.132304 

0.05 0.677 0.523 0.2317 -2.70609 0.87985 0.5415 0.075334 0.047235 1.136558 

0.06 0.677 0.523 0.2317 -2.66293 0.87641 0.54203 0.076256 0.04705 1.14102 

0.07 0.677 0.523 0.2317 -2.61977 0.87282 0.54258 0.077195 0.046858 1.145705 

0.08 0.677 0.523 0.2317 -2.57661 0.86909 0.54316 0.078153 0.046657 1.150627 

0.09 0.677 0.523 0.2317 -2.53345 0.8652 0.54376 0.079128 0.046448 1.155803 

0.1 0.677 0.523 0.2317 -2.49029 0.86114 0.54438 0.080122 0.04623 1.16125 

0.11 0.677 0.523 0.2317 -2.44713 0.85691 0.54504 0.081134 0.046003 1.166988 

0.12 0.677 0.523 0.2317 -2.40397 0.85249 0.54572 0.082165 0.045766 1.173038 

0.13 0.677 0.523 0.2317 -2.36081 0.84787 0.54643 0.083214 0.045518 1.179423 

0.14 0.677 0.523 0.2317 -2.31765 0.84305 0.54717 0.084281 0.045259 1.186167 

0.15 0.677 0.523 0.2317 -2.27449 0.83801 0.54795 0.085367 0.044989 1.1933 

0.16 0.677 0.523 0.2317 -2.23133 0.83274 0.54876 0.086471 0.044706 1.20085 

0.17 0.677 0.523 0.2317 -2.18817 0.82723 0.54961 0.087593 0.04441 1.208851 

0.18 0.677 0.523 0.2317 -2.14502 0.82146 0.55049 0.088733 0.0441 1.21734 

0.19 0.677 0.523 0.2317 -2.10186 0.81542 0.55142 0.089889 0.043776 1.226357 

0.2 0.677 0.523 0.2317 -2.0587 0.8091 0.5524 0.091061 0.043436 1.235947 

0.21 0.677 0.523 0.2317 -2.01554 0.80246 0.55342 0.092249 0.04308 1.24616 

0.22 0.677 0.523 0.2317 -1.97238 0.79551 0.55449 0.093451 0.042707 1.257051 

0.23 0.677 0.523 0.2317 -1.92922 0.78822 0.55561 0.094666 0.042316 1.268681 

0.24 0.677 0.523 0.2317 -1.88606 0.78057 0.55679 0.095892 0.041905 1.281118 

403


0.25 0.677 0.523 0.2317 -1.8429 0.77254 0.55803 0.097128 0.041473 1.29444 

0.26 0.677 0.523 0.2317 -1.79974 0.7641 0.55933 0.098371 0.041021 1.308731 

0.27 0.677 0.523 0.2317 -1.75658 0.75524 0.56069 0.099619 0.040545 1.324088 

0.28 0.677 0.523 0.2317 -1.71342 0.74592 0.56213 0.100869 0.040045 1.340621 

0.29 0.677 0.523 0.2317 -1.67026 0.73613 0.56364 0.102117 0.039519 1.358451 

0.3 0.677 0.523 0.2317 -1.6271 0.72584 0.56522 0.103359 0.038966 1.377719 

0.31 0.677 0.523 0.2317 -1.58394 0.71501 0.56689 0.104592 0.038385 1.398584 

0.32 0.677 0.523 0.2317 -1.54079 0.70362 0.56864 0.105809 0.037774 1.421226 

0.33 0.677 0.523 0.2317 -1.49763 0.69163 0.57049 0.107004 0.03713 1.445854 

β Β 0 

ˆ S.E( ˆ ) K ~ BIAS( ~ ) M.S.E( ~ ) R.E( ~ ) 

0.34 0.677 0.523 0.2317 -1.45447 0.67902 0.57243 0.10817 0.036453 1.472707 

0.35 0.677 0.523 0.2317 -1.41131 0.66575 0.57447 0.109299 0.035741 1.502061 

0.36 0.677 0.523 0.2317 -1.36815 0.65179 0.57662 0.110383 0.034991 1.534236 

0.37 0.677 0.523 0.2317 -1.32499 0.6371 0.57889 0.11141 0.034203 1.569607 

0.38 0.677 0.523 0.2317 -1.28183 0.62165 0.58127 0.112369 0.033373 1.60861 

0.39 0.677 0.523 0.2317 -1.23867 0.60541 0.58377 0.113246 0.032502 1.651761 

0.4 0.677 0.523 0.2317 -1.19551 0.58835 0.58639 0.114027 0.031586 1.699669 

0.41 0.677 0.523 0.2317 -1.15235 0.57043 0.58915 0.114695 0.030624 1.75306 

0.42 0.677 0.523 0.2317 -1.10919 0.55163 0.59205 0.115231 0.029614 1.812804 

0.43 0.677 0.523 0.2317 -1.06603 0.53193 0.59508 0.115614 0.028557 1.87995 

0.44 0.677 0.523 0.2317 -1.02287 0.51131 0.59826 0.11582 0.027449 1.955774 

0.45 0.677 0.523 0.2317 -0.97972 0.48975 0.60158 0.115826 0.026292 2.041838 

0.46 0.677 0.523 0.2317 -0.93656 0.46727 0.60504 0.115602 0.025086 2.140073 

0.47 0.677 0.523 0.2317 -0.8934 0.44388 0.60864 0.115118 0.023829 2.252885 

0.48 0.677 0.523 0.2317 -0.85024 0.41958 0.61238 0.114342 0.022525 2.38331 

0.49 0.677 0.523 0.2317 -0.80708 0.39444 0.61626 0.113239 0.021176 2.535214 

0.5 0.677 0.523 0.2317 -0.76392 0.36852 0.62025 0.111773 0.019784 2.713585 

0.51 0.677 0.523 0.2317 -0.72076 0.34189 0.62435 0.109905 0.018354 2.924949 

0.52 0.677 0.523 0.2317 -0.6776 0.31467 0.62854 0.107597 0.016893 3.177974 

0.53 0.677 0.523 0.2317 -0.63444 0.287 0.6328 0.104812 0.015407 3.484376 

0.54 0.677 0.523 0.2317 -0.59128 0.25905 0.63711 0.10151 0.013907 3.860296 

0.55 0.677 0.523 0.2317 -0.54812 0.23103 0.64142 0.097659 0.012403 4.32847 

0.56 0.677 0.523 0.2317 -0.50496 0.20318 0.64571 0.093228 0.010908 4.921754 

404


0.57 0.677 0.523 0.2317 -0.4618 0.17578 0.64993 0.088192 0.009437 5.689046 

0.58 0.677 0.523 0.2317 -0.41865 0.14913 0.65403 0.082535 0.008006 6.705696 

0.59 0.677 0.523 0.2317 -0.37549 0.12357 0.65797 0.07625 0.006634 8.092732 

0.6 0.677 0.523 0.2317 -0.33233 0.09946 0.66168 0.069342 0.005339 10.05463 

0.61 0.677 0.523 0.2317 -0.28917 0.07717 0.66512 0.06183 0.004143 12.95921 

0.62 0.677 0.523 0.2317 -0.24601 0.05707 0.66821 0.053747 0.003064 17.52351 

0.63 0.677 0.523 0.2317 -0.20285 0.03952 0.67091 0.045143 0.002122 25.3028 

0.64 0.677 0.523 0.2317 -0.15969 0.02487 0.67317 0.03608 0.001335 40.21467 

0.65 0.677 0.523 0.2317 -0.11653 0.0134 0.67494 0.026638 0.000719 74.64182 

0.66 0.677 0.523 0.2317 -0.07337 0.00535 0.67618 0.016909 0.000287 186.7609 

Β Β 0 

ˆ S.E( ˆ ) K ~ BIAS( ~ ) M.S.E( ~ ) R.E( ~ ) 

0.67 0.677 0.523 0.2317 -0.03021 0.00091 0.67686 0.006994 4.9E-05 1096.61 

0.68 0.677 0.523 0.2317 0.012948 0.00017 0.67697 -0.003 0.000009 5965.988 

0.69 0.677 0.523 0.2317 0.056107 0.00314 0.67652 -0.01296 0.000168 318.6621 

0.7 0.677 0.523 0.2317 0.099266 0.00976 0.6755 -0.02278 0.000524 102.4837 

0.71 0.677 0.523 0.2317 0.142426 0.01988 0.67394 -0.03234 0.001067 50.29742 

0.72 0.677 0.523 0.2317 0.185585 0.03329 0.67187 -0.04157 0.001787 30.03455 

0.73 0.677 0.523 0.2317 0.228744 0.04972 0.66934 -0.05036 0.002669 20.11174 

0.74 0.677 0.523 0.2317 0.271903 0.06884 0.6664 -0.05866 0.003696 14.52605 

0.75 0.677 0.523 0.2317 0.315063 0.0903 0.66309 -0.06641 0.004848 11.0741 

0.76 0.677 0.523 0.2317 0.358222 0.11373 0.65949 -0.07356 0.006106 8.792842 

0.77 0.677 0.523 0.2317 0.401381 0.13875 0.65563 -0.0801 0.007449 7.207063 

0.78 0.677 0.523 0.2317 0.44454 0.16501 0.65159 -0.086 0.008858 6.060316 

0.79 0.677 0.523 0.2317 0.4877 0.19215 0.64741 -0.09129 0.010315 5.204314 

0.8 0.677 0.523 0.2317 0.530859 0.21985 0.64314 -0.09596 0.011803 4.548476 

0.81 0.677 0.523 0.2317 0.574018 0.24784 0.63883 -0.10004 0.013305 4.034931 

0.82 0.677 0.523 0.2317 0.617177 0.27584 0.63452 -0.10356 0.014808 3.625306 

0.83 0.677 0.523 0.2317 0.660337 0.30364 0.63024 -0.10654 0.016301 3.293344 

0.84 0.677 0.523 0.2317 0.703496 0.33106 0.62602 -0.10904 0.017773 3.020584 

0.85 0.677 0.523 0.2317 0.746655 0.35794 0.62188 -0.11108 0.019216 2.793742 

0.86 0.677 0.523 0.2317 0.789814 0.38416 0.61784 -0.1127 0.020624 2.60306 

0.87 0.677 0.523 0.2317 0.832974 0.40963 0.61392 -0.11394 0.021991 2.441244 

0.88 0.677 0.523 0.2317 0.876133 0.43426 0.61012 -0.11484 0.023313 2.302747 

0.89 0.677 0.523 0.2317 0.919292 0.45802 0.60646 -0.11544 0.024589 2.183295 

0.9 0.677 0.523 0.2317 0.962451 0.48087 0.60295 -0.11577 0.025816 2.079549 

405


0.91 0.677 0.523 0.2317 1.005611 0.5028 0.59957 -0.11585 0.026993 1.988872 

0.92 0.677 0.523 0.2317 1.04877 0.52379 0.59634 -0.11572 0.02812 1.909158 

0.93 0.677 0.523 0.2317 1.091929 0.54386 0.59325 -0.1154 0.029197 1.838708 

0.94 0.677 0.523 0.2317 1.135088 0.56302 0.5903 -0.11493 0.030226 1.776141 

0.95 0.677 0.523 0.2317 1.178248 0.58129 0.58748 -0.11431 0.031206 1.720322 

0.96 0.677 0.523 0.2317 1.221407 0.59869 0.5848 -0.11357 0.032141 1.670315 

0.97 0.677 0.523 0.2317 1.264566 0.61526 0.58225 -0.11273 0.03303 1.625341 

0.98 0.677 0.523 0.2317 1.307726 0.63102 0.57982 -0.1118 0.033876 1.584745 

0.99 0.677 0.523 0.2317 1.350885 0.646 0.57752 -0.1108 0.034681 1.547978 

 

0 

Table 2: The estimator ( ~ ), the BIAS ( ~ , the MSE ( ~ ) and R.E ( ~ ) 

^ 

 

S.E( 

^ 

) K ~ BIAS( ~ ) MSE( ~ ) R.E( ~ ) 

0.01 0.48 0.507 0.0741828 -6.335700459 0.97569 0.506343722 0.0114241 0.0053693 1.02491 

0.02 0.48 0.507 0.0741828 -6.200898321 0.97465 0.506315609 0.0116600 0.0053636 1.02601 

0.03 0.48 0.507 0.0741828 -6.066096184 0.97354 0.506285667 0.0119055 0.0053575 1.02718 

0.04 0.48 0.507 0.0741828 -5.931294047 0.97236 0.506253736 0.0121613 0.0053510 1.02843 

0.05 0.48 0.507 0.0741828 -5.796491909 0.97110 0.506219638 0.0124280 0.0053440 1.02976 

0.06 0.48 0.507 0.0741828 -5.661689772 0.96975 0.506183173 0.0127062 0.0053366 1.03120 

0.07 0.48 0.507 0.0741828 -5.526887634 0.96830 0.506144120 0.0129967 0.0053286 1.03274 

0.08 0.48 0.507 0.0741828 -5.392085497 0.96675 0.506102232 0.0133003 0.0053201 1.03439 

0.09 0.48 0.507 0.0741828 -5.257283359 0.96508 0.506057231 0.0136178 0.0053109 1.03618 

0.10 0.48 0.507 0.0741828 -5.122481222 0.96329 0.506008804 0.0139502 0.0053011 1.03811 

0.11 0.48 0.507 0.0741828 -4.987679085 0.96136 0.505956600 0.0142984 0.0052904 1.04020 

0.12 0.48 0.507 0.0741828 -4.852876947 0.95927 0.505900222 0.0146637 0.0052789 1.04246 

0.13 0.48 0.507 0.0741828 -4.718074810 0.95701 0.505839220 0.0150471 0.0052665 1.04492 

0.14 0.48 0.507 0.0741828 -4.583272672 0.95456 0.505773084 0.0154501 0.0052530 1.04760 

0.15 0.48 0.507 0.0741828 -4.448470535 0.95190 0.505701229 0.0158739 0.0052384 1.05053 

0.16 0.48 0.507 0.0741828 -4.313668398 0.94900 0.505622992 0.0163201 0.0052224 1.05374 

0.17 0.48 0.507 0.0741828 -4.178866260 0.94584 0.505537610 0.0167904 0.0052050 1.05726 

0.18 0.48 0.507 0.0741828 -4.044064123 0.94238 0.505444203 0.0172866 0.0051860 1.06115 

0.19 0.48 0.507 0.0741828 -3.909261985 0.93858 0.505341761 0.0178107 0.0051651 1.06544 

0.20 0.48 0.507 0.0741828 -3.774459848 0.93441 0.505229107 0.0183648 0.0051421 1.07019 

0.21 0.48 0.507 0.0741828 -3.639657710 0.92981 0.505104879 0.0189512 0.0051168 1.07549 

0.22 0.48 0.507 0.0741828 -3.504855573 0.92472 0.504967482 0.0195724 0.0050888 1.08141 

0.23 0.48 0.507 0.0741828 -3.370053436 0.91908 0.504815050 0.0202310 0.0050578 1.08805 

0.24 0.48 0.507 0.0741828 -3.235251298 0.91279 0.504645387 0.0209299 0.0050232 1.09554 

406


0.25 0.48 0.507 0.0741828 -3.100449161 0.90577 0.504455899 0.0216720 0.0049846 1.10403 

0.26 0.48 0.507 0.0741828 -2.965647023 0.89791 0.504243509 0.0224603 0.0049413 1.11370 

0.27 0.48 0.507 0.0741828 -2.830844886 0.88906 0.504004554 0.0232979 0.0048926 1.12479 

0.28 0.48 0.507 0.0741828 -2.696042748 0.87906 0.503734653 0.0241878 0.0048376 1.13758 

0.29 0.48 0.507 0.0741828 -2.561240611 0.86772 0.503428549 0.0251324 0.0047752 1.15244 

0.30 0.48 0.507 0.0741828 -2.426438474 0.85481 0.503079914 0.0261339 0.0047041 1.16985 

0.31 0.48 0.507 0.0741828 -2.291636336 0.84004 0.502681104 0.0271931 0.0046228 1.19042 

0.32 0.48 0.507 0.0741828 -2.156834199 0.82307 0.502222874 0.0283089 0.0045294 1.21496 

0.33 0.48 0.507 0.0741828 -2.022032061 0.80348 0.501694036 0.0294776 0.0044216 1.24458 

407


 

0 

^ 

 

S.E( 

^ 

) K ~ BIAS( ~ ) MSE( ~ ) R.E( ~ ) 

0.34 0.48 0.507 0.0741828 -1.887229924 0.78078 0.501081072 0.0306907 0.0042967 1.28077 

0.35 0.48 0.507 0.0741828 -1.752427786 0.75436 0.500367728 0.0319332 0.0041513 1.32563 

0.36 0.48 0.507 0.0741828 -1.617625649 0.72351 0.499534657 0.0331793 0.0039815 1.38216 

0.37 0.48 0.507 0.0741828 -1.482823512 0.68738 0.498559244 0.0343883 0.0037827 1.45480 

0.38 0.48 0.507 0.0741828 -1.348021374 0.64503 0.497415885 0.0354967 0.0035497 1.55031 

0.39 0.48 0.507 0.0741828 -1.213219237 0.59545 0.496077232 0.0364092 0.0032768 1.67939 

0.40 0.48 0.507 0.0741828 -1.078417099 0.53768 0.494517241 0.0369860 0.0029589 1.85986 

0.41 0.48 0.507 0.0741828 -0.943614962 0.47101 0.492717378 0.0370290 0.0025920 2.12308 

0.42 0.48 0.507 0.0741828 -0.808812825 0.39547 0.490677696 0.0362718 0.0021763 2.52864 

0.43 0.48 0.507 0.0741828 -0.674010687 0.31238 0.488434245 0.0343810 0.0017191 3.20124 

0.44 0.48 0.507 0.0741828 -0.539208550 0.22525 0.486081862 0.0309898 0.0012396 4.43943 

0.45 0.48 0.507 0.0741828 -0.404406412 0.14056 0.483795044 0.0257833 0.0007735 7.11454 

0.46 0.48 0.507 0.0741828 -0.269604275 0.06776 0.481829551 0.0186448 0.0003729 14.75772 

0.47 0.48 0.507 0.0741828 -0.134802137 0.01785 0.480481877 0.0098215 0.0000982 56.03088 

0.48 0.48 0.507 0.0741828 0.000000000 0.00000 0.480000000 0.0000000 0.0000000 #NULL! 

0.49 0.48 0.507 0.0741828 0.134802137 0.01785 0.480481877 -0.0098215 0.0000982 56.03088 

0.50 0.48 0.507 0.0741828 0.269604275 0.06776 0.481829551 -0.0186448 0.0003729 14.75772 

0.51 0.48 0.507 0.0741828 0.404406412 0.14056 0.483795044 -0.0257833 0.0007735 7.11454 

0.52 0.48 0.507 0.0741828 0.539208550 0.22525 0.486081862 -0.0309898 0.0012396 4.43943 

0.53 0.48 0.507 0.0741828 0.674010687 0.31238 0.488434245 -0.0343810 0.0017191 3.20124 

0.54 0.48 0.507 0.0741828 0.808812825 0.39547 0.490677696 -0.0362718 0.0021763 2.52864 

0.55 0.48 0.507 0.0741828 0.943614962 0.47101 0.492717378 -0.0370290 0.0025920 2.12308 

0.56 0.48 0.507 0.0741828 1.078417099 0.53768 0.494517241 -0.0369860 0.0029589 1.85986 

0.57 0.48 0.507 0.0741828 1.213219237 0.59545 0.496077232 -0.0364092 0.0032768 1.67939 

0.58 0.48 0.507 0.0741828 1.348021374 0.64503 0.497415885 -0.0354967 0.0035497 1.55031 

0.59 0.48 0.507 0.0741828 1.482823512 0.68738 0.498559244 -0.0343883 0.0037827 1.45480 

0.60 0.48 0.507 0.0741828 1.617625649 0.72351 0.499534657 -0.0331793 0.0039815 1.38216 

0.61 0.48 0.507 0.0741828 1.752427786 0.75436 0.500367728 -0.0319332 0.0041513 1.32563 

0.62 0.48 0.507 0.0741828 1.887229924 0.78078 0.501081072 -0.0306907 0.0042967 1.28077 

0.63 0.48 0.507 0.0741828 2.022032061 0.80348 0.501694036 -0.0294776 0.0044216 1.24458 

0.64 0.48 0.507 0.0741828 2.156834199 0.82307 0.502222874 -0.0283089 0.0045294 1.21496 

0.65 0.48 0.507 0.0741828 2.291636336 0.84004 0.502681104 -0.0271931 0.0046228 1.19042 

0.66 0.48 0.507 0.0741828 2.426438474 0.85481 0.503079914 -0.0261339 0.0047041 1.16985 

408


 

0 

^ 

 

S.E( 

^ 

) K ~ BIAS( ~ ) MSE( ~ ) R.E( ~ ) 

0.67 0.48 0.507 0.0741828 2.561240611 0.86772 0.503428549 -0.0251324 0.0047752 1.15244 

0.68 0.48 0.507 0.0741828 2.696042748 0.87906 0.503734653 -0.0241878 0.0048376 1.13758 

0.69 0.48 0.507 0.0741828 2.830844886 0.88906 0.504004554 -0.0232979 0.0048926 1.12479 

0.70 0.48 0.507 0.0741828 2.965647023 0.89791 0.504243509 -0.0224603 0.0049413 1.11370 

0.71 0.48 0.507 0.0741828 3.100449161 0.90577 0.504455899 -0.0216720 0.0049846 1.10403 

0.72 0.48 0.507 0.0741828 3.235251298 0.91279 0.504645387 -0.0209299 0.0050232 1.09554 

0.73 0.48 0.507 0.0741828 3.370053436 0.91908 0.504815050 -0.0202310 0.0050578 1.08805 

0.74 0.48 0.507 0.0741828 3.504855573 0.92472 0.504967482 -0.0195724 0.0050888 1.08141 

0.75 0.48 0.507 0.0741828 3.639657710 0.92981 0.505104879 -0.0189512 0.0051168 1.07549 

0.76 0.48 0.507 0.0741828 3.774459848 0.93441 0.505229107 -0.0183648 0.0051421 1.07019 

0.77 0.48 0.507 0.0741828 3.909261985 0.93858 0.505341761 -0.0178107 0.0051651 1.06544 

0.78 0.48 0.507 0.0741828 4.044064123 0.94238 0.505444203 -0.0172866 0.0051860 1.06115 

0.79 0.48 0.507 0.0741828 4.178866260 0.94584 0.505537610 -0.0167904 0.0052050 1.05726 

0.80 0.48 0.507 0.0741828 4.313668398 0.94900 0.505622992 -0.0163201 0.0052224 1.05374 

0.81 0.48 0.507 0.0741828 4.448470535 0.95190 0.505701229 -0.0158739 0.0052384 1.05053 

0.82 0.48 0.507 0.0741828 4.583272672 0.95456 0.505773084 -0.0154501 0.0052530 1.04760 

0.83 0.48 0.507 0.0741828 4.718074810 0.95701 0.505839220 -0.0150471 0.0052665 1.04492 

0.84 0.48 0.507 0.0741828 4.852876947 0.95927 0.505900222 -0.0146637 0.0052789 1.04246 

0.85 0.48 0.507 0.0741828 4.987679085 0.96136 0.505956600 -0.0142984 0.0052904 1.04020 

0.86 0.48 0.507 0.0741828 5.122481222 0.96329 0.506008804 -0.0139502 0.0053011 1.03811 

0.87 0.48 0.507 0.0741828 5.257283359 0.96508 0.506057231 -0.0136178 0.0053109 1.03618 

0.88 0.48 0.507 0.0741828 5.392085497 0.96675 0.506102232 -0.0133003 0.0053201 1.03439 

0.89 0.48 0.507 0.0741828 5.526887634 0.96830 0.506144120 -0.0129967 0.0053286 1.03274 

0.90 0.48 0.507 0.0741828 5.661689772 0.96975 0.506183173 -0.0127062 0.0053366 1.03120 

0.91 0.48 0.507 0.0741828 5.796491909 0.97110 0.506219638 -0.0124280 0.0053440 1.02976 

0.92 0.48 0.507 0.0741828 5.931294047 0.97236 0.506253736 -0.0121613 0.0053510 1.02843 

0.93 0.48 0.507 0.0741828 6.066096184 0.97354 0.506285667 -0.0119055 0.0053575 1.02718 

0.94 0.48 0.507 0.0741828 6.200898321 0.97465 0.506315609 -0.0116600 0.0053636 1.02601 

0.95 0.48 0.507 0.0741828 6.335700459 0.97569 0.506343722 -0.0114241 0.0053693 1.02491 

0.96 0.48 0.507 0.0741828 6.470502596 0.97667 0.506370151 -0.0111973 0.0053747 1.02388 

0.97 0.48 0.507 0.0741828 6.605304734 0.97759 0.506395026 -0.0109791 0.0053798 1.02292 

0.98 0.48 0.507 0.0741828 6.740106871 0.97846 0.506418467 -0.0107691 0.0053846 1.02201 

0.99 0.48 0.507 0.0741828 6.874909009 0.97928 0.506440581 -0.0105668 0.0053891 1.02116 

409



ISSN 1943-2429 


ASPECTS OF STRATIGRAPHY AND FACIES PROFILE OF CLASTIC DEPOSITS IN 

DOMA FIELD, NIGER DELTA 

ROTIMI OLUWATOSIN JOHN*, ADEOYE OLUSHOLA TAIYE**, OFOMOLA MERRIOUS OVIRI*** 

* Petroleum Engineering Department, Covenant University, Ota, Nigeria 

** School of Earth and Mineral Science, FUTA, Akure, Nigeria 

*** Department of Physics, Delta State University, Abraka, Nigeria 

*E-mail address for correspondence: tossynrotimmy@yahoo.com 

______________________________________________________________________________________________ 

Abstract: The consistencies observed on lithologies encountered during exploration are often brief. They are usually 

characterized by rapidly changing signatures due to the rapid depositional patterns. Well logs and Seismic data 

employed in this study assisted in gaining insight into the Stratigraphy of the sand units and facies profile. By 

mapping lithologies from well logs an attempt was made to identify the depositional sequence. Reflections around 

important fluid markers were studied in detail on seismic sections. System tracts and the corresponding depositional 

environments determined from the log motifs were extended for lateral significance on seismic lines. Well to seismic 

tie was done to validate the recognition of strata patterns on the seismic sections for lateral facie classification. With 

results presented in time slices, well log panels and seismic cross sections, the spatial distribution of the identified 

hydrocarbon prone depositional facies was studied. 

Keywords: facies, depositional patterns, Stratigraphy, reflections, markers 

______________________________________________________________________________________________ 

INTRODUCTION 

Resolving stratigraphic patterns along the spread of an exploration field entails an integrated approach for a robust 

result to be achieved. Doma field has experienced successful exploration programs and an extra push is needed to 

assist engineers in making proper planning for a proposed secondary recovery operation. Water injection has been 

proposed to sweep hydrocarbon to production holes. This would be a huge success for the proposed mop-up of the 

remaining oil only if there is a revisit on the Stratigraphy of the oil hosting lithologies in the petroleum rich clastic 

facies of the Niger Delta. 

411


The geology of the Tertiary section of the Niger Delta is divided into three Formations – Benin, Agbada and Akata, 

representing prograding depositional facies distinguished mostly on the basis of sand-shale ratio and further 

subdivided into depobelts as progradation proceeds into the deeper waters (Short and Stauble, 1965; Doust and 

Omatsola, 1990; Kulke, 1995) 

Stacher, (1995), documented the formation of Akata Formation initiated in the Paleocene and through the Recent. A 

lowstand period characterized by low energy conditions and oxygen deficiency when terrestrial organic matter and 

clays were transported to deep-sea water. A paralic sequence of alternating Lower Eocene-to-Pleistocene sandstones 

and sand bodies with shale intercalations, which is known as the Agbada Formation overlies the undercompacted 

Akata shales (Doust and Omatsola, 1990). An extensively massive, porous, and unconsolidated freshwater bearing 

continental sands known as the Benin Formation caps the Niger Delta lithological cross section. The Doma field is 

on the eastern portion, onshore Niger Delta. 

MATERIALS AND METHODS 

Digital logs from three wells and SEG Y Seismic volume constitute the basic data point for this study. However, well 

log markers were available for two of the wells. In some of these markers, fluid contacts like water saturation level 

(S w ), oil up to (OUT), and gas down to (GDT) were observed. Stratigraphic interpretations that focused on the 

identification of the reservoir, source and seal prone depositional facies around these markers as these markers point 

directly to prospectivity of the field was done. Although these markers are more of petrophysical markers than 

stratigraphic markers because of the abundance of petrophysical properties attached to them. 

FLUID MARKERS IN WELLS 

The markers in well 2 include HD1000, HD2000, HD2400, HD5000, GC3000, GC7100 and FE3000 which has the 

fluid contacts observed within them. The markers in well 3 include HD1000, HD2000, HD5000, JF4100, JF4200, 

JF5000 and JF6000. 

Check shot data available on well 3 was used for the well to seismic tie operation. It was observed that seismic 

characters were related to stratigraphic markers and the well logs marker previously identified. This was important to 

substantiate the occurrence and position of both markers and sand sequences identifies on the field of study. The tops 

of sequence boundary (SB) one and two were tied to a moderately blue strong reflector labeled FF and high 

amplitude reflection labeled UU respectively. In another instance the top of the fluid contact OUT (at depth 1016m) 

in marker HD1000 was tied to a moderately high amplitude reflection on the seismic sections. The procedure 

adopted via the check shot indicated that the tops of the reservoir sands in the area are represented on the seismic 

volume by various amplitude reflections. The well to seismic match provides the basis for locating important seismic 

reflection profiles also on well log. 

412


RESULTS AND DISCUSSION 

Markers from the wells as observed were united in terms of fluid content characters. Markers HD1000, HD2000 and 

HD5000, were all observed in the two wells while others occurring have different identities and were not duplicated 

like these three. In well B, The HD1000 was observed at the depth interval of 1750m and 1764m where ODT was 

observed at the depth of 1761m. Water saturation in this zone is very low (20) and the implication is that the 

hydrocarbon content may be high and this is supported by the high reading of the resistivity log (RT). In the same 

well, markers HD2000 was observed at the depth of 1766m – 1809m and the fluid contacts within it include ODT at 

the depth of 1809m (Fig 1). The HD2400 was observed at the depth interval of 1812m and 1830m where HCWC was 

observed at the depth of 1817m. Water saturation in this zone is 17 and average porosity is 31. Markers HD3000 and 

HD5000, were in included in this study because of their closeness to other markers. 

Also in well C, The gas-oil contact/ oil-up to (GOC/OUT) was observed in markers JF4100 and JF4200 at the depths 

of 3173m and 3200m. The gas up to (GUT) was observed in marker JF5000 at the depths of 3238m. 

Figure 1: One of the wells in the field with well markers and fluid contacts 

The hydrocarbon water contact (HCWC/WUT) was observed within the HD1000, HD2000 and HD5000 at the 

depths of 1808m, 1824m and 2021m respectively. 

Sequence boundaries were interpreted both on well logs and seismic data. These stratigraphic markers were initially 

interpreted on well logs to validate the identity of the fluid markers. Sequence boundaries in the field were first 

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identified based on the interpretation of reflection terminations and unconformity surface seen on the seismic 

sections assisted by interpretation of well log motifs. They were defined by looking for abrupt bases of thick lowgamma 

ray- value intervals on the well logs (Catuneanu, 2006). The sequence boundary identification enabled the 

division of the stratigraphic surfaces into sequences. Using these criteria, sequence boundary one and two defined 

sequence one while sequence boundary two and three defined sequence two and sequence boundary three and four 

defined sequence three. Within the sequences, proper analysis of stratigraphic features and facies classification were 

then done. 

Sequence boundaries 

The oldest sequence boundary was observed in the three Wells with an average depth of 2882m. It is interpreted by 

the sharp boundary between increase and decrease in gamma-ray readings. This boundary serves as the base of 

sequence three which has intercalation of sand and shale in the lithology log. The overall log trend within the 

sequence is very irregular. Log trends observed include coarsening upwards log signatures which typifies the 

highstand system tract and the fining upwards log signature which is typical of the transgressive system tract. 

Figure 2: Log motifs and position of sequences from 2 of the wells 

Sequence boundary two is represented by a marked increase in gamma-ray values (figure 2). Above the sequence 

boundary, gamma-ray values increase systematically then decrease in the same manner. This log signature follow a 

414


bow trend as it signifies the start of the second sequence deposit. The sharp-based sequence represents a significant 

change in depositional environment. The sharp boundaries with overlying and underlying sequences imply the 

existence of an abrupt change from a low gamma coarse grained unit to a high gamma finer unit and back again in a 

progradational pattern as the stacking of the parasequences progresses. 

At an average depth of 1851m occurs the third sequence boundary. This marks the beginning of the last sequence as 

it caps the sequence beneath it giving it an average total depth thickness of 244m. It is characterized by the sharp 

boundary in alternating back turning (low and abrupt high) gamma-ray readings (figure 3). The boundary defines the 

basal boundary of sequence one that contains the greatest preserved thickness. 

Capping the clastic sequence studied is the fourth and youngest sequence boundary penetrated by all three wells in 

the field. The average depth of 1557m was observed for it (Fig 4). This boundary is characterized by overall low 

gamma ray values, corresponding to an increase in incoming sand in the lithology log. The overall log trend is very 

irregular with distinct spikes of log motifs due to rapidly alternating lithologies (sand and shale). This either reflects 

a multitude of discrete depositional events or a variable sediment supply (King et al, 1993). 

Figure 3: Observed log patterns of sequence boundary 3 

415


Figure 4: Sequence boundaries 1 and 2 shown on wells 2 and 3 

Stratigraphy and Facie patterns of Sequences 

The basal Sequence 1 is about 219m thick from two wells. Like the overlying sequences, gamma ray values abruptly 

decrease at the base of the sequence with blocky patterns signifying the lowstand portion of the sequence. This basal 

interval with low gamma ray values is vertically divided by several thick intervals with slightly high and moderate 

gamma ray values. The areas where gamma ray values increase abruptly in the middle of the sequence on the well 

logs are interpreted to define the transgressive portion of the sequence due to fining upwards log signatures. In Fig 6, 

on the seismic sections the entire sequences and sequence boundary are shown. The maximum flooding surface on 

top of the transgressive sequence observed as low amplitude reflections and laterally extensive shale blanket is 

sharply distinguished from the downward reflection and is predicted to be associated with the condensed section 

spread-out from the shelf environment. Seismic facies labeled IB are confined mainly to this transgressiveregressive 

portion of the sequence and are seen as hummocky (divergent) reflections. The interval of seismic facies 

IB is really thin. This high amplitude and moderate-to-good continuity reflections seen have parallel-to-subparallel 

reflections that are dominant in this seismic facies. Discontinuous reflections (mostly truncations) can also be seen 

locally. This seismic facies represent the common reflection character of the Formations throughout the area. These 

represent good image deposits of a fluvial-dominated environment. 

Sequence 2 averages about 244m thick from three wells where it was observed (Fig 5). The upper and lower 

sequence boundary occurs at an average depth 1851m and 2207m respectively. The basin floor fans mark the 

lowstand system tract. It occurs within the average interval of 1851m and 1981m on the well logs. The interpreted 

log signatures for this zone were blocky log patterns. 

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Figure 5: Sequence 2 observed in all wells with markers and thickness 

However, coarsening upward log patterns within shallower successions may indicate prograding wedge complex 

deposits formed as relative sea levels began to fall, whereas those higher in successions probably record submarine 

fluvial and channel deposits within slope fan complexes typical of shelf environment. This validates the formation of 

a depositional sequence that forms during a full cycle of change in accommodation, which involves both an increase 

(positive) and decrease (negative) in the space available for sediments to fill (Catuneanu et al, 2010). 

Figure 6: Stratigraphic contact on line 5192. Sequences identified and facies positions 

417


This has been initiated from the shelfal environment here and basinward. Seismic facies labeled IJ is also composed 

of sand and shales observed on the seismic sections near this region (between HD2400 and HD5000) (Fig 7). It is 

characterized by low-to-high or variable amplitude and poor to-low continuity reflections. High amplitude and 

continuity is related to widespread and uniform deposition. This is observed in the central and northern part of the 

study area on several seismic lines. As we move up the sequence, the well log pattern indicates that the transgressive 

system tract has been reached and the fining of gamma ray log signatures (stacked succession) was observed (Fig 5). 

Deposits interpreted in this section include shoreface sands and reworked sandstone units. Seismic facies labeled (IL) 

is also observed, characterized by low-to-high amplitude, package of brief irregular hummocky clinoforms. 

Sequence 1 averages about 285m thick from three wells as the topmost sequence. The upper and lower sequence 

boundary occurs at an average depth 1557m and 1851m respectively, enveloping the whole system tracts of the 

depositional cycle. The prograding wedge complex and the basin floor fan deposits mark the upper and lower part of 

the lowstand system tract respectively which occurs within the average interval of 1798m and 1853m on well logs 

(Fig 2). In the prograding section on the well logs, coarsening shaped log patterns were observed while blocky log 

patterns were interpreted for the slope fan deposits. On the seismic section the prograding complex is observed as 

high amplitude clinoforms reflections (sigmoidal), which eventually extended towards the lowstand system tract as a 

downlap surface observed on the seismic line 5505 (Fig 8). Seismic facies (presumed as sand and silt facies of the 

prograding complex) labeled I was observed in this interval. The sand and silt facies of the prograding complex is 

characterized by high amplitude reflections whereas those with low amplitudes with few hummocky zones were 

interpreted as marine sand and shales. The area of high continuity of the amplitudes is related to widespread and 

uniform deposition. This is observed in the upper part of the section. Marker in well B observed (GC3000, GC7100, 

HD1000, e.tc), which contain hydrocarbon contacts fall within this portion. Therefore, extensive reservoir analysis 

may be narrowed down to this formation. 

Figure 7: Inline 5447 showing sequence boundaries, facies patterns and faults 

418


Figure 8: Stratigraphic interpretation of sequence boundaries showing well penetration on seismic section 

On the well logs, the Blocky/serrate log patterns that indicate basin floor fans (or turbidites) may be formed as 

relative sea levels began to fall. In this part, the sequence contains fairly thick sand units explorable for hydrocarbon 

in the western part with high porosity based on the density logs (Fig 9). As we move up the sequence on the logs, the 

fining of deposits (transgressive unit) recognized in the upper most part may be deposits formed along tide/waveinfluenced 

coastlines typical of the Niger Delta depositional sequence (Fig. 2). 

419


Figure 9: corresponding high porosity values on density and sonic logs 

In the transgressive system tract, interpreted facies and deposition environment are the shoreface sands. In figure 8, 

rollover build up is seen at the base of the seismic section. This is where more transition in reflection character is 

observed (low amplitudes and hummocky reflections) with no significant continuity. This is an indication that the 

region is composed of another facie entirely. The Facies extends along the eastern part in the form of divergent 

seismic reflections (Fig 7). The highstand system tract is marked by gradual decrease in gamma ray log indicating 

coarsening upwards log signatures. Deltaic and shoreface sands are believed to be present within this interval, since 

river profiles stabilize in the highstand system tract and the Niger Delta is a fluvio-marine environment, river valleys 

and channels may also be present within this interval (tract). 

Facies distribution and geometry 

Sequence 1 and 2 were laterally examined for distinct properties to substantiate the profiling of subsurface 

formations studied. Most of the hydrocarbon markers and contacts delineated are within either one or two of the 

already identified facies. These fluid contacts projected across to determine the lateral spread of the units already 

inferred as reservoir candidates have significant extent due to the high degree of erosion strongly associated with 

tectonic subsidence expressed on the seismic sections as reflections with a protracted downlap surface. This was 

more pronounced within sequence one and two in the southwestern part of the field. Also the alternation of sands and 

shale within the sequence itself, provide the combination of source reservoir, and cap rock essential for hydrocarbon 

generation, accumulation and trapping. This suggests that oils found in the reservoirs of the sequence may have been 

generated from the shales within it. The Akata shale is also a potential and possible source bed within the average 

depths of 410m and 518m. 

420


Figure 11 shows amplitude distribution of OUT (fluid contact) which occurs inside well marker GC3000. This 

amplitude distribution approximates the lateral extent of the reservoir. These red broad high amplitude anomalies 

seen in the central part of the study area (near well C) trends in the North-South direction and correlates with the 

apparent truncation feature previously identified on the seismic sections (seismic line 3333). Higher amplitudes 

represented by red bands may also represent the stacks of highest sand accumulation but do not necessarily reflect 

reservoir quality. 

Figure 10 shows yellowish high amplitudes representing facie II in sequence two were seen in the centre of the field 

and locally dispersed all over proximally. The patterns appear as massive sand bodies and likely scattered deposits of 

flood plain adjoining the channel cut feature as inferred from time slice opened along this portion on the seismic 

volume. Blue colored areas may likely represent shale or any other high impedance layer. Facie IK (yellow) 

observed with similar character with the earlier one may have been the sand deposited when the major channels 

developed in the southern part, the river mouth bar, distal bar, and sand sheet were developed in the northern part. 

The sand bodies appear as strong reflection event in seismic section (Figure 6). 

In the central and southern (also scattered towards the east) part of the field of Figure 6, facie I is observed as 

moderate amplitude reflections (yellow) oriented NW-SE. The contact OUT was located within this reflection, so the 

facie analysis here can approximate lateral boundary of the reservoir. On the seismic section, the package appeared 

as a series of prograding reflectors on a marginal slope overlain by subparallel and laterally continuous beds. Using 

this information and the geometry observed, it is interpreted as channel or fan deposits. Along the dip-controlled 

boundary, the amplitude gradient was extrapolated to define the actual down-dip reservoir limit and its boundary 

marked xx (Fig 10). 

In the same figure the, low moderate amplitudes is observed in the central and upper part of the field (light blue 

color). It may represent thick clay bodies or shale development within the parallic and continental sequences in the 

delta fringe. Reservoir conditions change with facies belts and structure. For instance, structure is the key factor in 

the central part of the field, where the explorations wells in the sand formation have hit hydrocarbon. Towards the 

northern part of the field it was observed that seismic facie ILO identified in sequence one are formed within 

stratigraphic traps (Fluvial channel and valley incisions) as they are mainly truncations against the base of the 

channel with faults and rollover anticlines overlying them serving as the major structural trap mechanism (Figs 11). 

421


1 2 

Figure 10: 1- r.m.s amplitude maps of OUT surface showing facies distribution and geometry. 2- r.m.s amplitude 

map of the HCWC surface 

Structural maps of Sequence Boundaries 

To briefly validate the trapping potential of the sequence boundaries, time-structural maps were produced for two 

sequence boundaries. It also serves as a check on the roll-over structures identified on the seismic lines. 

Figure 11: Time structure maps of sequence boundaries 

The figure above is the time structural map of sequence boundary One and two. Structural highs are observed over 

the field in the north direction while structural lows were observed in the southern direction. Only one significant 

422


structural crest (confirming rollover) was observed over the horizon in the central part of the field (green to light 

green color). The structure covers an area of about 20 km and 13km for sequence boundaries 1 and 2 respectively. 

The large lateral area that they cover is also good for hydrocarbon amassing. This structures can serve as good traps 

for the hydrocarbon reservoirs since they can impede the vertical and lateral migration of fluid, with the embedding 

medium identified on well logs (Shale) serving as the seals. The fault styles seen on the map is characterized mostly 

by east-west trending faults that are gently dipping, all almost parallel to the main fault (fault F f ) with five antithetic 

faults observed dipping in the opposite direction. 

CONCLUSION 

Just like the adjoining portions of the distal segment of the highly productive Niger Delta petroleum system, this 

study has been able to revisit the facies imprints of the Doma field. The clastic deposits that are of the onshore 

depobelt are basically of three sequences and extend laterally with maturity for hydrocarbon content diminishing 

with the younging direction of the sequences. With the inclusion of the fluid markers in interpretation, accuracy has 

been achieved in delineating the facies on both the well logs and seismic lines and also evaluating the proficiency of 

the by-passed sand units as they are both stratigraphically and structurally mature and explorable. 

REFERENCES 

Catuneanu O. (2006). Principles of Sequence stratigraphy: Elsevier Radarweg Publishing. 29, PO Box 211, 1000 

AE Amsterdam p 42-54 

Doust, H., and Omatsola, E. (1990). Niger Delta, in, Edwards, J. D., and Santogrossi, P. A., Eds., Divergent/Passive 

Margin Basins, AAPG Memoir 48: Tulsa, Americam Association of Petroleum Geologists, Pg. 239-248. 

King, P.R., Scott, G.H., Robinson, P.H. (1993). Description, correlation and depositional history of Miocene 

sediments outcropping along North Taranaki Coast. Lower Hutt: Institute of Geological& Nuclear Sciences. 

Institute of Geological & Nuclear Sciences monograph 5. 199 p 

Kulke, H., (1995). Nigeria, in Kulke, H., Ed., Regional Petroleum Geology of the World. Part II: Africa; America; 

Australia And Antarctica: Berlin, Gebrüder Borntraeger, Pg. 143-172. 

O. Catuneanu, J.P. Bhattacharya, M.D. Blum, R.W. Dalrymple, P.G. Eriksson, C.R. Fielding, W.L. Fisher, W.E. 

Galloway, P. Gianolla, M.R. Gibling, K.A. Giles, J.M. Holbrook, R. Jordan, C.G.St.C. Kendall, B. 

Macurda, O.J. Martinsen, A.D. Miall, D. Nummedal, H.W. Posamentier, B.R. Pratt, K.W. Shanley, R.J. 

Steel, A. Strasser and M.E. Tucker (2010). Sequence stratigraphy: common ground after three decades of 

development. EAGE,First break vol.28. 

http://www.geology.utoronto.ca/Members/miall/miall_bib/pdfs/CatuneanuEtAl2010.pdf 

Short, K. C., and Stauble, A. J. (1965). Outline of Geology of Niger Delta: American Association of Petroleum 

Geologists Bulletin Vol. 51, Pg. 761-779. 

Stacher, P. (1995). Present Understanding of the Niger Delta Hydrocarbon Habitat, In, Oti, M. N., and Postman Eds., 

Geology of Deltas: Rotterdam, A. A., Balkema, Pg. 257-267. 

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ISSN 1943-2429 


IN STRATEGIC DECISION AND MOTIVATION IN JORDANIAN BANKING 

INDUSTRY 

MARWAN AL-NSOUR 

Faculty of Planning and Management, Al-Balqa Applied University 

E-mail address for correspondence: marwan_alnsour@yahoo.com 

_________________________________________________________________________________________ 

Abstract: This study aims at determining the level of participation of employees in strategic decision-making and 

its relationship to motivation towards working in the Jordanian banking industry. The study sample consisted of 

(167) employers and a employee, the study relied on descriptive method of analysis to achieve their goals, and 

developed a questionnaire to measure the variables of the study, the significance of validity and reliability is 

acceptable. The study results showed that the degree of participation of employees in strategic decision-making 

in the Jordanian banking industry was moderate. The level of motivation of employees in the Jordanian banking 

industry about the work was high, and the existence of the relationship with a statistically significant correlation 

between the participation of employees in strategic decision-making and motivation towards working in the 

Jordanian banking industry. The application of this study was limited to employees in the Jordanian banking 

industry in 2010, and the results of this study on the implications of validity and reliability of the tools in the 

study used.The study recommend enhancing the participation of employees in strategic decision-making related 

to them through their participation in decisions regarding the placement of the courses they need, activating the 

participation of employees in making strategic decisions about working through their participation in decisions 

concerning the status of the plans. 

Key words: Banking Industry , Decision-making, Jordan, Motivation, Strategic Decision-making. 

_________________________________________________________________________________________ 

INTRDUCUTION 

The process of decision-making is a cornerstone in the managing organizations, while Simon consider (1978) 

one of the pioneers that founded the decision making process in management. The essential elements of the 

decision making are:(1) a managerial problem requiring a solution (2) the availability of more alternative to 

resolve the administrative problem,(3) and then be offered alternatives to be discussed, studied, and evaluated 

until choose the alternative best suited to address the administrative problem, and thus, the decision is an act 

done by the individual to accomplish a specific goal by a trade-off set of alternatives or solutions and choose the 

most appropriate to achieve the goal or solve the problem (Habib, 1997). From the perspective of the strategist, 

or managerial decision-maker, the deliberate rational decision-making process involves five intertwined 

cognitive stages: (1) give attention to a problem or opportunity; (2) collect information; (3) develop an array of 

options; (4) value the options using expected costs and benefits; and finally (5) select the option with the greatest 

utility (Fredrickson, 1984; Mitchell and Beach, 1993). Strategic decision makers are often members of board of 

managers of organizations. From the governance perspective, in order for the board to make strategic decisions, 

its composition in terms of size and diversity should be taken into consideration. Good composition will allow 

425


the members to bring their expertise and different perspectives to the organization and to aid strategic decisions 

(Hillman, Keim et al. 2001; Hartaska and Mersland Forthcoming). 

Also associated with the management decision-making in the organization of course the role of manager is 

complexity, has led the expansion of technological development, and growth of the values of modern social 

complexity of the role of manager, which was imposed on managers need to cooperate with subordinates, and 

their employees and involve them in management functions in general, and decisions that is an important part of 

management in particular (Canaan, 2007). How strategic decisions are made and implemented and the factors 

which affect it (Elbanna 2007). 

The process of decision-making is a process involving a number of stages, based on the existence of essential 

elements necessary for a decision as the existence of a certain position, and the manager to be aware of the 

choice of the alternatives available, and that the alternative would be a realistic and well thought out and less 

expensive. Strategic Decision Making Process refers to a set of activities through which strategic problems are 

identified, interpreted, tackled and solved (Elbanna 2007). Accordingly, the process of management decisionmaking 

depends largely on the behavior of the manager to take the decision, and see Canaan (2007) that there is 

a range of factors that affect the behavior of the manager during the selected one of the alternatives, and thus 

affect the effectiveness of the resolution, and significantly influence the pattern of decision- decision has, and 

that the most important of those factors that influence the effectiveness of the resolution, and style are: the 

legislative texts that are imposed on him by virtue of his official position in the organization, and human factors 

that guide the behavior and orientation to choose the best alternative, and internal and external pressures faced 

by the manager during the decision-making process . 

As a result of rapid technological development has led to the complexity of the role of manager, forcing 

managers to cooperate with subordinates, and their employees and involve them in management functions in 

general, and decision-making in particular (Canaan, 2007). Motivations for in business are complex (Culkin & 

Smith, 2000), one of the main methods of participation in decision-making; systems suggestions: that allow 

employees to make a opinion, its effectiveness depends on how seriously the management of the system. And 

committees: a group of individuals entrusted with certain powers and duties, and are formed either by the 

administration to consider a specific problem and decide to solve them. And councils: the administrative 

formations with special functions, as determined in the decisions of its terms of reference composition (Khadra, 

1979). 

The participation in decision-making is an important element at the psychological factors, which contribute to 

improving the motivation of employees towards work, and help them to satisfy the basic needs they have clarity, 

and social relations, these needs leads to the activation of feelings of acceptance and commitment, security and 

the challenge the more innovative they have, and improve their performance (Hussein, 2007). In light of this 

came the study to look at the degree of participation of employees in strategic decision-making and its 

relationship motivation towards working in the Jordanian banking industry. 

Study Questions: 

This study attempted to answer the following questions: 

1. What degree of participation of employees in strategic decision-making in the Jordanian banking industry 

2. What level of motivation of employees in the Jordanian banking industry to work 

3. Is there a relationship statistically significant at the level of significance (0.05 ≥ α) between the participation of 

employees in strategic decision-making and motivation towards working in the Jordanian banking industry 

Importance of the Study: 

The importance of this study is to illustrate the relationship between the participation of employees in strategic 

decision-making and motivation towards work. 

The practical importance of this study lies in helping decision makers in the Jordanian banking industry how to 

develop management, and promote the participation of employees in strategic decisions, and reveals the 

importance of this participation in the development of motivation of personnel to work, and that through its 

recommendations based on their finding of results. 

426


Participation in Strategic Decision-making 

Employee participation in decision making, sometimes referred to as participative decision-making is concerned 

with shared decision making in the work situation (Mitchell, 1973) Strategic planning is the setting of long-term 

business goals, and the developing and implementing of plans to achieve these goals (O'Regan & 

Ghobadian,2004).Decision-making process a series of cascading events that include a variety of provisions 

affecting directly in the implementation process to resolve the problem or mitigate its results, and include such a 

step on the decision and all the steps until it reaches the stage of implementation (Mkrom, 1996). 

According to Simon (1978) that the decision-making is synonymous with management, the management 

decisions of the core functions and core functions of managers, the decision-making process is the analysis and 

evaluation of all the variables common subject of scientific measurement by the equations scientific research and 

scientific theories, quantitative methods and statistical purpose of reaching a solution or as a result and then 

come up with recommendations and conclusions of the application of these solutions. Yaghi (2005) explains the 

decision-making process as the process of selecting a conscious alternative to a particular one of several 

alternatives to meet the particular position or to address the problem or the issue of waiting for the appropriate 

solution. And must follow the decision-making process a scientific approach is the method that is based on 

objectivity and scientific scrutiny and logical thinking is biased based on the scientific method a specific start 

diagnosing the problem or situation and determine the objective or objectives and ends with selection of the 

decision most appropriate, which addresses the problem and achieve the goal (Emad El-Din, 1997) .El Serafy 

(2003) define the decision-making process as "a rational process to take shape in a rational choice between 

alternatives with multiple specifications commensurate with available resources and desired goals." According to 

Qaryouti (2009) the process of decision-making starts by identification the problem followed by the guidance 

and to exercise, its powers and responsibilities, but that everything is done by managers to make decisions. The 

Alkfawin (2005), she believes that the process of decision-making is the core of the administrative process, and 

the heart of administrative work, as well as its tool effectively to achieve the goals of the organization internally 

and externally, and is seen as an essential function and key exercised administrative in any location at any time. 

Importance of strategic decision-making: 

Decisions are made in all management functions and activities, motivation to perform well and solve their 

problems, and in control managers on the determination of appropriate criteria to measure business results, and 

the amendments will be held on the plan, and correcting errors, if any, and so decisions are being taken in a 

continuous cycle (Hawari, 1998). The importance of decision-making with respect to importance of the 

objectives to be achieved in the administrative system and the development of this device is measured by the 

success of the process of decision-making and the possibilities available with the need to formulate alternatives 

and select the best and the surest and then drafting the resolution and issued, implementation and follow-up. 

And Yaghi (2005) that the most important findings is that the experiences of Horton method of democratic 

governance is the most feasible method, and management on the exercise of this method and the participation of 

employees in decision-leader pattern. There is a difference between the decision maker, the manufacturer, 

decision is determined by the decisions in accordance with certain conditions set by the decision may not be 

exceeded, while the chosen decision-maker decision that suits him in the light of the conditions set in advance, 

and then implement the decision so we find that the decision point is the "administrative work" represents one 

aspect in the process of decision-making. 

The importance of the decision-making at the individual level, they stand out from many of the decisions taken 

by the individual in our daily lives is affected by and affect others, but for the importance of the decision-making 

at the level of small communities, it highlights the vulnerability of the behavior of the individual member of the 

small groups conduct of individual members of humanitarian groups that joins them, and the importance of 

taking decisions at the corporate level, the increasing degree of complexity is increasing as a result of inflation, 

the size of organizations, and openness to different environments, and the speed of the changes that have become 

characteristic of public life. 

Yaghi (2005) describe the process strategic of decision-making through four stages: 

1. Stage of problem identification and analysis: At this stage to identify the symptoms of the problem, and to 

distinguish them from the real problem 

2. The process of gathering information and data: This phase aims to develop alternatives to making the right 

decision, by identifying the information to be collected, and the sources of that information, and quality, and 

427


time available to provide that information, and therefore the quality, quantity and nature of the information and 

data required vary from problem to another. 

3. The stage of identifying the available alternatives and of the problem: After collecting the necessary information 

and study it properly and find out the causes of the problem and analyze the relationship between the different 

variables that led to a problem, move the decision maker to look for a set of options may be solutions to the 

problem. . 

4. The stage of choosing a suitable alternative to solve the problem: After the completion of the previous phase, to 

become the decision maker a set of possible solutions, who shall give the value of each alternative, telling the 

strengths and weaknesses of each alternative, are choosing the alternative that achieves the highest return (the 

most appropriate alternative). (Yaghi, 2005) 

Canaan (2007) show that the decision-making process affected by the by many factors, which in turn affect the 

decisions rational and success, and these factors are: 

1. Human Factors: There are many human factors that affect management decisions, and these factors with regard 

to the manager the same decision maker, which affects the rational resolution deep understanding of things and 

his anticipation and ability to innovate and take responsibility, and qualifications of the personal and scientific, 

cultural, experience, and ethics and its ability to act in difficult situations and social relationships. Human factors 

also aides the manager and his staff by virtue of their proximity and influence it, their thinking and way of 

display of the subject affect the process have taken decisions (Canaan, 2007). 

2. Laws, regulations and instructions: it takes into account the decision-makers not to with laws, regulations and 

directives in force, and may represent these factors obstacles to the manager for creativity, but in return they help 

to control process and control decision-making processes (Issa, 1993). 

3. Regulatory elements: The pattern of organization and philosophy and multiple levels of management, and in the 

values of the manager and staff and their interests and the extent of their agreement, as well as affect the internal 

and external pressure against the manager and staff, and the nature of administrative communication, which shall 

receive through the information and data required for a decision, therefore, the rational safety and management 

decisions depend on good communications and the speed and effectiveness in the performance of its mission 

(Canaan, 2007). 

4. Information System: The effectiveness of the decisions on the availability and integration of the necessary 

information and the accuracy, integrity and the organization so that they can use and benefit from, and represent 

the organization's ability to provide the necessary information quickly and demand basis to rationalize the 

management decision-making (Essa, 1993). 

5. Environmental factors and other pressures: There are many factors that affect the rational decision-making, 

especially in public institutions, the nature of the economic system and the existing political and social traditions, 

and spirituality, religious, and the pressures faced by managers, both internal, such as the centers of power within 

the organization, superiors and subordinates and interests between the conflicting organization, or external 

pressures such as public opinion and economic pressures such as the case of inflation, deflation, supply and 

demand, and government fiscal policy, as well as pressure control devices, whether internal or external (Canaan, 

2007). 

Participation is an important process contributing to reach the right decision, and affect the process of 

participation on decision-making process from the identification of the problem, until the stage to reach the 

decision, as the personnel are involved in the administration in identifying the problem and the collection of 

information, discussion and analysis, and after the manager takes the appropriate decision, the role of employees 

does not end when you participate in decision-making, but may extend also to the implementation of the 

resolution, and participation is the group's decision-making tool for the success of the resolution and easy to 

apply, because the group's participation in decision-making process means they understand it and thus contribute 

to the application (Khadra, 1979). Prahalad (1990) explain that one of the major problems in participation of 

effective decision making is that all the literature and consultants have suggested that participation in the 

motivation. 

The reason for the multiplicity of human activities, primarily to the large number of motivations and concerns in 

man, individuals working to diversify the behavioral patterns that are made in order to achieve the goals or 

satisfy the motives (Zgoul, 2000). The concept of motivation to internal situations of the individual that drives 

behavior, and orientation towards a specific goal, and maintain continuity in order to achieve the desired target, 

motive refers to the tendency interior of the individual to achieve a goal, this goal may be to satisfy the needs of 

the internal or the wishes of the party (lentil, Qatami, 2006). 

And known motivation as: "The impact of the events: the cognitive function that guide behavior, and function of 

counseling, which supplies the individual card movement, also known as a case of raising, and internal tension 

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give rise to behavior, and pay to achieve a particular goal (Khalifa, 2000). Qatami (1992) define motivation: "It 

is an internal case of an individual evoke behavior, and work to continue, and directed towards a specific goal." 

He explain motivation known as: "state of internal guides and supports the response, and can not be observed 

directly but inferred from the external behavior." The need for achievement as "a ready prompt pay the 

individual to confront challenges in order to obtain success and excellence, and this preparation leads the 

individual to set goals is difficult but achievable, and to calculate the risk and work to find new solutions and 

creative to the problems rather than adopting traditional solutions and take personal responsibility for the results 

of his behavior (Qatami,1992). 

Based on these perceptions, the motivation for achievement is defended human complex and the compound is 

characterized by access to achieve the difficult things as quickly as possible, and the advantage of risk, and fun 

competition, which increases the likelihood of success of failure, which activates the human behavior, and 

guided toward success, and achievement of the goal that seeks to achieve. 

Classification of motives: 

Motives can be classified into two types: (lentil, Qatami, 2006) 

1. Primary motivations (biological), which is the biological underpinnings of motivation such as hunger, thirst, rest 

and sleep. With regard to the relationship of these motivations to social factors, although not affected by 

biological drives directly to social factors, but the satisfied depends on the process of social learning. 

2. Secondary motivation (psychological or social), a motive which has no biological basis, such as ownership, 

respect, excellence and control. Featuring the motives of the biological motivations as they appear in the 

individual through interaction with others, including the motives of a sense of competence and merit and the 

search for new experiences. 

METHODOLOGY 

Sampling: 

Was selected sample of the study the way random from all employees in the Jordanian banking industry, and 

thus formed the study sample of (250) employees and a employee, and was distributed questionnaire study them, 

and after the recovery of the questionnaires, and correct, and the exclusion of the invalid, which include the 

study sample consisting of (167) employers and employees, of whom (96) and factor (71) and the employee, the 

table shows (1) the distribution of members of the study sample. 

Table 1: Sample distributions 

Variables Levels N Percentage 

Gender Male 96 45.5 

Females 71 54.5 

Experience Less than 5 years 61 36.4 

5-10 years 38 22.7 

More than 10 years 68 40.9 

Qualifications Bachelor or below 144 86.4 

Graduate 23 13.6 

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Instrument 

To achieve the goal of the study, the researcher developed a instrument to measure the variables of the study, and 

formed a tool of the study (60) items of which (32) items measures the participation of employees in strategic 

decision-making are distributed on four areas: decisions related to them, and measured by (1-9) items, and 

decisions related to managers and measured by (10-17) items, and decisions related to work and measured by 

(18-24) items, and decisions related to the local community, measured by (25-32) items, and (28) items measure 

employees' motivation to work and measured by (33-60) items, using a standard Likert scale five-rank, which 

range answer from one degree to the answer (very few), and two degrees to the answer (a few), and three degrees 

to the answer (medium), and four degrees to the answer (large), and five degrees before the answer (very large), 

and consisted tool study of three parts: the first part of primary data and are: gender (male, female), experience 

(less than 5 years, 5-10 years, and more than 10 years), and Qualification (BA and below, postgraduate). While 

the second part concerns the measurement of the degree of participation of employees in strategic decisionmaking, 

and the third part measures the motivation to work. 

Responses were divided as follows: There are five alternatives in the resolution, but these alternatives are five 

four categories: Category I (1 - 1.99), second (2 - 2.99), third (3 - 3.99), fourth (4-5). Number of classes are 

divided by the number of levels of the three averages, the result is 4 / 3 = 1.33 and the process of calculation 1 

1.33 = 2.33 So, if the arithmetic average ranged between (1-2.33) is a low-level 

2.33 1.33 = 3.66 So, if the arithmetic average ranged between (2.34 - 3.66) is the average level. Between what 

was (3.67 - 5) have a high level. 

Validity 

The instrument of the study has been reviewed by a number of specialists in the administrative area, amounting 

in number (10) raters, to see the relevance, validity and items are used to measure the variables of the study, and 

belonging to a domain that has developed within it, as it was modified the wording of some items. 

Reliability 

The factor of internal consistency of the instrument of the study, according to the responses of employees to 

identify the degree of their agreement on the instrument study based on Cronbach-Alpha formula for each area of 

participation of employees in strategic decision-making, and motivation to work, and table (2) shows the 

coefficient reliability, since the values of coefficient of internal consistency is acceptable. 

Variables 

Table 2: Cronbach-Alpha coefficient for the study instrument 

Participation in strategic decision-making decisions 

related to them 

Cronbach-Alpha coefficient 

0.84 

Decisions on managers 0.89 

Work-related decisions 0.89 

Decisions concerning the community 0.92 

Motivation to work 0.88 

 

 

Study concepts 

This study includes the following concepts: 

Participation in strategic decision-making: is a set of social relations within the organization under which 

employees take the decisions for the completion of work, and the report of the working conditions. 

Work motivation: the condition of internal and external to the individual that work the behavior, and directed 

towards a specific goal, and maintain the continuity of behavior until you achieve that goal. Known as 

procedural: the total score achieved by the teachers and parameters on the identification of the paragraphs of 

motivation. 

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The Limits of the Study and its Determinants 

The boundaries of the study and its determinants as follows: 

The application of this study was limited to employees in the Jordanian banking industry in 2010. 

Determined that the results of this study on the implications of validity and reliability of the tools in the study 

used. 

Analytical procedures 

 

 

To achieve the objectives of the study was the use of statistical software packages for the Social Sciences (SPSS) 

to answer the questions of the study, as follows: - 

Means and standard deviations, grade to answer the question I and II. 

Pearson's correlation coefficient to answer the third question. 

RESULTS 

The first results on answering the first question, which read, "What degree of participation of employees in 

strategic decision-making in the Jordanian banking industry 

To answer this question were calculated means and standard deviations for the degree of participation of 

employees in strategic decision-making in the Jordanian banking industry on each area of study tool, the table 

shows (3) that. 

No. 

Table 3: Means and standard deviations, rank and degree of participation of employees 

in strategic decision-making in the Jordanian banking industry in descending order 

Strategic decision-making 

variables 

Means 

Standard 

deviation 

Rank 

Participation 

level 

2 decisions on managers 3.45 0.97 1 Medium 

1 Resolutions of their 3.37 0.91 2 Medium 

3 work-related decisions 3.34 0.97 3 Medium 

4 decisions concerning the 

community 

3.04 1.01 4 medium 

Total 3.30 0.84 - Medium 

Notes from the table (3) that the degree of participation of employees in strategic decision-making in the 

Jordanian banking industry was moderate, with mean (3.30) standard deviation (0.84), came the areas of 

instrument study, all medium, with a range means between (3.45 to 3.04 ), and came in first order the decisions 

managers with mean (3.45) and a standard deviation (0.97), and in the second order came the decisions on their 

mean (3.37) and a standard deviation (0.91), and rank third came the decisions relating to work an average 

(3.34) and a standard deviation (0.97), and came in fourth grade and final decisions on the field of the local 

community mean (3.04) and a standard deviation (1.01). 

II: Results of answering the second question, which read, "What level of motivation of employees in the 

Jordanian banking industry to work 

Was calculated means and standard deviations of the level of motivation of employees in the Jordanian banking 

industry into a business, and the table shows (4) that. 

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Items 

No. 

Table 4: Means and standard deviations of the level of motivation of employees 

in the Jordanian banking industry to work in descending order 

Items Means Standard 

deviation 

rank 

Motivation 

level 

54 I feel happy when my success in achieving my goals. 4.62 0.67 1 High 

55 I have the ability to take responsibility. 4.57 0.70 2 High 

60 Always happiest when my success in raising the readiness of 

my colleagues about the work. 

4.57 0.68 2 High 

36 I am trying to achieve success in my work. 4.56 0.73 4 High 

57 I will do my best at work. 4.55 0.72 5 High 

56 Do my job to the fullest. 4.53 0.70 6 High 

33 Be sure to complete the work shown. 4.52 0.73 7 High 

50 I am trying to achieve excellence in my work. 4.50 0.75 8 High 

58 I am trying to implement the action plan accurately 4.49 0.73 9 High 

46 I try my best to achieve my ambitions. 4.46 0.75 10 High 

34 I completed the work required to perfection and dedication. 4.45 0.73 11 High 

35 Be sure to complete the work on time. 4.44 0.76 12 High 

53 I have confidence to achieve success 4.44 0.72 12 High 

43 I try to always search for solutions to the problems I am 

encountering. 

47 I am trying to achieve business objectives efficiently and 

effectively. 

4.43 0.74 14 High 

4.43 0.75 14 High 

37 Had the will power to accomplish the tasks required of me. 4.42 0.78 16 High 

42 I try my best to overcome the difficulties faced by my work. 4.42 0.77 16 High 

44 Always trying to develop my knowledge of the work. 4.42 0.75 16 High 

45 I look forward to developing my career. 4.41 0.77 19 High 

40 Make me appreciate others for me to make more effort. 4.40 0.85 20 High 

51 Held practical results Atousel it. 4.39 0.77 21 High 

38 Had the patience and the ability to withstand the rigors of 

work. 

41 discriminate the perseverance and the challenge of doing 

business difficult. 

4.38 0.78 22 High 

4.34 0.79 23 High 

59 I am leading the implementation of ideas without hesitation. 4.32 0.79 24 High 

39 I am trying to take the lead in the work. 4.26 0.81 25 High 

48 I put a future plan for the performance of my work. 4.26 0.85 25 High 

52 I think that my status in the community satisfactory. 4.14 0.93 27 High 

49 I am trying to participate in volunteer work. 4.10 0.94 28 High 

Total 4.42 0.56 - High 

Notes from the table (4) that the level of motivation of employees in the Jordanian banking industry about the 

work was high, as the mean (4.42) standard deviation (0.56), and came items of this area are all high, ranging 

from means between (4.62 -4.10), came in the first order of item (54) is "I feel happy when my success in 

achieving my goals" mean 4.62 and a standard deviation (0.67), and in the second order came item (55) "I have 

432


the ability to take responsibility" and (60) "the happiest Always when my success in raising the willingness of 

colleagues to work "with mean (4.57) and two standard deviations (0.70) and (0.68), respectively, and in the 

level before the last came item (52)" I think that my status satisfactory in society "mean my account (4.14) and 

the deviation standard (0.93), and came in the last item level (49) "I am trying to participate in voluntary work" 

mean (4.10) and a standard deviation (0.94). 

Third, results related to answer the third question, which read, "Is there a relationship statistically significant at 

the level of significance (0.05 ≥ α) between the participation of employees in strategic decision-making and 

motivation towards working in the Jordanian banking industry 

To answer this question, the correlation coefficient was calculated between the participation of employees in 

strategic decision-making and motivation towards working in the Jordanian banking industry using the Pearson 

coefficient, and the following table shows this. 

Table 5: The correlation coefficient between the participation of employees 

in strategic decision-making and motivation towards working the Jordanian 

banking industry using the Pearson coefficient 

Variables Correlation coefficient Sig. 

Decisions related to them 0.300 0.000* 

Decisions on managers 0.300 0.000* 

Business decisions 0.269 0.000* 

Decisions on the local 

community 

0.197 0.000* 

College degree 0.305 0.000* 

*p-value ≤ 0.05 

Table (5) show of statistical significance correlation between the participation of employees in strategic 

decision-making and motivation towards working in the Jordanian banking industry both in the total score, as 

was the correlation coefficient (0.305) level of significance (0.000), and (0.300) for the areas of decisionrelevant 

to them, decisions on the level of significance managers (0.000), and (0.269) for the field of the 

decisions on the level of significance (0.000), and (0.197) for the decisions on the local community level of 

significance (0.000). 

CONCLUSIONS 

 

 

 

The degree of participation of employees in strategic decision-making in the Jordanian banking industry was 

moderate, and came in first order the decisions managers, and in the second order came the decisions related to 

them, and rank third was the area of business decisions, and came in rank fourth and final area of the decisions 

related to the local community. 

The level of motivation of employees in the Jordanian banking industry about the work was high, and came in 

first order, "I feel happy when my success in achieving my goals," In the second order came, "I have the ability 

to take responsibility" and "happiest always at my success in raising the willingness of my colleagues about 

work ", and in the level before the last came," I think that my status in society satisfactory, "and came in the final 

grade" I am trying to participate in volunteer work. " 

A correlation of statistical significance between the participation of employees in strategic decision-making and 

motivation towards working in the Jordanian banking industry. 

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RECOMMENDATIONS 

According of the findings of this study, the following recommendations can be adopted for banking industry: 

1. Activating the participation of employees in making strategic decisions related to them through their 

participation in decisions regarding the placement of the courses they need. 

2. Activating the participation of employees in making strategic decisions about working through their participation 

in decisions concerning the status of the plans, and forming committees. 

3. Activate the participation of employees in decision-making strategy for the local community. 

4. Further studies that address the participation of employees in strategic decision-making in other industrys. 

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