Z-99 Investigating the detectability of gas sands offshore ... - PGS

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Z-99 Investigating the detectability of gas sands
offshore South Africa by means of AVO
modeling
Jürgen Hoffmann 1 and Raymond Durkan 2
1 PGS Geophysical, P. O. Box 354, N-1326 Lysaker, Norway
2 Sasol Petroleum International, P. O. Box 5486, Johannesburg 2000, South Africa
Introduction
In November 2001, Sasol Petroleum International concluded a production sharing agreement for South African
Block 3A/4A, located in the Orange Basin off the western coast of that country. Several unsuccessful wells had
been drilled in the area in the 1970’s and 1980’s, with failures being due primarily to a lack of structural closure
and/or severe reservoir diagenesis. However, a well in an adjacent block tested stratigraphically trapped gas at
high flow rates in relatively thin Albian sandstones. Due to the lack of a gas market, development was not
feasible at that time. This discovery is currently being developed by Forest Oil International.
Sasol’s evaluation of existing 2D seismic data in Block 3A/4A resulted in the identification of a low impedance
amplitude anomaly correlative to a wet Cenomanian sand, outside the anomalous area, in the A-L1 well. The
sand in A-L1 has a gross thickness of approximately 100 m and is interpreted to be a shallow marine unit. It
overlays a thick sequence of thin, probably fluvial, Albian sands, which are seen as a potential secondary
objectives.
PGS was contracted to acquire a 300 sq km 3D survey in November and December 2001 to better define the
areal extent and shape of the Cenomanian anomaly and to identify any anomalies in the Albian sands.
Concurrent with the data acquisition, PGS, using log data from A-L1, modeled the expected AVO response of
the Cenomanian sand to predict the effect of gas and to identify critical processing displays.
Methodology
AVO analysis is one of the fundamental tools in the exploration of gas sand provinces. Close-by well log data
are mostly used for the purpose of AVO modeling and prediction of the gas sand AVO signature in order to
validate the feasibility of using AVO attributes in the actual prospect area. AVO modeling requires that P-wave
and S-wave velocity data as well as density values are available in order to use the various forms of Zoeppritz
based AVO formulas or elastic modeling methods. Nearly always one of these parameters, often the shear wave
velocity, or other important factors like gas properties are not known and need to be predicted. This introduces a
significant uncertainty in the AVO prediction and needs to be addressed.
For the named exploration project offshore South Africa, we were faced with the situation, that only the data
from a neighboring brine-filled well without shear wave information were available and no exact values about
gas fluid properties known. We therefore designed a methodology for investigating the detectability of the AVO
signature of gas sands using AVO modeling.
The purpose of the study was to predict
- if gas sands could be identified by their distinct AVO behavior,
- what are the controlling factors in the AVO signature,
- relevant offset range for AVO processing, and
- what gas sand layer thickness could still be resolved.
We can separate our work in three main phases:
(a) petrophysical analysis of log data and estimation of elastic parameters using rock physics,
(b) visco-elastic modeling of the seismic response based on log-derived elastic parameters, and
(c) sensitivity analysis w.r.t. the predicted or inaccurately known parameters.
EAGE 64th Conference & Exhibition — Florence, Italy, 27 - 30 May 2002

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Figure 1 Result from the
petrophysical log analysis (CPI
computed petrophysical
interpretation). The target sands
(black arrow) are clearly indicated by
the large sand volume (yellow)
between 1650 m to 1750 m and a
porosity of about 20 %.
Petrophysical analysis and rock physics
Standard petrophysical well log analysis (Figure 1) was performed on the provided data set to calculate porosity
and shale volume. Since no shear wave information was contained, we predicted the shear wave using the
empirical Vp-Vs relations from Castagna et al. (1993) for brine-saturated rocks. We have chosen a simple Vs
prediction, since every Vs prediction may be error prone due to the variability of Vp-Vs relations and the lack of
reference data for Vs. We rather decided to address this uncertainty using AVO likelihood analysis.
After log analysis and Vs prediction, the required seismic parameters Vp, Vs and density were available,
however, only for the case of brine filled sands. Fluid substitution allows the prediction of corresponding
parameters for the case of gas filled pores. The other required parameters were selected based on standard
published data for quartz, brine and gas. We applied the Gassmann fluid substitution formula (Gassmann, 1951)
to replace the brine with gas within the target sands using the equations as described in Mavko et al. (1998,
chapter 6.3).
The change in Vp velocity due to fluid substitution is observed in Figure 2. The velocity for the gas sands is
reduced by about 300 m/s compared to that in the water sands. While many parameters affect the result of the
fluid substitution, the single most important one is the bulk modulus of the new fluid, i.e. that of the gas (Mavko
and Sengupta, 1999).
Figure 2 Log-plot of Vp versus depth for
both cases, i.e. brine filled target sands
(gray dots) and gas filled target sands
obtained by fluid substitution (colored
dots). The main effect of substituting
brine by gas in the reservoir is a reduction
of Vp by about 300 m/s. Vs and density
remain largely unchanged. The color code
shows the calculated porosity.

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Elastic modeling
The seismic response for both data sets was modeled using a visco-elastic reflectivity algorithm. The modeling
included interbed multiples, converted waves, absorption (based on typical quality factor values of Qp=200 and
Qs=100). Figure 3 shows a comparison between the AVO signature from brine and gas filled sands, where the
distinct class 3 AVO response for the gas sands can be observed.
Using these synthetic data and the model-based information about the incidence angle, we calculated angle range
stacks (Figure 4) to illustrate the expected signal after processing. The gas sand AVO characteristic is clearly
seen here, also.
Figure 3 Part of a synthetic shot gather for the case of gas filled target sands (left) and brine filled sands (right).
Geometrical spreading correction and LNMO were applied based on the model parameters. The shown offsets
range from 200 m to 2000 m. The top target sand reflection appears at about 1.44 s twt as black event with
increasing amplitude with offset for the gas case. The seismic data are underlain by the incidence angle for
primary reflections at the appropriate time and offset.
Figure 4 Angle range stack for gas filled target sands (left) and brine filled sands (right). The three angle
ranges used were 0 – 10 degree, 10 – 30 degree and 30 – 45 degree. The top reflection from the target sands
appears at 1.44 s twt.
Sensitivity analysis
Due to the variability of the target sand properties and the uncertainty in the shear wave velocity prediction, we
performed a sensitivity analysis. Based on average values for the seismic parameters in the shale section and for
the target sands, the AVO response of a single interface between overlying shale and target sands was
investigated for two cases:
Case 1: Shale overlying brine filled sands (marked as red crosses)
Case 2: Shale overlying gas filled sands (marked as blue circles)
For the two scenarios we calculated the AVO response while taking into account specified uncertainty limits.
The exact AVO response for all cases within the specified uncertainty limits was then inverted using a linearised
method to estimate the AVO attributes intercept B0 and gradient B1. These AVO attributes were then crossplotted
to analyse the ability to separate the values from the gas case and the brine case. The sensitivity analysis
was performed for the most uncertain or influential parameters, i.e. the bulk modulus of the gas, and the shear
wave velocity.
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Assuming the other seismic parameters are relatively well known, we specified an error range of ±100 m/s for
Vp of the gas filled sands. This corresponds to a change of about 0.8 GPa in fluid bulk modulus, which is
conservative considering typical moduli of 2.3 GPa for brine and less than 0.6 GPa or less for gas. The AVO
cross plot of intercept and gradient for this case (Figure 5 left) shows that even for such a low difference in fluid
compressibility, the gas and the brine case are quite well separated and promise good discrimination.
In the second exercise, we assumed all parameters well known except for the shear wave velocity for the shale
and the sands. For Vs we specified a conservative uncertainty range of ±250 m/s. Repeating the cross plot for
this case (Figure 5 right) we can observe that the red crosses (brine sands) and blue circles (gas sands) are well
separated. This indicates that the AVO response is not very sensitive to the shear wave velocity and therefore
the simplified Vs prediction can be justified in our case.
Figure 5 AVO cross plot of intercept B0 vs. gradient B1. Case 1 with brine filled sands (red crosses) and case 2
with gas filled sands (blue circles). Left: Uncertainly in the P-wave velocity in the gas sands of ∆Vp_sands =
±100 m/s. Right: Uncertainly in the shear wave velocity of ∆Vs = ±250 m/s.
Conclusions
Based on the well logs, we conclude that gas sands in the prospect area will exhibit an AVO class 3 behavior,
which can be detected and discriminated from brine sands by AVO analysis.
The two main uncertainties in this study are due to the prediction of the shear wave velocity Vs based on the
petrophysical interpretation of the lithology, and the selected value for the bulk modulus of the gas. The
sensitivity analysis showed that the latter, i.e. gas bulk modulus or Vp for the gas sands, is the controlling factor,
while the gas sand detection via AVO is not very sensitive with respect to the shear wave velocity.
An extended analysis addressing the detectability of gas sands with respect to sand layer thickness showed that a
distinct gas sand AVO character can be observed even for layers as thin as 17 m.
References
[1] Castagna, J.P., Batzle, M.L., and Kan, T.K., 1993. Rock Physics – The link between rock properties and
AVO response. In: Offset-dependent Reflectivity, Theory and Practice of AVO Analysis, (eds Castagna,
J.P, and Backus, M.), pp 135-171. Society of Exploration Geophysicists.
[2] Sengupta, M. and Mavko, G., 1999, Sensitivity analysis of seismic fluid detection, 69th Ann. Internat.
Mtg: Soc. of Expl. Geophys., 180-183.
[3] Gassmann, F., 1951. Über die Elastizität poröser Medien. Vier. der Natur. Gesellschaft in Zürich, 96, 1-
23.
[4] Mavko, G., Mukerji, T., and Dvorkin, J., 1998. The Rock Physics Handbook. Cambridge University Press.
Acknowledgements
We would like to thank the Petroleum Agency South Africa for providing the log data of well A-L1 and the
permission to show the data.