Geothermal Energy Potential in Selected Areas of Western Australia ...

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27 When the heat flow values for multiple wells (in the same field) in the Perth Basin are expressed as a single median value and compared to other fields, the overall basin median declines to 76.5 mW/m 2 . This value is about 18.6% higher than the Australian median value. 5.2. Reliability of heat flow data The major source of uncertainly in heat flow calculations is thermal conductivity. HDRPL has necessarily made certain assumptions about conductivity in this broad review of heat flow. The calculated heat flow values are valid so long as these assumptions hold true: • The conductivity of individual formations can be characterised by a single value and uncertainty margin. • Core specimens housed in the DoIR core library are representative of the formations from which they were derived. • Lithologies of unsampled formations are relatively typical, with conductivities similar to those measured globally on similar lithologies HDRPL considers the major uncertainties to lie in the conductivity estimates for coalbearing units. Coal is an excellent thermal insulator and even small concentrations can significantly reduce the bulk conductivity of a formation. For this study, HDRPL chose to assign measured values for the conductivity of coal measures, based on samples obtained from the DoIR core library. The assumption of a single characteristic conductivity value is unlikely to hold for the coal measures. The heat flow values for wells containing significant proportions of coal measures are, therefore, of lower reliability than other wells. HDRPL recommends a detailed examination of evidence for coal distribution and thickness, and the thermal conductivity implications of these parameters. almost certain to understate the true formation temperature (Beardsmore and Cull, 2001 9 Modelled outcomes also depend upon the quality and quantity of temperature data. Where temperature data were Horner corrected, temperature errors were estimated as ±3°C. Uncorrected temperature data are ), hence modelling with these www.hotdryrocks.com
28 data requires a positive error margin. Where uncorrected BHTs were used, a maximum positive error margin was derived by comparing corrected and uncorrected temperature values in wells with Horner corrected values. Such wells were modelled for heat flow using the mid-point between the temperature value and the positive error bar. The influence of low-reliability data tends to bias heat flow towards the lower end of the distribution. This is illustrated in the distribution of heat flow results for individual wells in the Dongara Field (Figure 5.2). Modelled heat flow values were ascribed a relative reliability ranking based on a qualitative assessment of the well temperature, depth and lithology data (Attachment K). The relative reliability of data is illustrated spatially in Figure 5.3 with increasing point size denoting increasing relative reliability. Frequency 16 14 12 10 8 6 4 2 0 Histogram of Dongara Field Heat Flow Data (Perth Basin) Low Qual. Ave = 96.7 All Ave = 99.7 80 85 90 95 100 105 110 115 120 Heat Flow (mW/m2) www.hotdryrocks.com Mod-High Qual. Ave = 102.6 Figure 5.2 Distribution of modelled surface heat flow for 28 wells in Dongara Field showing the influence of lower quality (uncorrected) temperature data on modelled heat flow. Wells with “low” quality temperature data have an average modelled heat flow of 96.7 mW/m 2 , whilst those with “moderate-high” quality data have an average modelled heat flow of 102.6 mW/m 2 .
Page 1 and 2: Hot Dry Rocks Pty Ltd Geothermal En
Page 3 and 4: • The distribution of heat flow v
Page 5 and 6: 2 List of Figures Figure 2.1 Strati
Page 7 and 8: 4 1. Introduction The Department of
Page 9 and 10: 6 inverted Permian half graben in t
Page 11 and 12: 8 Figure 2.2 Basin subdivisions and
Page 13 and 14: 10 east. The major sub-basin in the
Page 15 and 16: 12 Figure 3.1 Gravity image with OZ
Page 17 and 18: 14 Figure 3.3 Gravity image with OZ
Page 19 and 20: 16 4. Heat flow modelling methodolo
Page 21 and 22: 18 circulation. The accuracy of the
Page 23 and 24: 20 Table 4.1 Summary of rock therma
Page 25 and 26: 22 column. OZ SEEBASE depth-to-base
Page 27 and 28: 24 4.7. Estimating basement heat ge
Page 29: 26 5. Heat flow modelling results 5
Page 33 and 34: 30 The Dongara Field has 28 wells t
Page 35 and 36: 32 Figure 5.5 A bivariate plot of a
Page 37 and 38: 34 Figure 6.1 Inferred and gridded
Page 39 and 40: 36 Figure 6.3 Inferred and gridded
Page 41 and 42: 38 7. Stress field in the Perth Bas
Page 43 and 44: 40 King et al. (2008) 14 reported s
Page 45 and 46: 42 Regional Shmax Figure 7.2 Major
Page 47 and 48: 44 7.5. Recommendations for Stress
Page 49 and 50: 46 • Examine evidence for coal di
Page 51 and 52: 48 56 Dongara 25 W001065 DEV N GDA9
Page 53 and 54: 50 Attachment B: 80 wells previousl
Page 55 and 56: 52 Attachment C: Basement litholog
Page 57 and 58: 54 Well name TD (m) Probable Baseme
Page 69 and 70: 66 Attachment F - Recalculated cond
Page 71 and 72: Attachment H - Calculated heat gene
Page 73 and 74: Attachment J - Calculated heat gene
Page 75 and 76: 72 Dongara 12 3750 Gneiss N -29.238
Page 77 and 78: 74 Murrumbah 1 3750 Gneiss N -29.15
Page 79 and 80: Well name Overall reliability (high
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Well name Overall reliability (high
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Overall reliability (high, low, Hea
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Executive summary The Western Austr
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2 1.0 Introduction Thermal conducti
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4 2.0 Methodology Hot Dry Rocks Pty
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6 Gage Sandstone Quinn's Rock 1 776
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8 Sue Group: Ashbrook Sandstone Sue
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10 3. Thermal conductivity of rocks
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Table of Contents 1.0 HEAT FLOW MOD
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