8 re 045 rec res 1 rec res 2 rec res 3 rec res 4 rec

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Unformatted text preview: Hespos and Straussman (1965) have shown how the simulation approach can be extended to handle investment problems involving sequences of decisions using a method known as stochastic decision tree analysis. 103 Type of distribution assigned to reach reservoir parameter for each run Reservoir Base parameters value GRV 0.2 N/G 0.8 Porosity 0.32 Shc 0.8 Re 0.45 Rec Res 1 Rec Res 2 Rec Res 3 Rec Res 4 Rec Res 5 Rec Res 6 Normal Triangular Triangular Triangular Triangular Rec Res 7 Normal Triangular Lognormal Triangular Triangular Rec Res 8 Normal Normal Triangular Uniform Triangular Uniform Triangular Triangular Lognormal Triangular Rec Res 9 Rec Res 10 Normal Lognormal Lognormal Lognormal Lognormal Rec Res 11 Normal Lognormal Lognormal Lognormal Lognormal Rec Res 12 GRV 0.2 Normal Lognormal Lognormal Weibull Normal Beta N/G 0.8 Triangular Weibull Uniform Weibull Beta Weibull Porosity 0.32 Weibull Beta Uniform Weibull Pareto Triangular Shc 0.8 Triangular Uniform Uniform Weibull Uniform Lognormal Re 0.45 Triangular Triangular Uniform Weibull Weibull Weibull Table 5.5: Base value data and probability distributions assigned to each of the reservoir parameters (GRV=gross rock volume, N/G=net to gross, Shc=hydrocarbon saturation, Re=recovery efficiency, Rec Res=recoverable reserves) Percentile Rec Rec Rec Rec Rec Rec Reserves Reserves Reserves Reserves Reserves Reserves 1 2 3 4 5 6 0% 107 93 97 95 94 79 10% 138 132 132 132 137 120 20% 146 143 142 142 145 133 30% 152 150 150 151 153 141 40% 157 157 156 158 158 150 50% 163 162 163 164 164 160 60% 167 169 169 172 170 170 70% 173 176 177 180 176 181 80% 180 185 188 188 184 196 90% 189 198 203 203 196 217 100% 228 255 263 281 260 339 Percentile Rec Rec Rec Rec Rec Rec Reserves Reserves Reserves Reserves Reserves Reserves 7 8 9 10 11 12 0% 150 5 105 2359 17 9 10% 314 44 132 11599 246 113 20% 399 66 141 16651 382 175 30% 467 84 149 21955 527 225 40% 523 103 157 27209 675 280 50% 598 125 163 32842 817 337 60% 657 148 170 40866 984 404 70% 726 176 178 48650 1206 498 80% 817 205 187 62966 1544 626 90% 971 250 201 88855 2273 819 100% 1938 546 287 237909 17143 2903 Table 5.6: Table of the output generated using the base value data and input distributions specified in Table 5.5 (Rec reserves = recoverable reserves) The next section draws on the decision theory and industry literatures to present portfolio theory, a technique that has been used within the finance industry for a 104 number of years but which has only recently been applied to petroleum investment decisions. Therefore, the concepts of portfolio theory will be outlined first before its applicability to upstream investment decision-making is analysed. 5.5 PORTFOLIO THEORY In practice, a business will normally invest in a range, or portfolio, of investment projects rather than in a single project. The problem with investing all available funds in a single project is, of course, that an unfavourable outcome could have disastrous consequences for the business. By i...
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This document was uploaded on 03/30/2014.

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