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- W2555611885 abstract "Stochastic reserve estimate was analysed by integrating Monte-Carlo simulation and Parametric simulation techniques to quantify uncertainty in reserve estimate with the result compared with Crystal Ball software. Error parameters such as mean reward, standard deviation and coefficient of variation were deduced with low coefficient of variation value which gives good confidence, low risk and less uncertainty but with a deviation of -0.035882 and 0.263878 from Crystal Ball software for first and second simulation analysis respectively. Pre-determined interval was eliminated in this study by using Stugies rule in the algorithm while randomness of input parameters was achieved by using Chi- Square and 95% Chi-Square value. Sensitivity analysis of input parameters shows a decreasing order effect on reserve estimate from thickness, area, porosity, water saturation and formation volume factor for first and second simulation analysis respectively.." @default.
- W2555611885 created "2016-11-30" @default.
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- W2555611885 date "2015-01-01" @default.
- W2555611885 modified "2023-09-27" @default.
- W2555611885 title "Quantifying Uncertainty in Oil Reserves Estimate" @default.
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