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Probabilistic Prospect Evaluation With Spreadsheets

机译：电子表格的概率前景评估

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This case history describes the creation of a spreadsheetbased,rnMonte-Carlo economic model for explorationrnprospects. Looking at “probabilistic economics” instead ofrn“probabilistic reserves” allows decision-makers a betterrnunderstanding of the potential outcomes associated with arnprospect. Although commercial software exists for suchrnanalyses, creating this spreadsheet model proved morernefficient in this case through the utilization of spreadsheetrnalgorithms already in place. The simulation model is nowrnused routinely in-house for individual prospect analysis and isrnconsidered a viable alternative to the commercial packages.rnA probabilistic reserve distribution can be generated usingrnuncertainty distributions for volumetric input parameters andrnthen sampling the input distributions through Monte Carlornsimulation. After sampling the input distributions andrncalculating the corresponding reserves many times, arnprobabilistic distribution of reserves is created. Often in rankrnexploration prospects, a given reserve size is not a uniquernsolution to the volumetric equation. Different reservernscenarios, e.g. combinations of lateral extent and recovery perrnacre, may yield the same reserve size but may differ in capitalrnrequirements by an order of magnitude or more. In theserncases especially, it is appropriate to consider not only thernrange of reserve outcomes resulting from the full range ofrnpossible scenarios, but also the range of correspondingrneconomic outcomes for the many possible scenarios.rnMeanwhile every single realization within the range ofrnoutcomes must be realistic. Furthermore, by calculatingrneconomics stochastically, other probabilistic methods such asrnmean reverting price models may be incorporated.rnThe spreadsheet economic model was used because itrnprovides a significant advantage where evaluation time isrnlimited. For the evaluation described in this paper, thernanalysis of exploration prospects was accomplished within arnvery short time frame. As the prospects were in remoternlocations outside of the Lower 48 and estimation of capitalrnexpenditures and production taxes was complicated, arnspreadsheet program provided the desired degree of flexibility.rnThe model was created quickly since spreadsheet algorithmsrnalready existed to calculate reserves, capital, production taxes,rnmean reverting price forecasts, and AFIT economics.rnThis paper describes how five existing spreadsheetrnalgorithms were integrated to develop a robust Monte Carlorneconomic model for exploratory prospect evaluations.rnEmphasis is placed on the advantages of using the spreadsheetrnplatform to establish dependencies between variables and tornfacilitate customization of the model.
机译：本案例历史描述了基于电子表格的蒙特卡洛经济模型的创建，以进行勘探。考察“概率经济学”而不是“概率储备”可以使决策者更好地理解与预期有关的潜在结果。尽管存在用于此类分析的商业软件，但在这种情况下，通过利用已经存在的电子表格算法，创建这种电子表格模型被证明效率更高。现在，该模拟模型通常在内部用于单个前景分析，并被认为是商业软件包的可行替代方案。可以使用不确定性分布（用于体积输入参数）来生成概率储备分布，然后通过蒙特卡洛模拟对输入分布进行采样。在对输入分布进行采样并多次计算相应的储量之后，就创建了储量的概率分布。通常在等级勘探前景中，给定的储量不是体积方程的唯一解。不同的备用方案，例如侧向范围和采收率的组合可能产生相同的储量，但资本需求可能相差一个数量级或更多。特别是在某些情况下，不仅要考虑所有可能发生的情况所导致的储备结果的范围，而且还要考虑许多可能发生的情况所对应的经济结果的范围。同时，在结果范围内的每个实现都必须是现实的。此外，通过随机地计算经济学，可以合并其他概率方法，例如均值还原价格模型。使用电子表格经济模型是因为它在评估时间有限的情况下具有明显的优势。对于本文所述的评估，在很短的时间内完成了勘探前景的分析。由于潜在客户位于下48区以外的偏远地区，资本支出和生产税的估算很复杂，因此arnspreadsheet程序提供了所需的灵活性。rn由于电子表格算法已经存在，可以快速创建模型，因此已经可以计算储量，资本，生产税，均值还原价格预测和AFIT经济学。本文介绍了如何将五个现有的电子表格算法集成在一起，以开发用于探索性前景评估的稳健的蒙特卡洛经济学模型。重点放在使用电子表格平台建立变量之间的依存关系和简化模型自定义的优势上。

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