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A New Tool to Make Quick Estimates of Probabilistic Reserves from Production Trends

机译：一种根据生产趋势快速估算概率储量的新工具

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摘要

The estimation of probabilistic distribution of reserves isrnincreasingly being used in the oil industry. However, this isrnnot an easy assignment because of the amount of informationrnrequired and costs associated. Even more complicated is therntask of evaluating distribution of reserves departing fromrnproduction trends. The historic analysis of production hasrnusually used a deterministic approach in the form of DeclinernCurve Analysis (DCA).rnIn this paper we present a quick and efficient application forrnestimating probabilistic distribution of reserves combining thernusually available production information with the power ofrnstochastic methods through the use of decline curve analysis:rnPREP (Probabilistic Reserves Estimation Package). Therncomputational tool developed uses a Monte Carlo-typerntechnique under an efficient optimization algorithm torncalculate the DCA parameters. More than 200 realizations canrnbe generated and evaluated in a few seconds for diversernproduction scenarios and information such as standard errors,rnconfidence intervals, expectation curves can be visualized tornuncertainty diagnosis.rnWe have applied the proposed tool on several fields located inrnthe Valle Superior del Magdalena Basin in Colombia, SouthrnAmerica. The Valle Superior del Magdalena Basin isrnestimated to contain over 1,400 million barrels of oil-in-placernof which only 14.7% have been produced. The resultsrnobtained have had strong economic impact on reservoirrnmanagement decisions.
机译：石油工业中越来越多地使用概率分布来估算储量。但是，由于所需信息量和相关成本，这并不是一件容易的事。评估与生产趋势背离的储量分配的任务更加复杂。生产的历史分析通常以DeclinernCurve分析（DCA）的形式使用确定性方法。本文中，我们提出了一种快速有效的应用程序，通过利用递减的方法结合可用的生产信息和随机性方法的能力，来估计储量的概率分布。曲线分析：rnPREP（概率储量估算包）。开发的计算工具在有效的优化算法下使用了Monte Carlo类型的技术来计算DCA参数。几秒钟之内就可以针对不同的生产场景生成和评估200多个实现，并且可以可视化标准误差，置信区间，期望曲线等信息来进行不确定性诊断。我们已经将该提议的工具应用于位于马格达莱纳河谷上谷的几个油田。哥伦比亚，SouthrnAmerica。瓦莱苏必利尔马格达莱纳盆地经过重新评估后，将容纳超过14亿桶的代孕油，仅生产了14.7％。获得的结果对储层管理决策产生了重大的经济影响。

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