基于SPEE的美国二叠纪盆地储量评价集成工作流

Xiaoyang Xia, Eric T. Nelson, Daniel J Olds, L. Connor, He Zhang
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摘要

2011年,石油评价工程师协会(SPEE)发布了第3篇专论,作为非常规油气储量评价的行业指南,特别是概率方法。本文阐述了专论3推荐的工作流程。作者还指出了在应用指南时可能遇到的一些困境。最后,作者提出补救措施,以减轻局限性和提高该方法的效用。本案例研究包括二叠纪盆地约300口生产页岩井。参考专论3,根据位置、地质、钻完井(D&C)技术确定了类似井;然后利用递减曲线分析(DCA)对这些类似井的技术可采资源(TRRs)进行评价。其次,开发了具有不同统计特征的5口类型井。最后,确定了一些钻井机会,并进行了蒙特卡罗模拟,以建立每个类型井区未开发位置的统计分布。作者演示了最能代表研究区域的概率图和分箱策略的使用。作者根据多个标准调整了分组策略,包括每个横向长度的归一化trr的中位数、对数正态图中分布线的斜率、P10 / P90的比率、每种类型井类别的井数以及其他变量。分组试验基于不同的地理区域、生产油藏和作业者,并包括石油工程师协会(SPE) 2018年石油资源管理系统(PRMS)引入的相对较新的“学习曲线”概念。据作者所知,这篇论文是第一个将“学习曲线”方法考虑在内的公开案例研究。本文通过编码数据库查询或操作实现了图示工作流的自动化,从而提高了分组策略多次试验的效率。演示的案例研究说明了基于数据分析的有效决策过程。案例研究进一步确定了消除偏见的方法,并提出了独立客观的储量评估。这里的大多数挑战和情况没有在专论3中得到充分解决,也没有在美国证券交易委员会(SEC)的法规或PRMS指南中记录。虽然可能会有不同的方法,并且一些分析人员可能更喜欢替代方法,但作者认为,这里提出的项目将使许多开始将Monograph 3纳入其工作过程的人受益。作者希望这篇文章能在我们的行业中引起更多的讨论。
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An Integrated Workflow for Reserves Evaluation in the U.S. Permian Basin Based on SPEE Monograph 3
In 2011, the Society of Petroleum Evaluation Engineers (SPEE) published Monograph 3 as an industry guideline for reserves evaluation of unconventionals, especially for probabilistic approaches. This paper illustrates the workflow recommended by Monograph 3. The authors also point out some dilemmas one may encounter when applying the guidelines. Finally, the authors suggest remedies to mitigate limitations and improve the utility of the approach. This case study includes about 300 producing shale wells in the Permian Basin. Referring to Monograph 3, analogous wells were identified based on location, geology, drilling-and-completion (D&C) technology; Technically Recoverable Resources (TRRs) of these analogous wells were then evaluated by Decline Curve Analysis (DCA). Next, five type-wells were developed with different statistical characteristics. Lastly, a number of drilling opportunities were identified and, consequently, a Monte Carlo simulation was conducted to develop a statistical distribution for undeveloped locations in each type-well area. The authors demonstrated the use of probit plots and demonstrated the binning strategy, which could best represent the study area. The authors tuned the binning strategy based on multiple yardsticks, including median values of normalized TRRs per lateral length, slopes of the distribution lines in lognormal plots, ratios of P10 over P90, and well counts in each type-well category in addition to other variables. The binning trials were based on different geographic areas, producing reservoirs, and operators, and included the relatively new concept of a "learning curve" introduced by the Society of Petroleum Engineers (SPE) 2018 Petroleum Resources Management System (PRMS). To the best of the authors’ knowledge, this paper represents the first published case study to factor in the "learning curves" method. This paper automated the illustrated workflow through coded database queries or manipulation, which resulted in high efficiencies for multiple trials on binning strategy. The demonstrated case study illustrates valid decision-making processes based on data analytics. The case study further identifies methods to eliminate bias, and present independent objective reserves evaluations. Most of the challenges and situations herein are not fully addressed in Monograph 3 and are not documented in the regulations of the U.S. Security and Exchange Commission (SEC) or in the PRMS guidelines. While there may be differing approaches, and some analysts may prefer alternate methods, the authors believe that the items presented herein will benefit many who are starting to incorporate Monograph 3 in their work process. The authors hope that this paper will encourage additional discussion in our industry.
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