电容-电阻模型在泰国最大油田注水及提高采收率评价与优化中的应用进展

R. Laochamroonvorapongse
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引用次数: 0

摘要

水驱提高采收率的主要机理是注水驱油;然而,由于地质系统的复杂性、对井间连通性、垂向非均质性的认识有限,以及注入和生产控制的缺乏,导致注水效果低于预期。本研究旨在评估和优化泰国S1成熟油田正在进行的水驱和聚合物驱性能。电容电阻模型(CRM)是一种基于物理的储层模型,仅从生产、注入和压力数据的输入中得出井间连通性和储层性质。本研究以聚合物先导区和成熟水驱区为研究对象,利用Python语言构建了严谨的CRM模型与分流模型相结合的工作流程,对油藏进行动态分析。通过CRM模型匹配得到储层连通性图和储层物性,将两者耦合后的输出为防洪优化方案。如果有足够的生产数据,并且推导出的井间连通性与井间示踪剂结果、区域沉积供应方向和油藏工程师的注水分析结果吻合良好,则CRM模型可以很好地拟合井的产量。电潜泵(ESP)传感器输入的井底压力数据可以提高CRM管件的质量,特别是当油藏处于欠注入状态时。在优化研究中,以原油储量最大化为目标函数调整注入井速度,结果表明,总增量原油产量约为100万桶。推荐的注水优化方案已经实施,并正在现场进行评估。集成的CRM工作流可以取代3d -常规油藏模拟模型,该模型可能包含地质结构和特征的高不确定性。CRM还可以进行密集的注水和EOR评估,以及注水性能优化。该应用将是确保注水和提高采收率成功的关键。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Advancement in Waterflood and EOR Performance Assessment and Optimization with Capacitance-Resistance Model in the Largest Oil Field, Thailand
The main mechanism of waterflooding and enhanced oil recovery (EOR) is oil displacement by injected fluid; however, complexity in the geological system, limited understanding of interwell connectivity, vertical heterogeneity, and lack of injection and production controls lead to lower-than-expected flood performance. This study is aimed to assess and optimize the ongoing waterflood and polymer flooding performance in a mature S1 oil field in Thailand. The capacitance resistance model (CRM) is a physics-based reservoir model that derives interwell connectivity and reservoir properties solely from the input of production, injection, and pressure data. In this study, the rigorous workflow of CRM model coupled with fractional flow model was built by using Python language to dynamically perform the reservoir analysis focusing on the polymer pilot and mature waterflood areas. The reservoir connectivity map and reservoir properties were obtained from the CRM model matching, and the flood optimization plan was the output after coupling those two models. The CRM model provides good fittings of well production rates in case there is sufficient production data and the derived interwell connectivity is in good agreement with the interwell tracer results, the regional sedimentary supply direction, and waterflood analysis by reservoir engineers. The input of bottomhole pressure data from electric submersible pump (ESP) sensors can enhance the quality of CRM fittings, especially when reservoir is in the under-injection state. For the optimization study, well injection rates were adjusted with the objective function to maximize oil reserves, and the results signified a total incremental oil gain of 1 MMSTB approximately. The recommended waterflood optimization plan was implemented and is being evaluated in the field. The integrated CRM workflow could replace the 3D-conventional reservoir simulation model where it may contain high uncertainty of geological structures and characteristics. The CRM also enables the intensive waterflood and EOR assessment as well as flood performance optimization. This application would be a key to ensuring the success of the waterflood and EOR journey.
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