支撑剂在射孔簇中的分布快速定量分析

Dmitry Kortukov, Michael Williams
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引用次数: 2

摘要

在美国非常规油藏中,使用光纤对水力压裂井进行测量已成为常规作业。仪器井有助于了解支撑剂在射孔簇中的分布,以及几何压裂和井规划技术的低效率。然而,将光纤数据转换为支撑剂分布需要对大量数据进行管理,并将数据与井况、压裂参数和温度等因素进行关联。提出了一种用户友好的工作流程,用于了解水力压裂支撑剂和浆液随时间在不同射孔簇中的分布。理想情况下,浆液在射孔簇之间的流动是相等的,至少在时间上是恒定的,但现实情况却大不相同。解释工作流程基于通用井眼软件平台中的专有算法,旨在大大加快分析速度。我们建议使用分布式声学传感(DAS)数据(以定制频带能量(FBE)日志的形式)、分布式温度测量(DTS)和地面泵送数据,在几分钟内获得支撑剂分布的定量分析,并提供各种报告和可视化结果的选项。所选择的软件平台提供数据集成、可视化和内置算法的定制。新的工作流程允许用户上传DAS、DTS、流量、压力和其他测量数据,并使用定制算法定量分析支撑剂分布,从而实时决策,优化压裂作业。该方法的有效性通过对一口井的案例研究得到了验证,该井有28段,每段有4到5个簇。该工作流程是自动化的,可以实时提供结果,实现快速纠正措施,显著提高水力压裂的效率和经济性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Fast-Loop Quantitative Analysis of Proppant Distribution Among Perforation Clusters
Using optical fibers to instrument hydraulically fractured wells is becoming routine in US unconventional plays. Instrumented wells facilitate understanding of proppant distribution among perforation clusters and the inefficiencies of geometric fracturing and well planning techniques. However, converting fiber-optic data into proppant distribution requires management of high volumes of data and correlation of the data to factors such as well conditions, fracturing parameters, and temperatures. A user-friendly workflow for understanding hydraulic fracturing proppant and slurry distribution among different perforation clusters over time is presented. Ideally, slurry flow is equal between perforation clusters and, at least, constant in time, but the reality is very different. The interpretation workflow is based on proprietary algorithms within a general wellbore software platform and aims to greatly expedite the analysis. We propose using distributed acoustic sensing (DAS) data (in the form of custom frequency band energy (FBE) logs), distributed temperature measurements (DTS) and surface pumping data to obtain a quantitative analysis of proppant distribution within minutes, with various options for reporting and visualizing results. The software platform selected provides data integration, visualization, and customization of in-built algorithms. The new workflow enables users to upload DAS, DTS, flow rate, pressure, and other measurements and use customized algorithms to quantitatively analyze proppant distribution, enabling decisions in real time to optimize the fracturing operation. The validity of the approach is illustrated by a case study involving a well with 28 stages and four to five clusters per stage. The workflow is automated to provide results in real time, enabling quick corrective actions and significantly improving the efficiency and economics of hydraulic fracturing.
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