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Inversion of distributed temperature measurements to interpret the flow profile for a multistage fractured horizontal well in low-permeability gas reservoir

机译:反演分布式温度测量结果以解释低渗透气藏中多级压裂水平井的流场

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摘要

Distributed temperature sensors (DT%) are gradually being used to monitor downhole conditions for multistage fractured horizontal wells (MFHWs) during production. However, significant challenges exist with respect to translating the downhole DTS data to flow profiles of MFHWs, especially for low-permeability gas reservoirs (LPGRs).This study aims to interpret the flow profiles for an MFHW in LPGR through the inversion of downhole distributed temperature measurements. Firstly, a comprehensive inversion procedure combined with forward and inversion models is developed. The forward temperature prediction model is used to simulate the temperature distributions of an MFHW in each inversion iteration. Based on the Levenberg-Marquart (L-M) algorithm, an inversion model is proposed to decrease the differences between the simulated temperature data and the observed temperature data. Subsequently, a sensitivity study using an orthogonal design table L-18 (3(7)) is performed to determine the inversion parameters (fracture half-length and reservoir permeability). Then, an original case demonstrates the direct translation of the observed temperature to the flow profile. Finally, two more cases are presented to illustrate how to interpret the flow profiles based on the inversion results of the two aforementioned inversion parameters respectively. The satisfactory inversion results validate the accuracy and feasibility of the proposed inversion approach to predict flow profiles or diagnose fracture parameters from the DTS data of an MFHW in LPGR theoretically. (C) 2019 Elsevier Inc. All rights reserved.
机译:在生产过程中,分布式温度传感器(DT%)逐渐用于监测多级压裂水平井(MFHW)的井下状况。但是,将井下DTS数据转换为MFHW的流量剖面存在重大挑战,特别是对于低渗透气藏(LPGR)而言。本研究旨在通过反转井下分布温度来解释LPGR中MFHW的流量剖面测量。首先,开发了结合正向和反演模型的综合反演程序。正向温度预测模型用于在每次反演迭代中模拟MFHW的温度分布。基于Levenberg-Marquart(L-M)算法,提出了一种反演模型,以减小模拟温度数据与观测温度数据之间的差异。随后,使用正交设计表L-18(3(7))进行敏感性研究,以确定反演参数(裂缝半长和储层渗透率)。然后,一个原始案例证明了所观察到的温度直接转换为流动曲线。最后,给出另外两种情况来说明如何分别基于上述两个反演参数的反演结果来解释流场。令人满意的反演结果从理论上验证了所提出的反演方法预测流量剖面或从LPH中MFHW的DTS数据诊断裂缝参数的准确性和可行性。 (C)2019 Elsevier Inc.保留所有权利。

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