张量关键通路方法预测各向异性介质的渗透率  

Permeability estimation using tensor-based critical path analysisfor anisotropic media

作　　者：郭晨[1] 李梦 凌博闻 GUO Chen;LI Meng;LING Bowen(School of Information Engineering,Chang'an University,Xi'an 710064,China;Institute of Mechanics,Chinese Academy of Science,Beijing 100190,China;School of Engineering Science,University of Chinese Academy of Science,Beijing 100049,China)

机构地区：[1]长安大学信息工程学院,陕西西安710064 [2]中国科学院力学研究所流固耦合系统力学重点实验室,北京100190 [3]中国科学院大学工程科学学院,北京100049

出　　处：《石油物探》2024年第6期1274-1281,共8页Geophysical Prospecting For Petroleum

基　　金：国家自然科学基金委面上项目(42374154,42272158,42074170);中国石油集团科学技术研究院有限公司开放基金资助课题(No.2023-KFKT-24)共同资助。

摘　　要：在油气勘探开发过程中,渗透率是反应储层渗流能力的重要参数,对储层评价、开发和生产至关重要。关键通路(critical path analysis,CPA)方法基于渗流和电场的相似性,建立储层的渗透率和电导率的关系,是一种利用电法勘探结果预测渗透率的有效方法。然而,当非常规油气储层表现出较强的各向异性(如裂缝页岩)时,基于标量建立的CPA方法精度下降。针对各向异性介质,提出了一种基于等效电参数和渗透率张量的张量CPA方法。从三维真实数字岩心出发,提取岩心样本的孔隙网络,并通过定义连通矩阵来表征孔隙网络的连通关系和渗流信息,最终经过矩阵运算得到临界孔隙半径张量,进而预测渗透率。对比了张量CPA方法在各向同性介质和各向异性介质中的应用效果,结果表明,张量CPA方法通过引入张量形式的物理参量,可全面表征各向异性介质的结构特征,显著提高了各向异性介质渗透率预测准确度。In the exploration and development of oil and gas,permeability is an important parameter for reservoir evaluation,development,and production as it reflects fluid flow capacity in reservoirs.The critical path analysis(CPA)method combines the permeability and conductivity of the reservoir to predict permeability based on electrical exploration results.However,the accuracy of scalar-based CPA is insufficient to characterize unconventional oil and gas reservoirs with strong anisotropy(such as fractured shales).A tensor CPA method based on equivalent electrical parameters and permeability tensor is proposed for anisotropic media.The pore network of the core sample is extracted from a 3D real digital core,and the connectivity matrix is used to represent the connectivity and fluid flow in the pore network.The critical pore radius tensor is obtained by using matrix operation to predict permeability.According to the application results for isotropic and anisotropic media,the tensor CPA method can characterize the overall structure of anisotropic media by introducing physical parameters in the form of tensor and thus significantly improve permeability prediction for anisotropic media.

关 键 词：关键通路分析 非常规油气 各向异性 渗透率预测 电导率 

分 类 号：P631[天文地球—地质矿产勘探]