Technique and application of joint magnetotelluric and seismic modeling and constrained inversion based on clustering and multivariate geostatistics
YANG Bo1, ZHANG Xiangguo2, LIU Zhan1, XU Kaijun1
1. Department of Geophysics, China University of Petroleum(East China), Qingdao, Shandong 266580, China; 2. Research Institute of Exploration and Development, Daqing Oilfield Co Ltd, PetroChina, Daqing, Heilongjiang 163453, China
Abstract：With more and more complex and deeper geological bodies, the one-sidedness and limitation of a single geophysical method have become more and more prominent, and comprehensive utilization of multiple geophysical technologies and data has become an inevitable trend. This paper proposes cross-variogram in multivariate geostatistics to establish the petrophysical relationship between velocity and resistivity. Based on the relationship, the guided fuzzy C-means clustering algorithm in machine learning is used to conduct multi-constraint inversion and realize MT-seismic joint mo-deling. Application to real data recorded from the southern depression of the Dayangshu Basin has proved that the MT-seismic joint modeling and multi-constraint inversion can gradually reduce the ambiguity of a single geophysical method and improve the ability to identify target geological bodies. The results of MT and seismic methods are verified each other, demonstrating that the joint modeling and multi-constraint inversion technology is potential in field application.
杨博, 张祥国, 刘展, 徐凯军. 基于聚类和多元地质统计学的电—震联合建模约束反演技术及应用[J]. 石油地球物理勘探, 2021, 56(3): 670-677.
YANG Bo, ZHANG Xiangguo, LIU Zhan, XU Kaijun. Technique and application of joint magnetotelluric and seismic modeling and constrained inversion based on clustering and multivariate geostatistics. Oil Geophysical Prospecting, 2021, 56(3): 670-677.
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