Electrical-Elastic Joint Inversion Method for Fracture Characterization in Anisotropic Media

doi:10.1109/TGRS.2023.3312400

CORC > 力学研究所 > 中国科学院力学研究所 > 流固耦合系统力学重点实验室(2012-)

	Electrical-Elastic Joint Inversion Method for Fracture Characterization in Anisotropic Media
	Guo, Chen 6; Fan, Zhenzhen 6; Yang, Zhifang 5; Yan, Xinfei 3,4; Ling, Bowen 1,2
刊名	IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
	2023
卷号	61 页码:12
关键词	Electrical and elastic properties fractured media inversion method joint property
ISSN号	0196-2892
DOI	10.1109/TGRS.2023.3312400
通讯作者	Ling, Bowen(lingbowen@imech.ac.cn)
英文摘要	Fracture networks are omnipresent in unconventional energy reservoirs. The inversion of fractures is of vital importance to oil and gas exploration and production. Most of the existing inversion methods are developed based on homogeneous media theory and rely on a solitary physical descriptor. For instance, one commonly employed single-property inversion approach is the determination of water saturation through the use of the media's electrical conductivity. With the fast development of multiphysics geological survey, a joint inversion framework that is suitable for anisotropic fractured media is needed. In this article, we propose an electrical-elastic joint inversion method involving both electrical tensor and elastic tensor to invert the fracture characteristics (e.g., fracture shape, inclination angle, and porosity). We conduct numerical experiments with two-phase geometries containing idealized ellipsoidal fractures. The resistivity tensor and Young's moduli of different directions are calculated and used to construct an anisotropy diagram and a joint inversion chart. The method is validated by comparing the predicted fracture geometry with the actual geometry of the fracture embedded in media. Both ideal homogeneous media and digital rock samples are used to test the inversion framework. A comparison between the single- and the joint-property inversion is also presented, and the joint-property inversion shows a higher accuracy in predicting fracture volume and tilting angle. This work indicates that the proposed electrical-elastic joint method can capture the anisotropy of the formation rock, and the multiphysics inversion framework exhibits the potential to recover fracture features with high fidelity.
资助项目	National Science Foundation of China[42272158] ; National Science Foundation of China[42374154] ; National Science Foundation of China[41874140] ; PetroChina Research Institute of Petroleum Exploration and Development[41704107] ; [2022-KFKT-24]
WOS关键词	WATER SATURATION ; CONDUCTIVITY TENSOR ; NATURAL FRACTURES ; RESISTIVITY ; VELOCITY ; ROCKS ; SANDSTONE ; POROSITY ; MODEL ; SHALE
WOS研究方向	Geochemistry & Geophysics ; Engineering ; Remote Sensing ; Imaging Science & Photographic Technology
语种	英语
WOS记录号	WOS:001080998400026
资助机构	National Science Foundation of China ; PetroChina Research Institute of Petroleum Exploration and Development
内容类型	期刊论文
源URL	[http://dspace.imech.ac.cn/handle/311007/93252]
专题	力学研究所_流固耦合系统力学重点实验室(2012-)
通讯作者	Ling, Bowen
作者单位	1.Univ Chinese Acad Sci, Sch Engn Sci, Beijing 100049, Peoples R China 2.Chinese Acad Sci, Inst Mech, Beijing 100190, Peoples R China 3.PetroChina, Key Lab Geophys, Beijing 100083, Peoples R China 4.Res Inst Petr Explorat & Dev, Beijing 100083, Peoples R China 5.CNPC, PetroChina Res Inst Petr Explorat & Dev, Beijing 100083, Peoples R China 6.Changan Univ, Sch Informat Engn, Xian 710064, Peoples R China
推荐引用方式 GB/T 7714	Guo, Chen,Fan, Zhenzhen,Yang, Zhifang,et al. Electrical-Elastic Joint Inversion Method for Fracture Characterization in Anisotropic Media[J]. IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING,2023,61:12.
APA	Guo, Chen,Fan, Zhenzhen,Yang, Zhifang,Yan, Xinfei,&Ling, Bowen.(2023).Electrical-Elastic Joint Inversion Method for Fracture Characterization in Anisotropic Media.IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING,61,12.
MLA	Guo, Chen,et al."Electrical-Elastic Joint Inversion Method for Fracture Characterization in Anisotropic Media".IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING 61(2023):12.