A new elastic least-squares reverse time-migration method based on the new gradient equations

• Autorzy: Zhong, Yu , Liu, Yangting , Gu, Hanming , Mao, Qinghui
• Języki publikacji: EN

Abstrakty

EN

Compared with single-component seismic data, multicomponent seismic data contain more P- and S-wave information. Making full use of multicomponent seismic data can improve the accuracy of seismic exploration. Elastic reverse-time migration (ERTM) is the most advanced migration technology for imaging multicomponent seismic data from complex subsurface structures. However, most conventional ERTM methods often use the adjoint operator of forward operator for approximation to the inverse operator. When the multicomponent seismic data suffer from a finite recording aperture, limited bandwidth, and imperfect illumination, the image quality of conventional ERTM is greatly reduced. In this study, we propose an elastic least-squares reverse-time migration (ELSRTM) scheme to improve the image quality of ERTM through multiple iterations. We first review the ERTM method; then, we derive the Born modeling equations, adjoint wave equations, and gradient equations of P- and S-wave images of ELSRTM. The new gradient equations, which use the time derivative of stress to replace the spatial derivative of particle velocity for improving the accuracy of gradients near the boundary, are also proposed. We compare the performance of ERTM with ELSRTM via synthetic experiments in numerical examples. Synthetic examples reveal that ELSRTM can generate high-quality images with higher resolution, fewer artifacts, and more balanced amplitude than ERTM.

Słowa kluczowe

PL

migracja; metoda najmniejszych kwadratów

EN

migration; least squares; new gradient equations; elastic; reverse time

• Czasopismo: Acta Geophysica
• Rocznik: 2022
• Tom: Vol. 70, no 6
• Strony: 2733--2746
• Opis fizyczny: Bibliogr. 53 poz.

Twórcy

autor

Zhong, Yu

• Hubei Subsurface Multi-Scale Imaging Key Laboratory, Institute of Geophysics and Geomatics, China University of Geosciences, Wuhan 430074, China,

autor

Liu, Yangting

• First Institute of Oceanography, Ministry of Natural Resources, Qingdao 266061, China,

autor

Gu, Hanming

• Hubei Subsurface Multi-Scale Imaging Key Laboratory, Institute of Geophysics and Geomatics, China University of Geosciences, Wuhan 430074, China,
• Qingdao National Laboratory for Marine Science and Technology, Qingdao 266237, China

autor

Mao, Qinghui

• Key Laboratory of Exploration Technologies for Oil and Gas Resources (Yangtze University), Cooperative Innovation Center of Unconventional Oil and Gas (Ministry of Education & Hubei Province), Yangtze University, Wuhan 430100, China,

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Uwagi

PL

Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023).

Identyfikatory

DOI

10.1007/s11600-022-00872-x