Nonstationary seismic inversion: joint estimation for acoustic impedance, attenuation factor and source wavelet

Acta Geophysica

article

Hao, Yaju¹  Wen, Xiaotao²  Zhang, Hua¹  Zhu, Yunfeng¹  Deng, Chengxiang¹ 

[1] State Key Laboratory of Nuclear Resources and Environment, School of Geophysics and Measurement-Control Technology, East China University of Technology;State Key Laboratory of Oil and Gas Reservoir Geology and Exploitation, Chengdu University of Technology

关键词: Nonstationary inversion;    Acoustic impedance;    Attenuation factor;    Source wavelet;    Alternating optimization;   

DOI  :  10.1007/s11600-021-00555-z

学科分类：地球科学(综合)

来源: Polska Akademia Nauk * Instytut Geofizyki

【 摘 要 】

Seismic signal can be expressed by nonstationary convolution model (NCM) which integrates acoustic impedance (AI), attenuation factor (AF) and source wavelet (SW) into a single formula. Although it provides attractive potential to invert AI, AF and SW, simultaneously, effective joint inversion algorithm has not been developed because of the extreme instability of this nonlinear inverse problem. In this paper, we propose an alternating optimization scheme to achieve this nonlinear joint inversion. Our algorithm repeatedly alternates among three subproblems corresponding to AI, AF and SW recovery until changes in inverted models become smaller than the user-defined tolerances. Also, when we optimize one parameter, other two parameters are fixed. NCM is an explicit linear formula for AI; therefore, AI recovery is accomplished by linear inversion which is regularized by low-frequency model and isotropy total variation domain sparse constraints. However, NCM is a complicated nonlinear formula for AF. To facilitate the AF inversion, we propose a centroid frequency-based attenuation tomography method whose forward operator and observations are acquired from the time-varying wavelet amplitude spectra which is estimated according to Gabor domain factorization of NCM. SW is decoupled from NCM based on Toeplitz structure constraint, and we obtain an orthogonal wavelet transform domain sparse regularized SW inverse subproblem. Split Bregman technique is adopted to optimize AI and SW inverse subproblems. Numerical test and field data application confirm that the proposed nonstationary seismic inversion algorithm can stably generate accurate estimates of AI, AF and SW, simultaneously.

【 授权许可】

Unknown