Weighted envelope correlation-based waveform inversion using automatic differentiation
Author(s)
Song, Chao
Wang, Yanghua
Richardson, Alan
Liu, Cai
Type
Journal Article
Abstract
Full-waveform inversion (FWI) is a popularly used high-resolution seismic inversion method. It relies on the measure of the misfit between observed data and predicted data. Due to the sinusoidal nature of seismic waves, a direct comparison of observed data and predicted data using the l2 norm may cause cycle skipping. A variety of objective functions for FWI have been proposed to resolve this issue over the years. Based on the gradient optimization method, an explicit expression of the model gradient of the defined objective function is needed to be derived and calculated. This complicated step can be circumvented by using an automatic gradient calculation technique, called automatic differentiation (AD). AD allows calculation of the gradients of the model parameters, as well as those of the inputs using the chain rule. Taking advantage of the deep-learning framework, FWI with different objective functions can be automatically optimized using AD. To improve the accuracy and applicability of FWI on real data, we propose a new objective function that we refer to as the weighted envelope-correlation inversion (WECI), which combines two correlation-based waveform inversions. The weights imposed on these two terms in this new objective function can be dynamically adjusted by the sigmoid function during the optimization process. We show the versatility and effectiveness of AD-based waveform inversions using different objective functions through numerical tests. We also demonstrate the superiority of the proposed WECI method on synthetic data and real data.
Date Issued
2023-07-31
Date Acceptance
2023-07-27
Citation
IEEE Transactions on Geoscience and Remote Sensing, 2023, 61
ISSN
0196-2892
Publisher
Institute of Electrical and Electronics Engineers
Journal / Book Title
IEEE Transactions on Geoscience and Remote Sensing
Volume
61
Copyright Statement
Copyright © 2023 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Sponsor
BGP Inc
Identifier
https://ieeexplore.ieee.org/document/10197513
Grant Number
EACPR_P76158
Subjects
Science & Technology
Physical Sciences
Technology
Geochemistry & Geophysics
Engineering, Electrical & Electronic
Remote Sensing
Imaging Science & Photographic Technology
Engineering
Automatic differentiation (AD)
cycle-skipping
envelop inversion
full-waveform inversion (FWI)
global correlation norm (GCN)
MIGRATION VELOCITY ANALYSIS
PHASE
0404 Geophysics
0906 Electrical and Electronic Engineering
0909 Geomatic Engineering
Geological & Geomatics Engineering
Publication Status
Published
Article Number
4505011
Date Publish Online
2023-07-31