Acoustic- and elastic-waveform inversion with total generalized p-variation regularization

TL;DR

This paper introduces a novel full-waveform inversion method using total generalized p-variation regularization, effectively reconstructing sharp interfaces and smooth variations in geophysical models while reducing artifacts from noise and sparse data.

Contribution

It develops a new inversion algorithm that simultaneously captures sharp and smooth features in geophysical models using a total generalized p-variation scheme, improving robustness against noise and data sparsity.

Findings

Accurately reconstructs sharp interfaces and smooth variations.

Reduces artifacts caused by noise and sparse data.

Demonstrates effectiveness on synthetic and field seismic data.

Abstract

Geophysical models usually contain both sharp interfaces and smooth variations, and it is difficult to accurately account for both of these two types of medium parameter variations using conventional full-waveform inversion methods. In addition, sparse geometry, noisy data and source encoding usually lead to strong inversion artifacts. We develop a novel full-waveform inversion method for acoustic and elastic waves using a total generalized p-variation regularization scheme to address these challenging problems. We decompose the full-waveform inversion into two subproblems and solve these two minimization subproblems using an alternating-direction minimization strategy. One important advantage of the total generalized p-variation regularization scheme is that it can simultaneously reconstruct sharp interfaces and smooth background variations of geophysical parameters. Such capability can also effectively suppress the noises in source-encoded inversion and sparse-data inversion, or inversion of noisy data. We demonstrate the advantages of our new full-waveform inversion algorithm using a checkerboard model, a modified elastic SEG/EAGE overthrust model, and a land field seismic dataset. Our results of synthetic and field seismic data demonstrate that our new method reconstructs both smooth background variations and sharp interfaces of subsurface geophysical properties accurately, reduces the inversion artifacts caused by source encoding, noisy data or insufficient data coverage effectively, and provides a useful tool for accurate and reliable inversion of field seismic data.