Improved elastic full‐waveform inversion of ocean bottom node data

Author:

Wu Bo123,Yao Gang123ORCID,Zheng Qingqing14,Niu Fenglin5,Wu Di126ORCID

Affiliation:

1. National Key Laboratory of Petroleum Resources and Engineering China University of Petroleum (Beijing) Beijing China

2. Key Lab of Geophysical Exploration of CNPC China University of Petroleum (Beijing) Beijing China

3. Unconventional Petroleum Research Institute China University of Petroleum (Beijing) Beijing China

4. Department of Mathematics, College of Science China University of Petroleum (Beijing) Beijing China

5. Department of Earth, Environmental and Planetary Sciences Rice University Houston Texas USA

6. College of Geophysics China University of Petroleum (Beijing) Beijing China

Abstract

AbstractElastic full‐waveform inversion enables the quantitative inversion of multiple subsurface parameters, significantly enhancing the interpretation of subsurface lithology. Simultaneously, with the ongoing advancements in ocean bottom node technology, the application of elastic full‐waveform inversion to marine ocean bottom node data is receiving increasing attention. This is attributed to the capability of ocean bottom node to acquire high‐quality four‐component data. However, elastic full‐waveform inversion of ocean bottom node data typically encounters two challenges: First, the presence of low S‐wave velocity layers in the seabed leads to weak energy of converted S‐waves, resulting in significantly poorer inversion results for S‐wave velocity compared to those for P‐wave velocity; second, the cross‐talk effect of multiple parameters further exacerbates the difficulty in inverting S‐wave velocity. To effectively recover the S‐wave velocity using ocean bottom node data, we modify the S‐wave velocity gradient in conventional elastic full‐waveform inversion to alleviate the impact of cross‐talk from multiple parameters on the inversion of S‐wave velocity. Furthermore, to invert for density parameters, we adopt a two‐stage inversion strategy. In the first stage, P‐wave and S‐wave velocities are updated simultaneously with a single‐step length. Because the initial density model is far from the true one, density is updated using an empirical relationship derived from well‐log data. In the second stage, velocities and density are updated simultaneously with multi‐step length to further refine the models obtained in the first stage. The high effectiveness of the improved elastic full‐waveform inversion is validated by numerical examples.

Funder

National Natural Science Foundation of China

Publisher

Wiley

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