A Consensus Equilibrium Approach for 3-D Land Seismic Shots Recovery

Goyes-Penafiel, Paul; Vargas, Edwin; Correa, Claudia V.; Agudelo, William; Wohlberg, Brendt; Arguello, Henry

doi:10.1109/lgrs.2021.3082421

A Consensus Equilibrium Approach for 3-D Land Seismic Shots Recovery

Journal Article · Fri Jun 04 00:00:00 EDT 2021 · IEEE Geoscience and Remote Sensing Letters

DOI:https://doi.org/10.1109/lgrs.2021.3082421· OSTI ID:1825420

^[1]; ^[1]; ^[1]; Agudelo, William ^[2]; ^[3]; ^[1]

Industrial University of Santander, Bucaramanga (Colombia)
Colombian Petroleum Institute (ECOPETROL), Piedecuesta (Colombia)
Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

Physical and budget constraints often result in inadequate sampling for accurate subsurface imaging. Preprocessing approaches, such as missing trace interpolation, are typically employed to enhance seismic data in such cases. The compressed sensing (CS) framework has been applied for modeling missing seismic data, which is estimated by sparsity-based computational algorithms. While existing work mainly focuses on recovering missing traces resulting from receiver subsampling, source subsampling has greater economical advantages, as sources are more expensive than receivers. Moreover, stronger image models different from sparsity have not been explored for source recovery. This work presents a consensus equilibrium (CE) approach to recover missing seismic shots, which enables to incorporate various regularization operators modeling different data priors. Here, simulation results from a real 3-D land seismic dataset demonstrate that the CE approach provides more accurate estimations of the linear and hyperbolic events in the recovered shots, compared with pure sparsity-based reconstructions.

View Accepted Manuscript (DOE)

Research Organization:: Los Alamos National Laboratory (LANL), Los Alamos, NM (United States)

Sponsoring Organization:: Comisión Nacional de Investigación Científica y Tecnológica (CONICYT); USDOE Laboratory Directed Research and Development (LDRD) Program

Grant/Contract Number:: 89233218CNA000001

OSTI ID:: 1825420

Report Number(s):: LA-UR--21-22053

Journal Information:: IEEE Geoscience and Remote Sensing Letters, Journal Name: IEEE Geoscience and Remote Sensing Letters Vol. 19; ISSN 1545-598X

Publisher:: IEEECopyright Statement

Country of Publication:: United States

Language:: English

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