A Consensus Equilibrium Approach for 3-D Land Seismic Shots Recovery
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.
- Research Organization:
- Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
- Sponsoring Organization:
- USDOE Laboratory Directed Research and Development (LDRD) Program; Comisión Nacional de Investigación Científica y Tecnológica (CONICYT)
- Grant/Contract Number:
- 89233218CNA000001; 20200061DR; 5222395 UIS–ECOPETROL
- OSTI ID:
- 1825420
- Report Number(s):
- LA-UR-21-22053
- Journal Information:
- IEEE Geoscience and Remote Sensing Letters, Vol. 19; ISSN 1545-598X
- Publisher:
- IEEECopyright Statement
- Country of Publication:
- United States
- Language:
- English
Similar Records
Projected Multi-Agent Consensus Equilibrium (PMACE) With Application to Ptychography
Development and Calibration of New 3-D Vector VSP Imaging Technology: Vinton Salt Dome, LA