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ADMM-based full-waveform inversion for microseismic imaging
- Source :
- Geophysical Journal International, Geophysical Journal International, 2022, 228 (1), pp.259-274. ⟨10.1093/gji/ggab332⟩, Geophysical Journal International, Oxford University Press (OUP), 2022, 228 (1), pp.259-274. ⟨10.1093/gji/ggab332⟩
- Publication Year :
- 2021
-
Abstract
- SUMMARYFull waveform inversion (FWI) is beginning to be used to characterize weak seismic events at different scales, an example of which is microseismic event (MSE) characterization. However, FWI with unknown sources is a severely underdetermined optimization problem, and hence requires strong prior information about the sources and/or the velocity model. The frequency-domain wavefield reconstruction inversion (WRI) method has shown promising results to mitigate the non-linearity of the FWI objective function generated by cycle-skipping. WRI relies on the reconstruction of data-assimilated wavefields, which approach the true wavefields near the receivers, a helpful feature when the source is added as an additional optimization variable. We present an adaptation of a recently proposed version of WRI based on the alternating direction method of multipliers that first finds the location of the MSEs and then reconstructs the wavefields and the source signatures jointly. Finally, the subsurface model is updated to focus the MSEs at their true locations. The method does not require prior knowledge of the number of MSEs. The inversion is stabilized by sparsifying regularizations separately tailored to the source location and velocity model subproblems. The method is tested on the Marmousi model using one MSE and two clusters of MSEs with two different initial velocity models, an accurate one and a rough one, as well as with added noise. In all cases, the method accurately locates the MSEs and recovers their source signatures.
- Subjects :
- Optimization problem
Microseism
010504 meteorology & atmospheric sciences
Underdetermined system
Computer science
[SDU.STU]Sciences of the Universe [physics]/Earth Sciences
Inverse transform sampling
Strong prior
Inversion (meteorology)
010502 geochemistry & geophysics
01 natural sciences
Noise
Geophysics
Optimization and Control (math.OC)
[SDU]Sciences of the Universe [physics]
Geochemistry and Petrology
FOS: Mathematics
Focus (optics)
Algorithm
Mathematics - Optimization and Control
0105 earth and related environmental sciences
Subjects
Details
- Language :
- English
- ISSN :
- 0956540X and 1365246X
- Database :
- OpenAIRE
- Journal :
- Geophysical Journal International, Geophysical Journal International, 2022, 228 (1), pp.259-274. ⟨10.1093/gji/ggab332⟩, Geophysical Journal International, Oxford University Press (OUP), 2022, 228 (1), pp.259-274. ⟨10.1093/gji/ggab332⟩
- Accession number :
- edsair.doi.dedup.....e055a7d99a1c5a6fd090dd7edac16af4
- Full Text :
- https://doi.org/10.1093/gji/ggab332⟩