Full waveform inversion (FWI) can be applied to time-lapse (4D) seismic data for subsurface reservoir monitoring. However, non-repeatability (NR) can contaminate the data preventing reliable estimates of 4D changes. Using realistic reservoir models and NR measurements, we show the effects of sourcereceiver position errors and seawater changes on the 4D seismic data, and test 4D FWI against these effects. We find that ignoring these NR effects in the inversion can cause strong artifacts in velocity models, and thus should be addressed before or during inversion. By averaging forward and reverse bootstrap estimates, the central-difference 4D FWI method is more robust to these NR errors than the parallel and bootstrap 4D FWI methods.

Presentation Date: Monday, October 12, 2020

Session Start Time: 1:50 PM

Presentation Time: 1:50 PM

Location: 362D

Presentation Type: Oral

Keywords:
upstream oil & gas, position error, seg international exposition, reservoir characterization, seismic data, full-waveform inversion, artificial intelligence, data difference, exploration geophysicist 10, lumley
Subjects:
Reservoir Characterization, Formation Evaluation & Management, Seismic processing and interpretation, Four-dimensional and four-component seismic, Seismic (four dimensional) monitoring
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2020. Society of Exploration Geophysicists
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