Workflow for near-surface velocity automatic estimation: Source-domain full-traveltime inversion followed by waveform inversion

Lu Liu, Tong Fei, Yi Luo, Bowen Guo

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper presents a workflow for near-surface velocity automatic estimation using the early arrivals of seismic data. This workflow comprises two methods, source-domain full traveltime inversion (FTI) and early-arrival waveform inversion. Source-domain FTI is capable of automatically generating a background velocity that can kinematically match the reconstructed plane-wave sources of early arrivals with true plane-wave sources. This method does not require picking first arrivals for inversion, which is one of the most challenging aspects of ray-based first-arrival tomographic inversion. Moreover, compared with conventional Born-based methods, source-domain FTI can distinguish between slower or faster initial model errors via providing the correct sign of the model gradient. In addition, this method does not need estimation of the source wavelet, which is a requirement for receiver-domain wave-equation velocity inversion. The model derived from source-domain FTI is then used as input to early-arrival waveform inversion to obtain the short-wavelength velocity components. We have tested the workflow on synthetic and field seismic data sets. The results show source-domain FTI can generate reasonable background velocities for early-arrival waveform inversion even when subsurface velocity reversals are present and the workflow can produce a high-resolution near-surface velocity model.
Original languageEnglish (US)
Title of host publicationSEG Technical Program Expanded Abstracts 2017
PublisherSociety of Exploration Geophysicists
DOIs
StatePublished - Aug 17 2017

Fingerprint Dive into the research topics of 'Workflow for near-surface velocity automatic estimation: Source-domain full-traveltime inversion followed by waveform inversion'. Together they form a unique fingerprint.

Cite this