Wavefront picking for 3D tomography and full-waveform inversion

Author:

AlTheyab Abdullah1,Schuster G. T.1

Affiliation:

1. King Abdullah University of Science and Technology (KAUST), Thuwal, Saudi Arabia..

Abstract

We have developed an efficient approach for picking first-break wavefronts on coarsely sampled time slices of 3D shot gathers. Our objective was to compute a smooth initial velocity model for multiscale full-waveform inversion (FWI). Using interactive software, first-break wavefronts were geometrically modeled on time slices with a minimal number of picks. We picked sparse time slices, performed traveltime tomography, and then compared the predicted traveltimes with the data in-between the picked slices. The picking interval was refined with iterations until the errors in traveltime predictions fell within the limits necessary to avoid cycle skipping in early arrivals FWI. This approach was applied to a 3D ocean-bottom-station data set. Our results indicate that wavefront picking has 28% fewer data slices to pick compared with picking traveltimes in shot gathers. In addition, by using sparse time samples for picking, data storage is reduced by 88%, and therefore allows for a faster visualization and quality control of the picks. Our final traveltime tomogram is sufficient as a starting model for early arrival FWI.

Publisher

Society of Exploration Geophysicists

Subject

Geochemistry and Petrology,Geophysics

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. First-break automatic picking with deep semisupervised learning neural network;SEG Technical Program Expanded Abstracts 2018;2018-08-27

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