Automated Data-Driven Initial Velocity Model Building for Refraction Tomography
S. Re and A. Zarkhidze
Event name: 81st EAGE Conference and Exhibition 2019
Session: Full Waveform Inversion III
Publication date: 03 June 2019
Info: Extended abstract, PDF ( 1.13Mb )
Price: € 20
Near-surface characterization is an important part of the land seismic data processing workflow. Conventional approaches rely on refracted waves and estimate the compressional velocity models from the tomography of the first-break traveltimes. Seismic tomography, while extremely powerful for resolving subsurface velocity variability, produces inherently nonunique solutions. The inverse problem it attempts to solve requires the input of a-priori information to find a realistic solution. We can constrain our solution early in the inversion process by incorporating this information during building the initial model. We present a data-driven approach to derive the initial velocity model for a refraction tomography workflow in an automated fashion, reducing the amount of subjectivity that influences the starting model definition. We demonstrate the technique using a synthetic, but realistic, 3D example.