| Title | Elastic-Waveform Inversion with Compressive Sensing for Sparse Seismic Data |
|---|---|
| Authors | Youzuo LIN and Lianjie HUANG |
| Year | 2015 |
| Conference | Stanford Geothermal Workshop |
| Keywords | enhanced geothermal system, elastic-waveform inversion, compressive sensing, sparse source array, vertical seismic profiling surveys |
| Abstract | Accurate velocity models of compressional- and shear-waves are essential for geothermal reservoir characterization and microseismic imaging. Elastic-waveform inversion of multi-component seismic data can provide high-resolution inversion results of subsurface geophysical properties. However, the method requires seismic data acquired using dense source and receiver arrays. In practice, seismic sources and/or geophones are often sparsely distributed on the surface or in a borehole, such as 3D vertical seismic profiling (VSP) surveys. We develop a novel elastic-waveform inversion method with compressive sensing for inversion of sparse seismic data. We employ an alternating-minimization algorithm to solve the optimization problem of our new waveform inversion method. We validate our new method using synthetic VSP data for a geophysical model built using the geologic features found at the Raft River enhanced-geothermal-system (EGS) site. We apply our method to VSP data with a sparse source array and compare the results with those obtained with a dense source array. Our numerical results demonstrate that the velocity models produced with a sparse source array are almost as accurate as those obtained using a dense source array. |