From the seismic imaging point of view, the difficulty in locating passive seismic sources lies in their unknown start times. In other words, the source model has an additional dimension of time, which leads to an extended model space. Without proper preconditioning, the computational cost of directly inverting for the source functions can be intractable. Using the recently proposed cross-correlation time-reversal imaging condition, we formulate the imaging task as an inverse problem, and use a sparse weighting function calculated from the cross-correlation of back-propagated events to constrain the model space. We demonstrate that the proposed approach can effectively reduce the number of model parameters, leading to a rapid convergence rate using preconditioned conjugategradient iterations. The least-squares imaging of passive seismic sources can be further incorporated into full waveform inversion for Earth properties using the variable projection method. Synthetic examples verify the proposed method.
|Number of pages
|SEG Technical Program Expanded Abstracts
|Published - 2016
|SEG International Exposition and 86th Annual Meeting, SEG 2016 - Dallas, United States
Duration: Oct 16 2011 → Oct 21 2011
All Science Journal Classification (ASJC) codes
- Geotechnical Engineering and Engineering Geology