Time domain LSRTM with sparsity promotion

This applications is available only in the software release for members of SINBAD consortium.

This software provides an algorithm to perform least-squares RTM with sparsity promotion using the linearized Bregman method. By subsampling the sources in each iteration, the overall number of PDE solves lies in the range of a regular RTM image, making this method feasible for large-scale problems.

Author: Philipp Witte (pwitte@eos.ubc.ca) Date: February 2016

Contents

Downloading & Dependencies

The code can be found in the SLIM software release under /applications/Imaging/TimeDomainLSRTM

The code has been tested with Matlab R2015a and requires the Parallel Computing Toolbox.

This code uses the following packages, also found in the tools part of the SLIM software release.

If you want to use your own modules to do modelling or multiple prediction, please contact the author.

Running & Parallelism

All the examples and results are produced by the scripts found in this software release under /applications/Imaging/TimeDomainLSRTM/examples/. Start matlab from /applications/Imaging/TimeDomainLSRTM to add the appropriate paths.

To run the scripts follow the instructions in the README file enclosed inside the folder for each set of examples.

The scripts can be run in serial mode but parallel mode is advised.

Read more about SLIM's approach to parallel computing in Matlab.

Examples and results

Examples and results are shown here. Scripts to reproduce the results can be found under /applications/Imaging/TimeDomainLSRTM/examples.