Domain-specific abstractions for large-scale geophysical inverse problems

During these times of sustained low oil prices, it is essential to look for new innovative ways to collect (time-lapse) seismic data at reduced costs and preferably also at reduced environmental impact. By now, there is an increasing body of corroborating evidence — whether these are simulated case studies or actual acquisitions on land and marine — that seismic acquisition based on the principles of compressive sensing delivers on this premise by removing the need to acquire replicated dense surveys. Up to ten-fold increases in acquisition efficiency have been reported by industry while there are indications that this breakthrough is only the beginning of a paradigm shift where full-azimuth time-lapse processing will become a reality. To familiarize the audience with this new technology, I will first describe the basics of compressive sensing, how it relates to missing-trace interpolation and simultaneous source acquisition, followed by how this technology is driving innovations in full-azimuth (time-lapse) acquisition, yielding high-fidelity data with a high degree of repeatability and at a fraction of the costs.