Mosher, Charles C. (ConocoPhillips) | Keskula, Erik (ConocoPhillips) | Kaplan, Sam T. (ConocoPhillips) | Keys, Robert G. (ConocoPhillips) | Li, Chengbo (ConocoPhillips) | Ata, Elias Z. (ConocoPhillips) | Morley, Larry C. (ConocoPhillips) | Brewer, Joel D. (ConocoPhillips) | Janiszewski, Frank D. (ConocoPhillips) | Eick, Peter M. (ConocoPhillips) | Olson, Robert A. (ConocoPhillips) | Sood, Sanjay (ConocoPhillips)
Ideas from the field of compressive sensing are rapidly making their way into the geophysical realm. We believe that these concepts will motivate major changes in the way that our industry acquires, processes, and images seismic data. In preparation for these changes, we have undertaken an initiative to build a consistent framework for learning, investigating, and applying compressive sensing concepts to the full range of technologies used in seismic acquisition, processing, and imaging. We refer to this framework as Compressive Seismic Imaging (CSI). The components of our CSI framework include compressive sensing theory, acquisition design, processing and imaging algorithms, and the work flows that link these components into a complete system. A key element of our CSI program is the use of field trials to expose algorithms, processes, and people to the realities of deploying new technology in our industry. Before going to the field, we use extensive computer modeling to identify CSI concepts that are either ready for deployment, or require testing in the field to advance the technology. A number of 2D and 3D field trials were undertaken by ConocoPhillips in 2011 to test compressive sensing design ideas for seismic data acquisition. To date, we have acquired test datasets for validating CSI concepts for land, marine, and ocean bottom recording configurations. The key compressive sensing concepts we have tested so far include non-uniform sampling for sources and receivers, data reconstruction, simultaneous shooting, and source encoding. Initial results from these trials show that compressive sensing concepts have the potential to significantly improve acquisition efficiency. Use of the CSI framework has allowed us to quickly focus our attention on the most relevant problems for compressive sensing technology deployment, resulting in rapid progress in our understanding.