SBIR Phase I: Parallel Processing of Time-Lapse Seismic Data via the Internet

Fourth Wave Imaging Corporation, Aliso Viejo CA

Investigators

Abstract

This Small Business Innovation Research (SBIR) Phase I project from Fourth Wave Imaging Corporation concerns the processing and analysis of time-lapse seismic data on parallel computers, using the internet to control the processing flow and visualize the results. In recent years, there has been exponential growth in time-lapse seismic project activity. Time-lapse seismic analysis facilitates the management of oil and gas reservoirs by imaging fluid movement in the reservoir over time. The results are used to guide reservoir management decisions--such as where to place a new well or where to inject water, gas, or steam to stimulate hydrocarbon movement--and help maximize the life of both new and existing fields while minimizing recovery costs. The computer algorithms needed to process time-lapse seismic data are complex and require advanced computational hardware--typically multiprocessor Unix workstations or clusters of personal computers--that can execute instructions in parallel. There is little standardization in parallel hardware. Customers typically have no parallel machines at all or machines whose architecture is fundamentally different from that of the software vendor--hindering the marketing and deployment of this software. The proposed innovation will allow customers to process their data on a centralized PC cluster, using the internet to control the processing and visualize the results. It will also improve the links between the components of the time-lapse seismic workflow, leading to greater understanding and more widespread commercial acceptance of the technology. Potential applications of the proposed research include petroleum industry mapping of bypassed oil, monitoring of costly injected fluids, and imaging flow compartmentalization and the hydraulic properties of faults and fractures. Non-petroleum applicatons include monitoring groundwater reserves, subsurface monitoring of contaminant plumes and environmental clean-up projects. The internet-based parallel software system developed for this project could be applied to other compute-intensive fields suchas medical and satellite imaging, weather forecasting, and finance.