A Cross-Disciplinary Environment for Computationally and Data Intensive Applications in the Geosciences

The exploration and production of oil and natural gas is one of the most computationally demanding endeavors, generating terabytes of data. To optimize the management of a producing oil field or to find new reserves, the E and P data must be readily available to a multidisciplinary asset management team. The data must be easy to access, and it must be effectively managed by a team of geologists, geophysicists, and engineers. However, the analysis, processing, and interpretation of these datasets is a labor-intensive and extremely time consuming task. This project will develop a system to facilitate the access and interaction of a wide range of data types needed for collaboration and cross-diciplinary work in the Earth sciences. The system will include tools for: (1) specification, discovery, and access of metadata; (2) remote visualization of large datasets; (3) real-time monitoring and steering of computational and visualization processes; and (4) optimized utilization of data, machine, and human resources. In Phase I, a prototype proof-of-concept system will be implemented to demonstrate collaboration, and will include specialized capabilities for data management and remote visualization of large data volumes. In Phase II, the system will be expanded to include modules for depth imaging, reservoir simulation, automatic model updating, and optimal control of oil and gas full-field models. Commercial Applications and Other Benefits as described by the Applicant: The software system should become an important productivity tool for the oil and gas industry. In addition, the technology should have application to the monitoring of ground water reserves, contaminant plumes, and environmental hazard assesment. Commercial and societal benefits include finding new oil and gas reserves, extending the life of existing oil and gas fields, reducing dependance on foreign oil, and improving the nation's energy security.