A Grid-enabled problem-solving environment for advanced reservoir uncertainty analysis

摘要

Uncertainty analysis is critical for conducting reservoir performance prediction. However, it is challenging because it relies on (1) massive modeling-related, geographically distributed, terabyte, or even petabyte scale data sets (geoscience and engineering data), (2) needs to rapidly perform hundreds or thousands of flow simulations, being identical runs with different models calculating the impacts of various uncertainty factors, (3) an integrated, secure, and easy-to-use problem-solving toolkit to assist uncertainty analysis. We leverage Grid computing technologies to address these challenges. We design and implement an integrated problem-solving environment ResGrid to effectively improve reservoir uncertainty analysis. The ResGrid consists of data management, execution management, and a Grid portal. Data Grid tools, such as metadata, replica, and transfer services, are used to meet massive size and geographically distributed characteristics of data sets. Workflow, task farming, and resource allocation are used to support large-scale computation. A Grid portal integrates the data management and the computation solution into a unified easy-to-use interface, enabling reservoir engineers to specify uncertainty factors of interest and perform large-scale reservoir studies through a web browser. The ResGrid has been used in petroleum engineering. Copyright