Automated Workflow for Real-Time Management in a Large Carbonate Field

Abstract

Managing an oil and gas reservoir requires the integration and analysis of several data elements, including reservoir, well, and production data from multiple sources. Quick and efficient access to this data will allow engineers to concentrate their efforts on the important tasks of analysis and decision making, to improve reservoir and field performance. This paper presents an overview of the implementation of an automated workflow designed to support the management of a Saudi Arabian reservoir, by integrating real-time production data with other data elements. The workflow and techniques used require specialized engineering processes to fully understand the reservoir behavior and associated parameters to identify wells with anomalous behavior1. Among the solutions provided in this workflow is a system for real-time data retrieval, visualization, and analysis of reservoir production performance. This is achieved by linking dynamic surveillance processes with real-time data, and allowing data to be provided in real-time at the engineer's desktop. To provide a coherent explanation of the production behavior, multiple analysis processes and tools were used. These included a workover candidate selection system, decline curve analysis, and heterogeneity index analysis. The workflow also included mapping and quality control tools to flag out data outliers. In addition, alarm systems were included to alert the engineer when sudden changes in reservoir performance occur in the field. The implementation of this workflow has resulted in considerable time savings, with pertinent data being automatically updated and used in the analysis, as opposed to manual processing, leading to improved efficiency in field management practices. The workflow has been deployed as an application of the Intelligent Field concept in a carbonate field in Saudi Aramco.