Abstract
This paper describes solutions developed using a dynamic surveillance tool to automate several workflow processes of the reservoir management, production engineering, and R&D Center at Saudi Aramco. The objective is to provide improved efficiency in field management practices, while enhancing collaboration between reservoir and production engineers; ultimately resulting in improved decision-making process.
The solutions provided include a combination of smart tools and automated workflows designed to improve reservoir management and surveillance processes. A candidate recognition system was developed to identify and flag problem wells that require immediate remediation. As new production and injection data become available, the system that is linked to the corporate database can automatically display these data for fast and rigorous validation. In addition, a formation damage indicator function is also calculated using field data and mapped to spot production problem areas and identify damaged wells. A daily surveillance tool, which compares the performance of individual wells to the average performance of a group of wells, is also provided to allow the reservoir and production engineers to easily identify underperforming wells, promptly intervene, and recommend best completion practices. Benefits include efficient well management and cost avoidance resulting from early intervention and remediation, while avoiding full-scale problem resolution.
Another dynamic surveillance tool was designed and views were developed to provide online access to the hydrocarbon phase behavior and petrophysical data for the R&D scientists and reservoir engineers. The tool allows integration of the hydrocarbon phase-behavior data and comparison of petrophysical data with historical production/injection data and production well logs, resulting in enhanced analysis, production optimization and data validation. Additional benefits of the smart tools and automated workflow processes include considerable timesavings, with pertinent data being automatically updated, validated and used in the analysis, leading to improved efficiency in field management practices.
