Production and Cost Optimization in a Complex Onshore Operation Using Integrated Production Model

Abstract

During this low oil price era, E&P operators are challenged to reduce operating costs by evaluating their production system. Integrated production model (IPM), which combined subsurface model and surface production system, is a tool that can be utilized to evaluate the existing production system and to arrange the upcoming production strategy. This paper focuses on Kaji-Semoga oil field which consists of three field processing stations, three compressor stations, 130 ESP and 63 gas lift (GL) wells. The system evaluation started with evaluating the total GL injection required for all GL wells to observe the opportunity to increase the oil production or reduce the active compressor. This required gas lift performance curve for each wells with sensitivity to the various well head pressure. The ESP, as equipped with variable speed drive, can be optimized in accordance to the pump capacity and facility constraints. The artificial lift reliability was also evaluated to reduce the oil deferment and to foresee the next production strategy. The IPM for Kaji-Semoga was built to integrate those issues. Based on the IPM, the total GL injection rate can be reduced by up to 17% while maintaining the total oil production. With the aim of cost optimization by saving the gas fuel and reducing compressor cost, then the gas lift compressors had been shut down and relocated to another asset. As the result, 24% of total annual compressors cost was saved. From the artificial lift reliability evaluation shows that GL system reliability was reduced along with the gas shortage, whereby contributed 71% of total oil deferment. The artificial lift conversion from GL to ESP then selected as a solution. The strategy for shutdown the next gas lift compressors was then generated in accordance with the artificial lift conversion schedule and the gas lift network distribution. To overcome the limitation of liquid handling capacity at the field stations due to the conversion project, the IPM could optimize the GL and ESP simultaneously thus total fluid production can be maintained at a minimum level by continuing to retain the oil production. The paper describes some of lesson learned in constructing and utilizing the IPM as an effective tool, not only to optimize the existing production system, but also to generate the future production strategy, cost reduction opportunity and operation maneuver.

Machine Learning Approach for Predictive Maintenance of the Electrical Submersible Pumps (ESPs)

“…Previous research in this area promised to further revolutionize key aspects of oil production applications including well monitoring and control, reservoir management, − production optimization, , artificial lift, − flow assurance, , and predictive maintenance. In general, this research area focuses on the utilization of machine learning in order to understand the status of equipment so as to facilitate predictive maintenance and to avoid operation downtime.…”