Leveraging Enhanced WRFM Workflows for Production Enhancement and Asset Optimization: Anderson Field Case Study

Abstract

Managing mature oil and gas assets presents persistent challenges, including declining production rates, compounding well and facilities integrity risks driven by increasing mechanical failures, and escalating operational inefficiencies as surveillance data grows in volume without a commensurate increase in actionable value. These challenges are further exacerbated by fragmented data sources, inconsistent data quality, and limited integration across surface and subsurface disciplines, constraining effective and timely decision-making. In swamp assets, these issues are amplified by terrain and access constraints, necessitating bespoke approaches to surveillance, optimization, and resource utilization. Effective operationalization of Well, Reservoir, and Facilities Management (WRFM) best practice is therefore critical for sustaining production, maximizing asset value, and ensuring asset longevity in such environments. The Anderson Field, a mature swamp asset in the Niger Delta region with over 60 years of production history, reached a peak oil production of approximately 75,000 barrels of oil per day (BOPD) during early development but has since experienced a prolonged decline. To arrest this decline and systematically unlock remaining production potential, a structured and automated WRFM framework was implemented to integrate people, data, and processes, leveraging automated surveillance and candidate screening for accelerated opportunity identification and maturation. Designated technical data owners ensured the accuracy, completeness, and accessibility of critical datasets, addressing long-standing surveillance gaps. The integrated WRFM workflow was configured using Schlumberger Oil Field Manager (OFM) and the in-house RADA Asset Management Solution (RADA AMS). Production enhancement opportunities including perforation extension were automated, and stimulation candidates were selected using the Heterogeneity Index (HI) and four-quadrant analysis. Additional opportunity types included bean-up optimization, cement packer installations, etc., to sustain production and restore production from shut-in wells. Recoverable reserves from the opportunities were generated through seamless OFM-RADA AMS integration to support automated Decline Curve Analysis (DCA) forecasts for each identified opportunity. Economic evaluation was automated to enable consistent ranking based on technical and economic performance indicators, accelerating field-wide screening and execution prioritization. The workflow embedded governance and audit controls through standardized processes, role-based data ownership, and versioned forecasts, ensuring end-to-end traceability across surveillance, candidate screening, reserves generation, and economics. Execution of selected opportunities delivered an incremental production gain of approximately 3,500 BOPD. This paper demonstrates how structured data management, automation, and enhanced WRFM workflows can improve surveillance efficiency, optimize resource utilization, and accelerate intervention candidate screening in mature swamp assets. The methodology is scalable and transferable across analogous Niger Delta operating environments.