Capitalizing on untapped potential and quantifying risk is the key to success in a turbulent commodity industry. Mature fields have seen it all. Periods of high oil price have invited increased investment and pushed boundaries, while low-oil-price periods have had a severe effect on the fields’ sustainability and development. Mature fields have existed through a time of great technological change and stand on the cusp of their ultimate fate—either to maximize recovery with the lowest possible expenditures amid tightening environmental regulations or to close the taps and prepare for painful abandonments. In a capital‑intensive industry, mistakes often are unforgiving and the costs of uncertainty and error are great.
Fluctuating technological, political, and business influences add to the volatility and risk in selecting the next big idea for mature fields. The framework and success of future opportunities is reliant on the data used to quantify them, and this is something of which all mature fields have plenty. As they have delivered value throughout their life, the uncertainty associated with them reduces, and the new ideas discussed here come to light.
Alternative use of wells for geothermal energy generation, carbon sequestration in depleted reservoirs, and the use of machine learning to maximize recovery are solutions that provide insight into how diverse the scope of mature field rejuvenation ideas can be. These solutions have something in common, however; they aim to capitalize on data, modularize problems, and structure a sustainable solution. These solutions are scalable, upgradable, and, most importantly, cost-effective for large and small operators. The upstream sector has long valued efficiency and accuracy. Small improvements in mature fields can make a significant economic difference with an established infrastructure in place. Value in large mature fields still exists, but one has to know where to look and what lenses to use.
This Month’s Technical Papers
Three-Way Coupled Modeling Evaluates CO2 Sequestration in Depleted Reservoir
Flow Simulator Optimizes Geothermal Heat Extraction From End-of-Life Wells
Automated Work Flow Identifies Opportunities for Production, Cost Improvements
Recommended Additional Reading
IPTC 21436 Permeability Prediction Using Rock Typing, Flow-Zone Indicator, and Machine-Learning Techniques in a Brownfield Offshore Malaysia by Budi Priyatna Kantaatmadja, Petronas, et al.
SPE 208204 Generating Value From Mature Gas Fields by Quantifying Well-Integrity Assurance With a Critical Analysis of Multiple Logs and Retrieved Tubular Surface Inspection by Christna Golaco, Sharjah National Oil Corporation, et al.
SPE 209988 Successful Reservoir Management and Optimization of Mature Steamflood Projects Using Artificial Intelligence by Andrei Popa, Chevron, et al.
Siddharth Jain, SPE, is field development team leader at Sharjah National Oil Corporation. He holds a bachelor’s degree in petroleum engineering, an MBA degree in oil and gas management, and an executive master’s degree in energy management. Jain has worked on field development, integrated reservoir management, production enhancement, and upstream data-hub projects. He has served as the young professional chair for the SPE Northern Emirates section since 2019 and is a technical committee member in various industry forums. Jain has been awarded the SPE 2021 MENA Regional Young Member Outstanding Service Award and was recognized as a 2021 Energy Influencer by SPE’s The Way Ahead in June 2021. Most recently, he has been awarded the Young Energy Professional of the Year 2022 at the Middle East Energy Awards in Dubai.
