Field Development-2022

In this month’s Field Development feature, SPE conference authors place an emphasis not only on original research and findings but also on validation and refinement of existing techniques that may not have received thorough attention in the literature.

Field Development intro image

In this month’s Field Development feature, SPE conference authors place an emphasis not only on original research and findings but also on validation and refinement of existing techniques that may not have received thorough attention in the literature. As operators strive to achieve the greatest returns possible from technically, environmentally, and economically challenging plays, they are driven to innovate new approaches and to fine-tune existing ones.

In paper SPE 206267, the authors investigate the performance of a distributed quasi-Newton (DQN) derivative-free optimization (DFO) method, which, they write, had not yet been validated by realistic applications or compared with other DFO methods. They integrate DQN into a versatile field-development optimization platform designed for iterative work flows enabled through distributed parallel flow simulations. The method was field-tested on two realistic applications and identified the global optimum with the least number of simulations and the shortest run time on a synthetic problem with a known solution.

The authors of paper SPE 207146 create and evaluate a development plan for an oil field discovered in a remote offshore environment in the Niger Delta. Because the oil in place was uncertain, a probabilistic approach was used to estimate the stock-tank oil originally in place using low, mid, and high cases. Keeping in mind governmental regulations to maintain the reservoir pressure above bubblepoint, the authors propose a development plan that is marginally base modeled and, despite the uncertainty of oil prices in the market, able to cover any unforeseen situations.

Finally, the authors of paper SPE 208882, addressing the challenge posed by cumbersome integrated technical work flows for multiwell fracture modeling and reservoir simulation, use tools existing in the literature to quantify the effect of changing well spacing on well productivity for a given completion design using a simple, intuitive empirical equation. After describing and qualifying the use of their approach, they apply it to a case study from the Permian Basin.

This Month’s Technical Papers

Field-Development Optimization Method Benchmarked, Field Tested

Probabilistic Approach Guides Field Development Plan in Niger Delta

Approach With Simple Tools Enables Well-Spacing Optimization for Unconventionals

Recommended Additional Reading

OTC 31151 Autonomous Subsea Field Development—Value Proposition, Technology Needs, and Gaps for Future Advancement by Giorgio Arcangeletti, Saipem, et al.

SPE 206533 Field Development Optimization Using Machine-Learning Methods To Identify the Optimal Waterflooding Regime by Alexey Vasilievich Timonov, Consultant, et al.

URTeC-2021-5301 Unconventional Reservoir Development Performance Reviews—the Northern Midland Basin Case Study by Hongjie Xiong, University Lands, et al.


Adam Wilson is SPE’s special publications editor, responsible for SPE’s online publications HSE Now and Data Science and Digital Engineering in Upstream Oil and Gas. He has been editing for SPE for more than 12 years, starting his tenure there working with peer-reviewed technical journals. Before joining SPE, Wilson spent more than a decade working for daily newspapers. He holds a bachelor’s degree in journalism from the University of North Texas and can be reached at awilson@spe.org.