Advanced monitoring and simulation for underground gas storage risk management

Advanced monitoring and simulation for underground gas storage risk management

Artificial intelligence

Decision support systems

Underground gas storage

Decision making

Monitoring

Risk management

Temperature sensors

Gas industry

Digital storage

Storage management

Flow of gases

Reservoir management

It is crucial to ensure the safety and integrity of underground gas storage (UGS) infrastructure for energy reliability in California, and many other places around the world. To address the risk management need in UGS industry, we take advantage of recent advances in downhole fiber optic monitoring and coupled well-reservoir simulation to provide unprecedented understanding of gas flow in wells at UGS sites. We have combined advanced monitoring and simulation of UGS operations into a decision-support system called the Integrated Risk Management and Decision Support System (IRMDSS). The IRMDSS framework includes three components: (i) mechanistic models, (ii) continuous and frequent monitoring data, and (iii) a supervisory interface for performing analyses using the models and monitoring data. The goal of the IRMDSS is to equip UGS operators with real-time monitoring data and simulation tools that can alert them to potential failures, detect early leakage, and support mitigation decision-making to prevent otherwise larger failures. We demonstrate an application of the IRMDSS by analyzing the temperature and pressure response to a hypothetical leak. Through a review of distributed temperature sensing (DTS) data collected at an operating UGS facility we show that DTS can uniquely and precisely identify the depth of the gas-water-contact in the well annulus, and that DTS can provide an early warning signal of upward gas flow as would occur in a well blowout scenario. When combined with modeling analysis, a rough leak rate can be roughly estimated to understand the severity of the leakage conditions and to support the mitigation decision needed. 2021 The Authors

208

Journal of Petroleum Science and Engineering

2022

Zhang, Yingqi

Oldenburg, Curtis M.

Zhou, Quanlin

Pan, Lehua

Freifeld, Barry M.

Jeanne, Pierre

Rodriguez Tribaldos, Veronica

Vasco, Donald W.

journalArticle

9204105

10.1016/j.petrol.2021.109763