Dynamic Optimization of Underground Gas Storage Reservoir Rate Schedules

Abstract

Depleted or partially depleted natural gas reservoirs are attractive candidates for large scale underground gas storage. The effectiveness of underground gas storage reservoirs as a means of addressing seasonal gas demand and supply imbalances depends on optimal storage and withdrawal rate scheduling. In this paper, we develop an approach to maximize seasonal underground gas storage reservoir performance by dynamic optimization of storage and withdrawal rate schedules. Our method involves coupling a predictive gas production and storage system model to a non-invasive population-based optimizer. Optimization is performed progressively on a receding time horizon over which updated optimization requirements and constraints may be admitted. An example application is included to illustrate the approach. The results show that dynamic rate schedule optimization can significantly improve underground gas storage reservoir performance.