A Novel Performance Evaluation Method for Gas Reservoir-Type Underground Natural Gas Storage

Qiqi Wanyan, Hongcheng Xu (), Lina Song, Weiyao Zhu (), Gen Pei, Jiayi Fan, Kai Zhao, Junlan Liu and Yubao Gao
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Qiqi Wanyan: PetroChina Research Institute of Petroleum Exploration & Development, China National Petroleum Corporation, Beijing 100083, China
Hongcheng Xu: PetroChina Research Institute of Petroleum Exploration & Development, China National Petroleum Corporation, Beijing 100083, China
Lina Song: PetroChina Research Institute of Petroleum Exploration & Development, China National Petroleum Corporation, Beijing 100083, China
Weiyao Zhu: School of Civil and Resources Engineering, University of Science and Technology Beijing, Beijing 100083, China
Gen Pei: PetroChina Research Institute of Petroleum Exploration & Development, China National Petroleum Corporation, Beijing 100083, China
Jiayi Fan: PetroChina Research Institute of Petroleum Exploration & Development, China National Petroleum Corporation, Beijing 100083, China
Kai Zhao: PetroChina Research Institute of Petroleum Exploration & Development, China National Petroleum Corporation, Beijing 100083, China
Junlan Liu: PetroChina Research Institute of Petroleum Exploration & Development, China National Petroleum Corporation, Beijing 100083, China
Yubao Gao: School of Civil and Resources Engineering, University of Science and Technology Beijing, Beijing 100083, China

Energies, 2023, vol. 16, issue 6, 1-21

Abstract: The regulation of the seasonal energy supply for natural gas and the storage of fossil energy are important to society. To achieve it, storing a large amount of natural gas in porous underground media is one of the government’s choices. Due to the successful lesson learned from the oil and gas industry, natural gas storage in underground porous media has been regarded as the most potential long−term energy storage method. In this paper, we developed a new workflow to evaluate the performance of gas reservoir−type underground natural gas storage (UGS). The theoretical background of this workflow includes the correction of the average formation pressure (AFP) and gas deviation factor by error theory and the analytical mathematical model of UGS wells. The Laplace transform, line source function, and Stehfest numerical inversion methods were used to obtain pressure solutions for typical vertical and horizontal wells in UGS. The pressure superposition principle and weighting method of the gas injection−withdrawal rate were used to obtain the AFP. Through the correction of the AFP and gas deviation factor in the material balance equation, the parameters for inventory, effective inventory (the movable gas volume at standard condition), working gas volume (the movable gas volume is operated from the upper limit pressure to the lower limit pressure), and effective gas storage volume (the available gas storage volume at reservoir condition) were determined. Numerical data from the numerical simulator was used to verify the proposed model pressure solution. Actual data from China’s largest Hutubi UGS was used to illustrate the reliability of the proposed workflow in UGS performance evaluation. The results show that large−scale gas injection and withdrawal rates lead to composite heterogeneity in gas storage wells. The nine injection and production cycles’ pressure and effective inventory changes from Hutubi UGS can be divided into a period of rapid pressure rise and a period of slow pressure increase. The final AFP is 32.8 MPa. The final inventory of the Hutubi UGS is 100.1 × 10 8 m 3 , with a capacity filling rate (the ratio of effective inventory to designed gas storage capacity) of 93.6%. The effective inventory is 95.3 × 10 8 m 3 , and the inventory utilization ratio (the ratio of effective inventory to inventory) is 95.2%. The working gas volume is 40.3 × 10 8 m 3 . This study provides a new method for inventory evaluation of the gas reservoir−type UGS.

Keywords: underground natural gas storage; evaluation method; Hutubi UGS; pressure monitoring (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2023
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