Co-Optimization of Operational and Intelligent Completion Parameters of CO 2 Water-Alternating-Gas Injection Processes in Carbonate Reservoirs

Xili Deng, Jingxuan Wang, Xiangguo Zhao, Liangyu Rao, Yongbin Zhao and Xiaofei Sun ()
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Xili Deng: Department of Middle East E&P, Research Institute of Petroleum Exploration & Development, China National Petroleum Corporation, Beijing 100083, China
Jingxuan Wang: Science and Technology on Aerospace Chemical Power Laboratory, Hubei Institute of Aerospace Chemotechnology, Xiangyang 441003, China
Xiangguo Zhao: International Hong Kong Limited—Abu Dhabi, China National Petroleum Corporation, Abu Dhabi 93785, United Arab Emirates
Liangyu Rao: International Hong Kong Limited—Abu Dhabi, China National Petroleum Corporation, Abu Dhabi 93785, United Arab Emirates
Yongbin Zhao: School of Petroleum Engineering, China University of Petroleum (East China), Qingdao 266580, China
Xiaofei Sun: School of Petroleum Engineering, China University of Petroleum (East China), Qingdao 266580, China

Energies, 2025, vol. 18, issue 2, 1-22

Abstract: Recently, maximum reservoir contacting (MRC) wells have attracted more and more attention and have been gradually applied to CO 2 WAG injections. During the use of MRC wells for CO 2 WAG injections, intelligent completions are commonly considered to control CO 2 breakthroughs. However, the design of the operational and intelligent completion parameters is a complicated process and there are no studies on the co-optimization of the operational and intelligent completion parameters for CO 2 WAG processes. This study outlines an approach to enhance the oil recovery from CO 2 WAG injection processes through the co-optimization of the operational and intelligent completion parameters of MRC wells in a carbonate reservoir. First, a simulation method is developed by using Petrel and Intersect. Then, a series of simulations are performed to prove the viability of intelligent completions and to investigate the effects of the timing and duration of the CO 2 WAG injection, as well as the type, number, and placement of intelligent completion devices on the performance of a CO 2 WAG injection by MRC wells. Finally, the imperialist competitive algorithm is used to co-optimize the operational and intelligent completion parameters for MRC wells. The results show that compared with the spiral inflow control device (SICD), autonomous inflow control device (AICD), labyrinth inflow control device (LICD), and annular interval control valve (AICV), the nozzle inflow control device (NICD) is the best type of intelligent completion device for MRC wells. There is an optimal installation timing, inflow area, and number of NICDs for a CO 2 WAG injection by MRC wells. The NICDs need to be placed based on the permeability distribution. The oil recovery for the optimal case with the NICDs reached 46.43%, which is an increase of 3.8% over that of the base case with a conventional completion. In addition, compared with the non-uniformity coefficient of the base case (11.7), the non-uniformity coefficient of the optimal case with the NICDs decreased to 4.21. This is the first time that the co-optimization of the operational and intelligent completion parameters of a CO 2 WAG injection has been reported, which adds more information about the practical applications of MRC wells in CO 2 WAG injections for enhancing oil recovery in carbonate reservoirs.

Keywords: carbonate reservoirs; CO 2 water-alternating-gas injection; operational parameters; intelligent completion; optimization (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: 2025
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