Optimization of triple-alternating-gas (TAG) injection technique for enhanced oil recovery in tight oil reservoirs.

Autor: Edouard, Mvomo Ndzinga, Dong, Pingchuan, Okere, Chinedu J., Nkok, Luc Y., Adoum, Abakar Y., muchiri, Nguu D., Xiaodong, Gao, Jacques, Fame N., Prosper, Samba K.
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Zdroj: Journal of Petroleum Exploration & Production Technology; Jan2022, Vol. 12 Issue 1, p215-225, 11p
Abstrakt: After single-gas (SG) injection operations in tight oil reservoirs, a significant amount of oil is still unrecovered. To increase productivity, several sequencing gas injection techniques have been utilized. Given the scarcity of research on multiple-gas alternating injection schemes, this study propose an optimized triple-alternating-gas (TAG) injection for improved oil recovery. The performance of the TAG process was demonstrated through numerical simulations and comparative analysis. First, a reservoir compositional model is developed to establish the properties and composition of the tight oil reservoir; then, a suitable combination for the SG, double alternating gas (DAG), and TAG was selected via a comparative simulation process. Second, the TAG process was optimized and the best case parameters were derived. Finally, based on the oil recovery factors and sweep efficiencies, a comparative simulation for SG, DAG, and TAG was performed and the mechanisms explained. The following findings were made: (1) The DAG and TAG provided a higher recovery factor than the SG injection and based on recovery factor and economic advantages, CO2 + CH4 + H2S was the best choice for the TAG process. (2) The results of the sensitivity analysis showed that the critical optimization factors for a TAG injection scheme are the injection and the production pressures. (3) After optimization, the recovery factor and sweep efficiency of the TAG injection scheme were the best. This study promotes the understanding of multiple-gas injection enhanced oil recovery (EOR) and serves as a guide to field design of gas EOR techniques. [ABSTRACT FROM AUTHOR]
Databáze: Complementary Index
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