AUTHOR=Yin Xiaohong , Yuan Yongjie , Liu Yuanyuan , Mei Qingyan , Guo Fufeng , Wei Xing , Li Xi TITLE=A new method for evaluating the utilization effect of carbonate gas reservoir reserves JOURNAL=Frontiers in Energy Research VOLUME=11 YEAR=2023 URL=https://www.frontiersin.org/journals/energy-research/articles/10.3389/fenrg.2023.1228773 DOI=10.3389/fenrg.2023.1228773 ISSN=2296-598X ABSTRACT=

After nearly 60 years of development, the carbonate gas reservoirs in Sichuan Basin have entered the middle and late stages of development. Affected by various geological factors such as complex structure, formation water distribution and water invasion intensity, low permeability, fracture development degree, fracture-cavity combination, etc., and the difference of development technical policies, the utilization effect of reserves varies greatly among different gas reservoirs. Moreover, the current indicators for evaluating the utilization effect of reserves are mainly reserve utilization degree, dynamic-static reserve ratio, recovery degree, etc., yet a unified evaluation method has not been formed. In order to effectively evaluate the utilization effect of reserves and improve the development benefit of gas reservoirs, the evaluation of utilization effect of reserves was carried out by comprehensively considering geological characteristics and development technical policies. On this basis, a new method for evaluating the utilization effect of carbonate gas reservoir reserves was formed and applied in specific gas reservoirs. The research results show that: 1) The quality of reserve utilization can accurately evaluate the utilization effect of gas reservoir reserves; 2) By introducing big data analysis technology, comprehensively using ward clustering analysis method and Pearson coefficient to correlate the main influencing factors of reserve utilization effect, a prediction model of reserve utilization effect was established; 3) The WBT Carboniferous gas reservoir was chosen to verify the aforementioned model, and the result shows that the model has high prediction accuracy and strong adaptability, which can accurately evaluate the utilization effect of developed gas reservoir reserves. The model is also applicable to evaluating the utilization effect of undeveloped gas reservoirs. In conclusion, by adopting big data analysis, the established prediction model of reserve utilization effect is suitable for quantitative evaluation and analysis of reserve utilization effect of carbonate gas reservoirs, which can provide a basis for guiding the formulation of reasonable development technical policies and improving the reserve utilization effect for similar types of gas reservoirs.