Gas Production Prediction Model of Volcanic Reservoir Based on Data-Driven Method

Based on on-site construction experience, considering the time-varying characteristics of gas well quantity, production time, effective reservoir thickness, controlled reserves, reserve abundance, formation pressure, and the energy storage coefficient, a data-driven method was used to establish a natural gas production prediction model based on differential simulation theory. The calculation results showed that the average error between the actual production and predicted production was 12.49%, and the model determination coefficient was 0.99, indicating that the model can effectively predict natural gas production. Additionally, we observed that the influence of factors such as reserve abundance, the number of wells in operation, controlled reserves, the previous year’s gas production, formation pressure, the energy storage coefficient, effective matrix thickness, and annual production time on the annual gas production increases progressively as the F-values decrease. These insights are pivotal to a more profound understanding of gas production dynamics in volcanic reservoirs and are instrumental in optimizing stimulation treatments and enhancing resource recovery in such reservoirs and other unconventional hydrocarbon formations.

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Publication Details

Journal
Energies
Published
2024-10-31
DOI
https://doi.org/10.3390/en17215461
Citations
2
Primary Topic
Reservoir Engineering and Simulation Methods
Type
article
Field-Weighted Citation Impact
0.67

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article

Gas Production Prediction Model of Volcanic Reservoir Based on Data-Driven Method

Zhonghua Liu, Haijie Zhang, Junwei Pu, X. Tong et al.
2 citations
Energies
Reservoir Engineering and Simulation Methods
0.67
article

Gas Production Prediction Model of Volcanic Reservoir Based on Data-Driven Method

Zhonghua Liu, Haijie Zhang, Junwei Pu, X. Tong, Li Zhang, Yingming Xie, Jihao Yu, Xiangjie Man, Han‐Wu Deng
article en
2 citations

Abstract

Based on on-site construction experience, considering the time-varying characteristics of gas well quantity, production time, effective reservoir thickness, controlled reserves, reserve abundance, formation pressure, and the energy storage coefficient, a data-driven method was used to establish a natural gas production prediction model based on differential simulation theory. The calculation results showed that the average error between the actual production and predicted production was 12.49%, and the model determination coefficient was 0.99, indicating that the model can effectively predict natural gas production. Additionally, we observed that the influence of factors such as reserve abundance, the number of wells in operation, controlled reserves, the previous year’s gas production, formation pressure, the energy storage coefficient, effective matrix thickness, and annual production time on the annual gas production increases progressively as the F-values decrease. These insights are pivotal to a more profound understanding of gas production dynamics in volcanic reservoirs and are instrumental in optimizing stimulation treatments and enhancing resource recovery in such reservoirs and other unconventional hydrocarbon formations.

EnergiesVol. 17(21)
Chongqing University of Science and Technology (CN)
Chongqing Municipal Education Commission
Openalex Percentile: Top 30%
Reservoir Engineering and Simulation Methods
0.67
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