Multi-Lateral Well Productivity Evaluation Based on Three-Dimensional Heterogeneous Model in Nankai Trough, Japan

Xin Xin (), Ying Shan, Tianfu Xu, Si Li, Huixing Zhu and Yilong Yuan
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Xin Xin: Key Laboratory of Groundwater Resources and Environment, Ministry of Education, Jilin University, Changchun 130021, China
Ying Shan: Key Laboratory of Groundwater Resources and Environment, Ministry of Education, Jilin University, Changchun 130021, China
Tianfu Xu: Key Laboratory of Groundwater Resources and Environment, Ministry of Education, Jilin University, Changchun 130021, China
Si Li: Key Laboratory of Groundwater Resources and Environment, Ministry of Education, Jilin University, Changchun 130021, China
Huixing Zhu: Key Laboratory of Groundwater Resources and Environment, Ministry of Education, Jilin University, Changchun 130021, China
Yilong Yuan: Key Laboratory of Groundwater Resources and Environment, Ministry of Education, Jilin University, Changchun 130021, China

Energies, 2023, vol. 16, issue 5, 1-19

Abstract: Widely employed in hydrate exploitation, the single well method is utilized to broaden the scope of hydrate decomposition. Optimizing the well structure and production strategy is necessary to enhance gas recovery efficiency. Complex wells represented by the multilateral wells have great application potential in hydrate mining. This study focused on the impact of multilateral well production methods on productivity, taking the Nankai Trough in Japan as the study area. The spatial distribution of physical parameters such as porosity, permeability, and hydrate saturation in the Nankai Trough has significant heterogeneity. For model accuracy, the Sklearn machine learning and Kriging interpolation methods were used to construct a three-dimensional heterogeneous geological model to describe the structure and physical property parameters in the study area of the hydrate reservoir. The numerical simulation model was solved using the TOUGH + Hydrate program and fitted with the measured data of the trial production project to verify its reliability. Finally, we set the multilateral wells for hydrate high saturation area to predict the gas and water production of hydrate reservoir with different exploitation schemes. The main conclusions are as follows: ① The Sklearn machine learning and Kriging interpolation methods can be used to construct a three-dimensional heterogeneous geological model for limited site data, and the fitting effect of the heterogeneous numerical simulation model is better than that of the homogeneous numerical simulation model. ② The multilateral well method can effectively increase the gas production rate from the hydrate reservoir compared with the traditional single well method by approximately 8000 m 3 /day on average (approximately 51.8%). ③ In the high saturation area, the number of branches of the multilateral well were set to 2, 3, and 4, and the gas production rate was increased by approximately 51.8%, 52.5%, and 53.5%. Considering economic consumption, the number of branching wells should be set at 2–3 in the same layer.

Keywords: natural gas hydrate; numerical simulation; depressurization; spatial heterogeneity; multilateral well technology (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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