Optimization design of multi-gathering mode for the surface system in coalbed methane field

Jun Zhou , Tiantian Fu , Kunyi Wu , Yunxiang Zhao , Lanting Feng

Petroleum ›› 2023, Vol. 9 ›› Issue (2) : 237 -247.

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Petroleum ›› 2023, Vol. 9 ›› Issue (2) :237 -247. DOI: 10.1016/j.petlm.2022.01.001
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Optimization design of multi-gathering mode for the surface system in coalbed methane field
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Abstract

As a potential resource for emerging clean energy with abundant reserves, coalbed methane (CBM) has risen rapidly in recent years, and the construction of rational and economical CBM gathering system plays a vital role in the development of the oil and gas industry. At present, there is no literature that considers the optimization of the multi-gathering mode of coalbed methane pipe network system. Due to the complexity and high investment, this paper establishes a unified mixed-integer nonlinear programming model to determine the gathering modes (including liquified natural gas, compressed natural gas, and gas gathering station) of gathering system to reduce the cost of coalbed methane collection and export. The objective function is the maximization of total profit during the period of the whole project, and such constraints, like network structure, facility number, location, node flow balance, capacity and variable value, are taken into consideration. The solution strategy and heuristic algorithm is proposed and verified by the field data from Shanxi province (China). The results show that the model can solve the problem for optimization design of the surface system in complicated CBM fields.

Keywords

Coalbed methane / Multi-gathering mode / Optimization / Pipeline network

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Jun Zhou, Tiantian Fu, Kunyi Wu, Yunxiang Zhao, Lanting Feng. Optimization design of multi-gathering mode for the surface system in coalbed methane field. Petroleum, 2023, 9(2): 237-247 DOI:10.1016/j.petlm.2022.01.001

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Acknowledgments

This work was part of the program “Study on the optimization method and architecture of oil and gas pipeline network design in discrete space and network space”, funded by the National Natural Science Foundation of China, grant number 51704253. The authors are grateful to all study participants.

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