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

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 fiow 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. & COPY; 2022 Southwest Petroleum University. Publishing services by Elsevier B.V. on behalf of KeAi Communications Co. Ltd. This is an open access article under the CC BY-NC-ND license (http:// creativecommons.org/licenses/by-nc-nd/4.0/).

Automated summary

Coalbed methane (CBM) is a potential resource for clean energy and has experienced rapid growth in recent years. The construction of a rational and economical CBM gathering system is crucial for the development of the oil and gas industry. This paper establishes a unified mixed-integer nonlinear programming model to optimize the gathering modes of the CBM pipe network system, aiming to reduce the cost of coalbed methane collection and export. The proposed model considers various constraints and has been verified using field data from Shanxi province, China.