Lithologic Reservoirs ›› 2020, Vol. 32 ›› Issue (6): 164-171.doi: 10.12108/yxyqc.20200616

• OIL AND GAS FIELD DEVELOPMENT • Previous Articles     Next Articles

Well placement optimization of coalbed methane based on hybrid particle swarm optimization algorithm

LIU Mingming1, WANG Quan2, MA Shou1, TIAN Zhongzheng1, CONG Yan1   

  1. 1. SinoFTS Petroleum Services Ltd., Beijing 100101, China;
    2. Petro-CyberWorks Information Technology Co., Ltd., Beijing 100007, China
  • Received:2019-12-13 Revised:2020-02-12 Online:2020-12-01 Published:2020-10-30

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Abstract: The well locations directly influence the gas recovery factor and the economic benefit of coalbed methane development projects. Based on the disadvantage of particle swarm optimization and the advantage of simulated anneal algorithm,a hybrid particle swarm optimization algorithm was proposed. This algorithm took the net present value as the objective function,the single well control area and well location as variables,and combined the reservoir numerical simulation method to optimize the single well control area and well location with the largest net present value(NPV),which was realized by matlab programming. The results show that the well location optimization based on hybrid particle swarm optimization algorithm overcomes the disadvantage of the conventional well pattern which is experience-dependent. It needs less amount of computation to determine the optimal well location compared with exhaust algorithm. The optimal single well control area of coalbed gas field in Qinshui Basin is 0.2 km2. For the optimal control area of a single well,the optimal NPV obtained by hybrid particle swarm optimization algorithm is 12.55% higher than that of the conventional rectangular well pattern. The optimal well location is closely related to gas content and permeability,among which the permeability distribution is particularly important,and it is an optimal combination of gas content and permeability. The research results provide a new method for the well location optimization of CBM development.

Key words: coalbed methane, well location optimization, single well control area, hybrid particle swarm optimization algorithm, numerical simulation, Qinshui Basin

CLC Number: 

  • TE32+4
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