Reservoir Evaluation and Development ›› 2018, Vol. 8 ›› Issue (3): 30-34.

• Reservoir Evaluation • Previous Articles     Next Articles

Hierarchical optimization research based on fuzzy clustering analysis

Feng Guoqing,Pan Liyan,Kong Bing,Luo Jiashun   

  1. (State Key Laboratory of Reservoir Geology and Development Engineering, Southwest Petroleum University, Chengdu, Sichuan 610500, China)
  • Received:2017-09-01 Online:2018-06-26 Published:2018-12-07

Abstract:

According to the deficiency of the development status and the distribution law of the remaining oil in the reservoir-H, we used the fuzzy clustering analysis and numerical simulation technique to optimize the layers, evaluated the factors influencing the reservoir, and ultimately, got the comprehensive evaluation index, by which we could optimize the layers to reduce the contradiction between the layers and increase the water drive degree. Firstly, we determined 9 feature parameters as the evaluation indexes by the gray correlation analysis, that is, the water extraction degree, water flooding degree, abundance of remaining oil storage, porosity, variable coefficient of permeability, reservoir depth, oil content, and permeability. Based on the fuzzy clustering analysis, we classified the small layers into three groups. Each set of schemes was divided into two sets of layers. Then, we used the numerical simulation to predict and contrast the annual oil production, recovery, and moisture content of three schemes in 10 years later to get the preferred plan. The experimental results confirmed the feasiblility of the fuzzy clustering method in the optimization of the layer system.

Key words: reservoir-H, reservoir optimization, fuzzy cluster analysis, numerical simulation

CLC Number: 

  • TE39