Feng Guoqing, Pan Liyan, Kong Bing, et al. Hierarchical optimization research based on fuzzy clustering analysis[J]. Petroleum Reservoir Evaluation and Development, 2018, 8(3): 30-34. DOI: 10.13809/j.cnki.cn32-1825/te.2018.03.007.
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.