Abstract
In the comprehensive classification and evaluation of low permeability reservoirs with different geological genesis, the correlation between the classification results with gas permeability as the classification standard and the oil well productivity is low. In order to improve the correlation between the classification results of low permeability reservoirs with different geological genesis and the productivity of oil wells, the grey correlation degree (ri) between the evaluation parameters of low permeability reservoirs with different geological genesis and the reservoir seepage capacity (RQI) is calculated based on the grey correlation method. According to the size of ri, the main control evaluation parameters affecting RQI are obtained. Then the multivariate classification coefficient (Feci) of the main control evaluation parameters is calculated by the multivariate classification method, and the size of Feci is compared to comprehensively classify and evaluate the low permeability reservoirs with different geological genesis. Taking the three types of low permeability reservoirs with geological genesis in the S oilfield as an example, the main control evaluation parameters affecting the RQI of the three types of low permeability reservoirs with geological genesis are as follows : shale content, mainstream throat radius, crude oil viscosity, starting pressure gradient, movable fluid saturation and fracturing adaptability parameters. The Feci of the main controlling factors is calculated, and the reservoirs are classified into four categories. Feci>0.8 is class I reservoir, 0.4-0.8 is class II reservoir, 0.2-0.4 is class III reservoir, < 0.2 is class IV reservoir ; the R2 value of Feci and oil well productivity is 0.795, and the R2 value of gas permeability and oil well productivity is 0.0219.Grey correlation-multiple classification comprehensive classification results have better correlation with oil well productivity.
Keywords different geological causes ; low permeability reservoir ; comprehensive classification evaluation ; grey correlation ; multivariate classification
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