Productivity evaluation model for multi-cluster fractured wells based on volumetric source method

Abstract

Multi-cluster fracturing in horizontal wells is a widely performed key technology for the development of low permeability and tight oil reservoirs. However, it is difficult to predict the oil productivity after fracturing efficiently and accurately. A practical productivity prediction model of fractured horizontal wells based on volume source method is proposed. The model comprehensively considers the effects of nonlinear seepage, reservoir physical properties, cluster distribution mode and non-uniform fracture length on productivity. The reliability of the proposed model is verified by field data. The conclusion shows that the cumulative production of fractured horizontal wells increases with the increase of permeability and storage capacity coefficient, and decreases with the increase of starting pressure gradient (SPG) and stress sensitivity coefficient (SSC). With the increase of the number of fractures, the influence of nonlinear seepage characteristics on cumulative production (CP) intensifies. Increasing the crack length can reduce the impact of production decline caused by stress sensitivity effect, but has little impact on the starting pressure gradient. With the increase of dimensionless conductivity, the decrease of CP caused by starting pressure gradient and stress sensitivity effect gradually increases. Under the same fracture parameter, the influence of stress sensitivity effect is stronger than that of starting pressure gradient effect on CP. In the segmented clustering mode, the multi-cluster fracturing productivity decreases gradually with the decrease of segment spacing and the increase of cluster spacing. The cumulative production of multi-cluster fracturing with non-uniform spacing and non-uniform fracture length distribution mode is less than that with equal spacing and equal fracture length mode. This model eliminates the problems of singularity of point source function, slow convergence speed or non-convergence of calculation. The nonlinear percolation characteristics of tight reservoirs are taken into account in this prediction model, which has the advantages of fast convergence and high calculation efficiency. The findings of this study can help for better understanding of productivity prediction of fractured horizontal wells, which has important guiding significance for the optimization of fracturing parameters.