A New Approach for Multi-Fractured Horizontal Wells Productivity Prediction in Shale Oil Reservoirs

Abstract

Abstract The continental shale oil reservoirs usually have strong heterogeneity, which make the law of fracture propagation extremely complex, and the quantitative characterization of fracture network swept volume brings great challenges. In this paper, firstly, the grey correlation analysis method is used to calculate the correlation coefficient between different parameters and microseismic monitoring volume (SRV), and the key factors affecting SRV are identified. Secondly, the relationship between key geological engineering parameters and SRV is established by using the method of multiple linear regression, and the relationship is further corrected by productivity numerical simulation method, and the empirical formula for quantitative characterization of fracture network swept volume(FSV) is established. Finally, according to the field production of big data, the fitting chart of the accumulated oil production and the FSV is established, and the production of horizontal well is further predicted according to the fitting formula. The study results shown that the main factors affecting the SRV were fracturing fluid volume, fracture density, brittleness index, pump rate, horizontal stress difference, net pay thickness and proppant amount.The FSV in the study area was positively correlated with the cumulative oil production of the horizontal well. With the increase of the FSV, the accumulated oil production increased at first and then tended to be stable, and the optimal FSV was 760 ~ 850*104m3. The prediction method was verified by the typical platform in the field to be accurate and reliable. It can provide scientific basis for the productivity prediction of horizontal wells in shale oil reservoirs.