Research on Productivity Prediction Model of Three-Dimensional Directional Wells in Different Reservoirs

Abstract

Productivity prediction of perforation completion is key for well optimizing completion methods and reservoir engineering research. Productivity prediction models using an additional pressure drop to represent skin factor are limited. In this study, a steady-state productivity prediction model coupled with reservoir seepage and fluid flow in the wellbore was developed. The impact of different perforation parameters on well production was studied. Considering perforation depth, perforation density, perforation diameter, phase angle, depth of contaminated zone, and pollution degree of the contaminated zone, a semi-analytical skin calculation model under different reservoir conditions and completion methods with the least-squares method combining the consideration of perforation depth, perforation density, perforation diameter, phase angle, depth of contaminated zone, and pollution degree of the contaminated zone was developed. Perforation parameters were optimized. A 3D directional well unsteady productivity prediction model was established using the finite-volume method considering the influence of conventional perforation completion parameters, gravel packing perforation completion parameters, natural fractures, reservoir heterogeneity, reservoir scale, skin factor, fluid gravity, fluid compressibility, and rock compressibility. A new method for optimizing perforation parameters and characterizing skin factors was developed, providing a theoretical basis and simulation means for deeper understanding of the development law of directional wells.