GA-Based Minimum Miscible Pressure Prediction

Su Kun; Xin Wei Liao; Jing Chen

doi:10.4028/www.scientific.net/AMR.361-363.530

Paper Titles

Sensitivity Analysis of Fracture Affecting Factors in Low Permeable Fractured Reservoir
p.510

Key Problems in the Calculation of Minimum Miscibility Pressure Based on Analytical Method
p.516

Advance Water-Flooding to Reduce the Stress Sensitivity Affect on Low Permeability Reservoir Development
p.520

Study on Properties of Pectinate Hydrophobically Associating Polyacrylamide Solutions
p.526

GA-Based Minimum Miscible Pressure Prediction
p.530

Study on Combustion Model of the Propellant Used in Oil Composite Perforation
p.534

Research on Modeling of Screw Pump Characteristic Mathematical Model
p.540

Research on the Correction Method for Measurement Data of WOB while Drilling Based on Strain Analysis
p.547

Research on Viscosity Reduction and the Transportation at Atmospheric Temperature for Heavy Oil with Microwave Radiation Technique
p.557

HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 361-363GA-Based Minimum Miscible Pressure Prediction

GA-Based Minimum Miscible Pressure Prediction

Abstract:

Minimum Miscible Pressure (MMP) is among key parameters to predict CO₂ flooding performance during candidate reservoirs screening process. In this paper, key factors determining MMP are screened after investigation over previous researches, and then by seven samples of oil component, a reasonable empirical function is developed to predict MMP for reservoirs in China, of which coefficients are calculated by genetic algorithm (GA) to improve accuracy for further application. After comparison, it proves better prediction by new function than the ones already existed, which can be widely used for further MMP prediction for pilot reservoir in China.