Numerical Approach for Enhanced Oil Recovery with Surfactant Flooding using STARS (CMG)

doi:10.20431/2454-7980.0304001

Cited by 1 publication

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References 15 publications

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“…A Cartesian grid system with specified divisions along X-axis, and the developed model was simulated to match flooding history data using CMOST analysis tool. Prior to running the STARS simulation for aqueous flooding model and subsequent history-matching of experimental recovery data, the following assumptions were made to obtain accurate findings [31,32]:…”

Section: Simulation Methodologymentioning

confidence: 99%

Numerical Simulation of Enhanced Oil Recovery (EOR) studies for aqueous Gemini Surfactant-Polymer-Nanoparticle systems

Pal

Mandal²

2020

Preprint

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The article investigates the efficacy of gemini surfactant/polymer/nanoparticle flooding on chemical EOR. Initially, physicochemical behavior of aqueous chemical fluids were investigated via interfacial tension reduction, wettability alteration, adsorption, viscosity moderation and oil displacement experiments. During compositional analysis, Cartesian model with specified grid properties, injection flow-rate, well pattern, and rock-fluid characteristics was developed using CMG-STARS tool. Contour map analyses showed that oil saturation decreased from˜80% (initial) to 31.96%, 30.68% and 29.30% after {14-6-14 GS + chase water}, {14-6-14 GS + PHPA + chase water} and {14-6-14 GS + PHPA + SiO2 chase water} flooding respectively. Tertiary recoveries of 15-19% were achieved, depending on injected fluid composition. Experimental data were history matched via CMOST tool to achieve good matching of simulated results. The CMG flooding simulator provides a holistic approach to investigate oil displacement profiles, assess flooding recovery capabilities with near-accuracy and predict the feasibility of proposed chemical EOR projects.

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Section: Simulation Methodologymentioning

confidence: 99%