1887

Abstract

Summary

The mechanistic foam population balance (PB) model has clear physics, but it is generally challenging to be applied due to the high computational cost and the difficulty for determining a number of kinetic foam parameters. In this presentation, a simplified mechanistic foam PB model was developed and applied for simulating enhanced oil recovery (EOR) process in the laboratory.

An improved foam coalescence function for oil destabilizing effect and dry-out effect on foam was incorporated into the mechanistic foam PB model, and a simplified mechanistic foam PB model was obtained after local equilibrium approximation. The simplified mechanistic foam PB model was first validated by fractional flow theory. Then, it was applied for history matching an efficient foam EOR process performed in the laboratory. These experiments involves foam flooding tests (co-injection of surfactant and nitrogen) in the absence of crude oil, foam tests in the presence of residual oil after water flooding and a series of foam quality scan tests in the presence of residual oil after foam flooding. The parameters for oil saturation dependent function were estimated after numerical simulation of foam transport in the presence of water flooded residual oil, while the parameters for foam dry-out function was estimated after history matching the steady state foam quality scan data at residual oil saturation after foam flooding. The simulation results were also compared with those obtained from the foam PB model and foam local equilibrium (LE) model of a commercial simulator in terms of history matching quality and computational costs.

It is found that the numerically calculated pressure gradient, cumulative oil recovery and effluent surfactant concentration reproduce the experimental results notably well. Both the steady-state and transient foam flows can be reproduced reasonably well by the simplified mechanistic foam PB model. Moreover, the simplified mechanistic PB model is more efficient in terms of computational cost in comparison to the full physics PB model, thereby appearing to be a potentially effective tool for modeling at field scale.

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2020-09-14
2024-04-26
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