An improved methodology for estimation of two-phase relative permeability functions for heavy oil displacement involving compositional effects and instability
In heavy oil recovery by immiscible gas injection, adverse mobility ratio and gravity segregation along with influential mass transfer are the most crucial factors controlling displacement efficiencies. Obtaining relative permeability functions using conventional techniques that are based on a stable displacement front could be highly misleading. In this work, an improved methodology was proposed for estimating relative permeability curves under simultaneous effects of frontal instability and mass transfer using history-matching techniques. The compositional analysis of produced oil from a coreflood experiment was employed, which represents dynamic interactions more realistically. For the history matching, an optimum, high-resolution, two-dimensional core model was used, as opposed to the industry standard use of a one-dimensional model. The results of the simulation were then verified by a semi-empirical approach using the Koval model, which was then used to predict a similar experiment but in a vertical orientation. A good match was obtained between the forward simulation and the experiment. To highlight the effect of mass transfer on the shape of relative permeabilities, the simulation results from two immiscible gas injection corefloods were compared: CO2 injection with mass transfer and N2 injection without mass transfer. The results showed that the two estimated functions were quite similar, indicating that instability levels would determine the displacement pattern rather than local mass transfer. This integrated approach, therefore, highlights the importance of employing the right fluid model and an appropriate 2D-grid model in estimating relative permeabilities in displacement with instability and mass transfer against the current industry practice.
KeywordsHistory matching Relative permeability Heavy oil CO2 injection Unstable displacement Compositional simulation
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This work was carried out as a part of the Non-thermal Enhanced Heavy Oil Recovery joint industry project (JIP) in the Centre for Enhanced Oil Recovery and CO2 Solutions of the Institute of Petroleum Engineering at Heriot-Watt University.
The project was equally funded by Total E&P, ConocoPhillips, CONACyT-SENERHidrocarburos - Mexico, Pemex, Wintershall, and Eni, which is gratefully acknowledged. Usman Taura thanks the Petroleum Technology Development fund, Nigeria, for the financial assistance for this work.
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