A Semianalytical Model for Simulating Combined Electromagnetic Heating and Solvent-Assisted Gravity Drainage
- Lanxiao Hu (University of Alberta) | Huazhou A. Li (University of Alberta) | Tayfun Babadagli (University of Alberta) | Majid Ahmadloo (TRTech)
- Document ID
- Society of Petroleum Engineers
- SPE Journal
- Publication Date
- August 2018
- Document Type
- Journal Paper
- 1,248 - 1,270
- 2018.Society of Petroleum Engineers
- Solvent-assisted gravity drainage, Semi-analytical model, Process optimization, Heavy oil recovery, Electromagnetic heating
- 5 in the last 30 days
- 199 since 2007
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Solvent/thermal hybrid methods have been proposed recently to enhance heavy-oil recovery and to overcome the shortcomings that are encountered when either method is solely applied. One of the methods for this hybridization is to combine electromagnetic (EM) heating and solvent injection to facilitate heavy-oil production by gravity drainage. This approach has several advantages including reduced CO2 emissions, decreased water consumption, and appropriateness for water-hostile reservoirs. We are currently lacking any mathematical model for better understanding, designing, and optimizing this hybrid technique, which is partly attributed to this technique still being in its infancy.
We propose a semianalytical model to predict the oil-flow rate resulting from the combined EM heating and solvent-assisted gravity drainage. The model first calculates the temperature distribution within the EM-excited zone caused by the radiation-dominated EM heating. Using different attenuation coefficients within and beyond the vapor chamber, the model can properly describe the corresponding temperature responses in these regions. Next, an average temperature of the chamber edge contributed by EM heating is used to estimate the temperature-dependent properties, such as vapor/liquid equilibrium ratios (K-values), heavy-oil/solvent-mixture viscosity, and solvent diffusivity. Subsequently, a 1D diffusion equation is used to calculate the solvent-concentration distribution ahead of the chamber edge. Eventually, the oil-flow rate is evaluated with the calculated temperature and solvent distributions ahead of the chamber edge. The proposed model is validated against the experimental results obtained in our previous study, and the predicted oil-flow rate agrees reasonably well with the experimental data.
The proposed model can efficiently predict the oil-flow rate of this hybrid process. We conduct sensitivity analyses to examine the effect of major influential factors on the performance of this hybrid technique, including EM heating powers, solvent types, solvent-injection pressures, and initial reservoir temperatures. The modeling results demonstrate that a higher EM heating power, a heavier solvent, and a higher solvent-injection pressure could accelerate the oil-recovery rate, but tend to lower the net present value (NPV) and increase the energy consumption. In summary, the newly proposed model provides an efficient tool to understand, design, and optimize the combined technique of EM heating and solvent-assisted gravity drainage.
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