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Design of optimal operational parameters for steam-alternating-solvent processes in heterogeneous reservoirs – A multi-objective optimization approach

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Abstract

Steam injection is a widely-used process for heavy oil and bitumen recovery. However, a significant drawback is the excessive energy requirement, water consumption, and CO2 generation. The Steam Alternating Solvent (SAS) process has been proposed as an eco-friendlier alternative to the existing steam-based methods. It involves injecting steam and solvent (i.e. propane) in separate cycles. The interplay between reservoir heterogeneity and the complex physical mechanisms of heat and mass transfer has made optimizing its design parameters quite challenging. This work aims to develop a hybrid Multi-Objective Optimization (MOO) scheme for determining the optimal operational parameters using the Pareto dominance concept while considering several conflicting objectives (i.e. RF, steam, and solvent injection) under several heterogeneous scenarios. A 2-D base homogenous reservoir model is built according to the Fort McMurray formation in the Athabasca region in Alberta, Canada. Next, shale barriers with varying proportions, lengths, and locations are superimposed onto the base model. Then, a sensitivity analysis is performed to assess the controllable operational parameters’ impact and formulate several objective functions; proxy models are introduced to speed up the objective function evaluations. Finally, different Multi-Objective Evolutionary Algorithms (MOEAs) are applied to establish the optimal ranges to operate the selected decision variables. Different optimal operating strategies are needed depending on the shale barrier distribution. Injector bottom-hole pressure, steam trap, and producer gas rate significantly impact the model response. Injecting high propane concentration over short durations is recommended. The length of the steam injection phase seems to be more sensitive to the reservoir heterogeneities; extended steam injection is needed for the more heterogeneous models. This paper is the first work comparing different MOEAs to optimize the SAS process using multiple heterogeneous models.

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Acknowledgments

This research was supported by funding from the Canada First Research Excellence Fund as part of the University of Alberta’s Future Energy Systems research initiative with the project number T07-C01. The authors would like to thank Computer Modelling Group (CMG) and MathWorks for providing the academic licences for STARS/CMOST and MATLAB, respectively.

Conflicts of interest/competing interests

The authors have no conflicts of interest to declare relevant to this article’s content.

Availability of data and material (data transparency)

The datasets generated and/or analysed during the current study are available from the corresponding author on reasonable request.

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Authors and Affiliations

  1. Computational Earth Science, University of Alberta, Edmonton, Canada

    Israel Mayo-Molina & Juliana Y. Leung

  2. Los Alamos National Laboratory, New Mexico, USA

    Zhiwei Ma

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  1. Israel Mayo-Molina
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Correspondence to Juliana Y. Leung.

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Mayo-Molina, I., Ma, Z. & Leung, J.Y. Design of optimal operational parameters for steam-alternating-solvent processes in heterogeneous reservoirs – A multi-objective optimization approach. Comput Geosci 26, 1503–1535 (2022). https://doi.org/10.1007/s10596-022-10170-6

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