Heavy oil recovery by combined solvent and hot water (CS-HW) injection: Experimental, numerical and data mining-based analysis
type: CreativeWork
description: In this study, a hybrid EOR process is developed and optimized in a two-well configuration for heavy-oil recovery which combines solvent injection using different solvents such as carbon dioxide (CO2), methane (CH4) and propane (C3H8) with a moderate reservoir heating by hot-water flooding (HWF) as a solution to enhanced heavy oil recovery (EHOR), reduce energy consumption, and improved solvent retrieval efficiency. The combined injection of solvent and hot water offers several advantages including reduction of energy consumption compared to steam-based thermal EOR methods, and reduction of solvent volume required to reduce the viscosity of heavy oil. The proposed hybrid EOR method of combined solvent and hot water (CS-HW) injection outperformed the sole injection of solvent, conventional water flooding (WF) and hot-water flooding (HWF) by sustaining the foamy oil flow and effectively delaying water and gas breakthrough times. A total of 21 laboratory tests including water flooding (WF), hot-water flooding (HWF), solvent injection, combined solvent and hot water (CS-HW) injection in a two-well configuration were designed and conducted. More specifically, the design parameters such as injection rate (qinj) and temperature (Tinj), solvent composition and slug size were optimized with the objective of maximizing heavy oil recovery. In order to study the numerical simulation of CS-HW injection and other laboratory tests presented in this research, CMG-STARS module was used. Sensitivity analysis was performed on the effective parameters of CS-HW injection process to obtain the best history-match between the experimental data and the simulation model. Furthermore, a new computational approach for predicting the performance of hot-water flooding (HWF) in unconsolidated heavy oil reservoirs was presented. The proposed model predicts the changes in the oil–water viscosity ratio (μo/μw) by estimating the reservoir temperature distribution through porous media. Then, the dimen…
abstract: In this study, a hybrid EOR process is developed and optimized in a two-well configuration for heavy-oil recovery which combines solvent injection using different solvents such as carbon dioxide (CO2), methane (CH4) and propane (C3H8) with a moderate reservoir heating by hot-water flooding (HWF) as a solution to enhanced heavy oil recovery (EHOR), reduce energy consumption, and improved solvent retrieval efficiency. The combined injection of solvent and hot water offers several advantages including reduction of energy consumption compared to steam-based thermal EOR methods, and reduction of solvent volume required to reduce the viscosity of heavy oil. The proposed hybrid EOR method of combined solvent and hot water (CS-HW) injection outperformed the sole injection of solvent, conventional water flooding (WF) and hot-water flooding (HWF) by sustaining the foamy oil flow and effectively delaying water and gas breakthrough times. A total of 21 laboratory tests including water flooding (WF), hot-water flooding (HWF), solvent injection, combined solvent and hot water (CS-HW) injection in a two-well configuration were designed and conducted. More specifically, the design parameters such as injection rate (qinj) and temperature (Tinj), solvent composition and slug size were optimized with the objective of maximizing heavy oil recovery. In order to study the numerical simulation of CS-HW injection and other laboratory tests presented in this research, CMG-STARS module was used. Sensitivity analysis was performed on the effective parameters of CS-HW injection process to obtain the best history-match between the experimental data and the simulation model. Furthermore, a new computational approach for predicting the performance of hot-water flooding (HWF) in unconsolidated heavy oil reservoirs was presented. The proposed model predicts the changes in the oil–water viscosity ratio (μo/μw) by estimating the reservoir temperature distribution through porous media. Then, the dimen…
author: Masoomi, Reza
language: en
date published: 2023-06
date modified: 2026-07-24T04:03:34Z
provider: University of Regina
publisher: Networked Digital Library of Theses and Dissertations
type: WebPage
source organization: Faculty of Graduate Studies and Research, University of Regina

PropertyValue
property ID: Handle
value: https://hdl.handle.net/10294/16174

PropertyValue
property ID: DOI
value: 10.82465/4218