Doctor of Philosophy (PhD)
The efficiency of the use of CO2 as a displacement fluid in oil recovery is hampered by the existence of an unfavorable mobility ratio that is caused by the large difference in viscosity between the injected fluid (CO2) and the reservoir fluids. This viscosity contrast results in early CO2 breakthrough, viscous fingering, gas channeling, and consequently, the inability of CO2 to effectively contact much of the reservoir and the oil it contains. Improvement of sweep efficiency and mobility control in CO2 injection require solutions to these problems. The use of surfactants and other chemical means for mobility control has been studied extensively and offer promising results, as they provide ways of increasing the viscosity of CO2 and/or block high permeability zones. One common problem that researchers encounter occurs when moving from core-scale experiments to field-scale implementation. Results obtained from laboratory experiments serve as inputs to reservoir simulators for modeling field-scale processes and estimating surfactant requirements. Generally, core-scale permeability is assumed to be homogeneous. While this assumption simplifies laboratory experiments and provides information of some flow properties, it does not present in-depth knowledge on the true heterogeneity of a reservoir system as a whole, and how the varying permeability affects recovery. Core-scale results also typically imply that chemical requirements for field-scale implementation are uneconomic. It is thereby crucial to develop a method to characterize scaling of results from the core-scale to the field-scale, especially as it pertains to the amount of chemical to use in this recovery method. This will provide an insight into the dynamics of water, oil, surfactant and CO2 flow within a stratified system using results obtained from laboratory experiments. This study focused on the development, evaluation and validation of scaling (dimensionless) groups for surfactant transport in porous media that affect sweep efficiency. The groups were obtained through dimensional and inspectional analysis and verified through practical laboratory coreflood experiments and numerical simulation. Design of experiments was used to generate an appropriate sample space for the dimensionless groups from which a model that is capable of predicting oil recovery and pressure difference is developed. The scaling groups derived correspond to existing scaling methods for homogeneous systems. Therefore, Dykstra-Parson’s coefficient, VDP, was introduced so as to incorporate heterogeneity for the evaluation of surfactant requirements. Borchardt et al. (1985), Yin et al. (2009), Bian et al. (2012) and Emadi et al. (2012) have conducted experimental studies to understand the mechanism of foam generation and propagation from CO2 and surfactant solution in the presence of oil. The findings reported by these researchers were based solely on laboratory investigations as they did not utilize numerical simulation to further understand the behavior of their respective systems. One researcher, Ren (2012b), used history-matching to relate surfactant transport properties measured during core experiments to a simulator-derived Mobility Reduction Factor, MRF. While very good matches were obtained, Ren (2012b) reported that each of the fitted parameters that led to a good fit of pressure and saturation data may not represent actual foam physics. For the first time, a comprehensive study that interfaced laboratory experiments and numerical simulation, while maintaining realistic interactions between phases, was conducted. This research work led to the development of a process that can be used to design a CO2-surfactant oil recovery project. This process is very flexible, and can be applied to a wide range of reservoir types as long as there is physical commonality between the laboratory and field models. The process allows for the assessment of ranges of parameters such as surfactant concentration and Dykstra-Parsons coefficients so as to aid in the selection of the optimum and economic surfactant concentration and to account for uncertainties due to heterogeneity.
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Afonja, Gbolahan I., "Development of a framework for scaling surfactant enhanced CO₂ flooding from laboratory scale to field implementation" (2013). LSU Doctoral Dissertations. 527.