6 research outputs found
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Modeling CO2 Partitioning at a Carbonate CO2-EOR Site: Permian Basin Field SACROC Unit
Bureau of Economic Geolog
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Carbon dioxide trapping mechanisms assessment using numerical and analytical methods
Carbon capture and storage (CCS) is a proven technique for reducing greenhouse gas emissions and climate change. Although monitoring shows that COâ‚‚ can be safely stored underground, COâ‚‚ leakage is still of concern. Therefore, understanding and forecasting the COâ‚‚ distribution over a geological time is necessary to assess the storage performance and related risks. To understand the COâ‚‚ distribution during or/and after a CCS process, four main trapping mechanisms have been introduced: stratigraphic (structural) trapping, residual trapping, solubility trapping, and mineral trapping. The relative contribution of each mechanism in COâ‚‚ sequestration is expected to change over time as COâ‚‚ migrates and reacts with formation rock and fluids. Although structural trapping is the most active trapping mechanism after COâ‚‚ injection, some of the structurally trapped COâ‚‚ dissolves into water with the rest becoming residual over time. Both the residual and dissolved COâ‚‚ then react with rock and trap some of the COâ‚‚, the process of which is recognized as part of mineral trapping. The relative contribution of different trapping mechanisms depends on different parameters, such as the type of geologic sink (i.e., saline aquifers, hydrocarbon reservoirs), and the properties of the reservoir fluids contained. Additionally, in the case of COâ‚‚-EOR/storage the importance of different trapping mechanisms may change depending on the COâ‚‚ injection strategy (e.g., water alternating gas, WAG; continuous gas injection, CGI; water curtain injection, WCI). In this dissertation, I investigate the COâ‚‚ trapping mechanisms in two CCS processes: COâ‚‚-EOR/storage and COâ‚‚ injection in dipping aquifers. First, I investigate the COâ‚‚ trapping mechanisms during and after a COâ‚‚-EOR process using reservoir simulation. The main purpose is to answer questions associated with the relationship between EOR operational strategies and COâ‚‚ utilization ratios, and to understand the impact of the different COâ‚‚ trapping mechanisms on this relationship. To answer these questions, I integrate three main elements of field assessment: physical field characterization, production and pressure history, and reservoir simulation. I use this method to model and compare two fields that represent two different reservoir settings: Cranfield (representative of the U.S. Gulf Coast sandstone reservoirs) and SACROC (representative of the Permian Basin carbonate reservoirs). CGI is the original operating strategy in Cranfield and WAG is the original operating strategy applied in the SACROC unit. Second, I investigate the impact of relative permeability on the trapping mechanisms in a COâ‚‚-EOR process using fractional flow analysis and reservoir simulation. I use the fractional flow theory for miscible displacement to analytically and graphically analyze the distribution of COâ‚‚ trappings. I use the Cranfield model to show the impact of relative permeability on field predictions. I discuss the relative permeability impact on four different COâ‚‚ injection schemes: continuous gas injection (CGI), water alternating gas injection (WAG), water curtain injection (WCI), and WCI+WAG. Third, I introduce a mathematical model, derived from force balance, to predict COâ‚‚ plume migration in dipping aquifers. This model calculates the down and up-dip extension of COâ‚‚ plume in the absence of trapping mechanisms. The force balance shows that there is a point in the down-dip flow where buoyancy and viscous forces are equal and the plume cannot extend further. However, in the up-dip flow, where the direction of viscous and buoyancy forces are the same, the plume migrates upward for an unlimited time. I validate the mathematical model against numerical simulation results. I introduce an effective relative permeability correlation to capture the competition between water and COâ‚‚. I adjust the permeability of the aquifer to validate the mathematical model against heterogeneous cases. The results show that the heterogeneity-induced error is small if we use the near well-bore average permeability. I also investigate the effect of local capillary trapping on the plume shape. Using numerical simulation, I apply capillary trapping and show how capillary forces prevent the buoyant COâ‚‚ from migrating up-dip.Civil, Architectural, and Environmental Engineerin
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Further model development and application of University of Texas Chemical Compositional Simulator for microbial enhanced oil recovery and reservoir souring
This research presents an improved simulator to predict the enhanced oil recovery after applying microbial enhanced oil recovery (MEOR) technique and the onset of reservoir souring in sea-water injected reservoirs. The model is developed to study the effect of temperature, salinity, and pH on the growth of bacteria which are responsible for producing in-situ bioproducts in MEOR and causing microbial reservoir souring. The effects of environmental factors (i.e., pH, salinity, and temperature) are implemented into a four-phase chemical flooding reservoir simulator (UTCHEM).
In the MEOR process, nutrients and natural bacteria are injected into a reservoir and both indigenous and injected microorganisms are able to react and then generate bioproducts based on in-situ reactions. In this study, we considered three different mechanisms proposed for MEOR: biosurfactant-dominated MEOR, biopolymer-dominated MEOR, and biomass-dominated MEOR. Results show that in-situ bioproduct generation rates can be thoroughly modeled based on environmental factors. Simulation results show 10-15% incremental oil recovery using in-situ biosurfactant compared to waterflooding, biopolymer can increase the oil recovery by 3%, and biomass can contribute to oil production by increasing the recovery by 6%. The simulation results show that nutrient concentration, salinity, and temperature are the most significant parameters influencing oil recovery, whereas pH has an insignificant effect.
Reservoir souring is a phenomenon that occurs because of in-situ biodegradation reactions and is modeled in the present study. Sulfate-reducing bacteria (SRB) can convert sulfate ions into hydrogen sulfide by oxidizing a carbon source. This phenomenon is called reservoir souring when it occurs in water-flooded reservoirs. The generated H2S content affects the properties of rocks, reduces the value of produced hydrocarbon, causes corrosion in production facilities, and has health and safety issues. Because of the severity of the problem, several attempts have been made to model and predict the onset of souring. However, there are high uncertainties because of many inestimable and uncertain parameters (e.g., biodegradation parameters, sulfate concentration, reservoir pH, salinity, and temperature). Therefore, the capability of UTCHEM for calculating the maximum growth rate in terms of temperature, salinity, and pH helped us to show the environmental effect on the process. We also investigated the effect of maximum growth rate and available sulfate on the biodegradation process that leads to reservoir souring. In summary, our results show that the microbial reservoir souring process can be modeled based on environmental factors. More importantly, the results show the high sensitivity of the process to different parameters.Environmental and Water Resources Engineerin
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Evolution of CO2 Utilization Ratio and CO2 Storage under Different CO2 - EOR Operating Strategies: A Case Study on SACROC Unit Permian Basin
Bureau of Economic Geolog
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Impact of field development strategies on CO2 trapping mechanisms in a CO2– EOR field: A case study in the permian basin (SACROC unit)
Bureau of Economic Geolog
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Impact of Relative Permeability Uncertainty on CO Trapping Mechanisms in a CO-EOR Process: A Case Study in the U.S. Gulf Coast Cranfield
Bureau of Economic Geolog