The objective of this work is to utilize integrated geomechanics, field vertical seismic profile (VSP) and microseismic data to characterize the complex subsurface stress conditions at the Farnsworth Unit (FWU). The model is based on a five-spot sector model extracted from a primary geomechanical model. The five-spot well injection pattern is characterized by extensive reservoir characterization data, such well logs, extracted cores and borehole geophone data, to facilitate the detailed examination of stress changes and microseismic event occurrences. The study utilizes field vertical seismic volumes acquired from the injection well 13-10A. The seismic volumes successfully provided snapshots of the behavior of the reservoir at distinct times. The use of VSP and microseismic data provided direct and indirect estimates of the dynamic stress changes occurring in the overburden, reservoir and underburden rock formations. In order to illuminate the stress regions and identify rocks that have undergone inelastic failure, microseismic event occurrences were utilized. Microseismic activity has been detected at the FWU; further study of its locations, timing, and magnitude was needed to deduce the nature of the changing stress state. The results of the study revealed that microseismic events were successfully modeled within the Morrow B formation. Moment magnitudes of seismic events were within the same magnitudes for events in the reservoir, suggesting the suitability of the model. The results of the study showed that the computed moment magnitudes for seismic events were insignificant to warrant safety concerns. The study findings showed the usefulness of coupled hydromechanical models in predicting the subsurface stress changes associated with CO₂ injection. The knowledge gained from this study will serve as a guideline for industries planning to undertake underground CO₂ storage, and characterize the subsurface stress changes.

This study evaluates the feasibility of CO₂ Water-Alternating-Gas (WAG) injection for enhanced oil recovery (EOR) in a highly heterogeneous reservoir using cost-effective and efficient tools. The Rule of Thumb method was initially used to screen the reservoir, confirming its suitability for CO₂-WAG injection. A fluid model was constructed by comparing several component lumping methods, selecting the approach with the least deviation from experimental data to ensure accuracy. The minimum miscibility pressure (MMP), a critical parameter for CO₂-EOR, was estimated using three methodologies: 1D simulation based on the slim tube test, semi-empirical analytical correlations, and fluid modeling. These techniques provided complementary insights into the reservoir’s miscibility conditions. The CO₂ Prophet software version 1 was employed to history-match production data and evaluate different development strategies. The Kinder Morgan CO₂ Scoping Model was used to perform production forecasting and assess the economic viability of implementing CO₂-WAG. Quantitative comparisons showed that the CO₂ Prophet version 1 model revealed minimal deviations from the history match results: oil production estimates differed by only 3.5%, and water production estimates differed by −4.11%. Cumulative oil recovery was projected to reach approximately 20.26 MMSTB over a 25-year production period. The results indicate that CO₂-WAG injection could enhance oil recovery significantly compared to water flooding while maintaining economic feasibility. This study demonstrates the practical integration of analytical tools and inexpensive models to evaluate and optimize CO₂-EOR strategies in complex reservoirs. The findings provide a systematic workflow for deploying CO₂-WAG in heterogeneous reservoirs, balancing technical and economic considerations.

This study provides a methodology for optimizing oil production and CO2 sequestration using an integrated asset model of the Farnsworth Unit field, incorporating extensive geological, geophysical, and engineering data. Sensitivity analysis identified critical parameters impacting oil recovery and CO2 storage, leading to the construction of a proxy model using polynomial regression and radial basis function neural networks, with the latter proving more effective for "What-if" analysis. The sensitivity analysis indicated that the Corey parameters impact cumulative oil produced the most. Comprehensive history matching validated the model against historical production data, ensuring reliability for forecasting and optimization. Two scenarios, "Do-Nothing" and development strategy, were forecasted over 15 years (2020-2035). The "Do-Nothing" scenario resulted in 9.57 MMSTB of oil recovery and 2,822.70 MMlbs of CO2 storage. The development strategy case improved outcomes with 13.95 MMSTB of oil recovery and 5,061.68 MMlbs of CO2 stored, and was selected for optimization using particle swarm optimization. The optimized strategy achieved 14,043,372 STB of cumulative oil and 4,832.18 MMlbs of CO2 stored, and increased the field NPV by 25.84% to $114,871,730. This study underscores the significance of integrated asset modeling in enhancing oil recovery and optimizing CO2-EOR processes, providing valuable insights into operational conditions and constraints.