Many oil reservoirs worldwide have cycle dependent oil recovery either by design (e.g. WAG injection) or unintended (e.g. repeated expansion/shrinkage of gas cap). However, to reliably predict oil recovery involving three-phase flow process, a transformational shift in the procedure to model such complex recovery method is needed. Therefore, this study focused on identifying the shortcomings of the current reservoir simulators to improve the simulation formulation of the cycle-dependent three-phase relative- permeability hysteresis. To achieve this objective, several core-scale water-alternating-gas (WAG) injection experiments were analysed to identify the trends and behaviours of oil recovery by the different WAG cycles. Furthermore, these experiments were simulated to identify the limitations of the current commercial simulators available in the industry. Based on the simulation efforts to match the observed experimental results, a new methodology to improve the modelling process of WAG injection using the current simulation capabilities was suggested. Then the WAG injection core-flood experiments utilized in this study were simulated to validate the new approach. The results of unsteady-state WAG injection experiments performed at different conditions were used in this simulation study. The simulation of the WAG injection experiments confirmed the positive impact of updating the three-phase relative-permeability hysteresis parameters in the later WAG injection cycles. This change significantly improved the match between simulation and WAG experimental results. Therefore, a systematic workflow for acquiring and analyzing the relevant data to generate the input parameters required for WAG injection simulation is presented. In addition, a logical procedure is suggested to update the simulation model after the third injection cycle as a workaround to overcome the limitation in the current commercial simulators. This guideline can be incorporated in the numerical simulators to improve the accuracy of oil recovery prediction by any cycle-dependent three-phase process using the current simulation capabilities.

Storing CO2 in deep saline aquifers is a viable technology to manage carbon emissions. However, in finite aquifers, reservoir pressure builds up quickly which can reduce injectivity and limit the ultimate storable quantities of CO2. Therefore, the purpose of this work is to investigate the optimum design for reservoir pressure-management wells during carbon dioxide (CO2) storage in finite aquifers using a numerical simulation method. In this paper, a synthetic aquifer model was used to investigate the optimal well placement and geometry, and well spacing to maximize CO2 storable quantities with a less total number of wells. Furthermore, the main target is to maximize the pore volume utilization and target injection rate per well without exceeding the reservoir fracture limit. A fit-for-purpose 3D reservoir simulation model used in this study was built to allow robust and accurate large-scale numerical simulation studies related to CO2 sequestration and storage using synthetic data. Multiple CO2 gas injectors were placed at the crest of the structure to utilize most of the available pore volume and maximize the injection rate. Various pressure management schemes were modeled and compared to find out the optimal design which can provide maximum injection rate and ultimate storage capacity. The results showed that well placement depth and the number of active relief wells both are playing a major role in maximizing the ultimate storage efficiency. Since reservoir heterogeneity and anisotropy can significantly affect the relief wells’ design, streamlines tracing can be very helpful to optimize the well spacing and orientation. After 80 years of injection, the simulation sensitivity study showed a significant difference (10-20% of CO2 storage efficiency) between the different pressure management schemes. In conclusion, relief wells are often needed to manage reservoir pressure build-up during CO2 storage in finite aquifers and their design is vital in maximizing the ultimate CO2 storage capacity. The outcome of this study is providing a useful guideline to optimize the field development plans and maximize the CO2 storage capacity in finite aquifers.