History matching is widely considered as the most time- and resource-consuming phase of reservoir simulation modeling. Even with the advent of modern, computer-assisted, history matching methods, the dynamic calibration of large-scale simulation models represents a considerable computational undertake. The challenges become even more pronounced with incorporation of subsurface and production uncertainty. This paper outlines a step forward in acceleration of reservoir simulation studies by applying a split/merge approach constrained by no-flow boundary drainage region. The method transforms the history-matching process into an accelerated progressive sequence of dynamic model updates in time and space. Each segment defined as distinctive drainage region, the boundaries of the drainage regions are mapped based on no-flow conditions. Each segment is dynamically calibrated and history matched simultaneously in parallel. Lastly, the segments are merged back to reconstruct the original model to run the prediction phase. The detail of the workflow is described, as well as the implementation of the workflow in a synthetic model. A comparison between the conventional approach and the new approach is discussed. Recommendation and a way forward are shared to capitalize on the accelerated method for future reservoir studies.

Managing carbon emissions has become a major responsibility for the oil and gas industry in a drive to ensure sustainable energy and create a clean environment. Therefore, governments, research centers, IOC’s and NOC’s are actively adopting new guidelines and inventing new technologies to safely circulate carbons. In this paper, the process of modeling CO2 sequestration in a deep saline aquifer will be discussed. Carbon dioxide can be safely stored indefinitely in subsurface geological formations by four trapping mechanisms; structural, residual, soluble, and mineral trapping. These four trapping mechanisms can take hundreds or thousands of years to happen. Furthermore, the oil and gas industry standard recommend that any technology used to store CO2 needs to demonstrate a storage capacity of 1000 years with less than 0.1 per-cent leakage potential per year. Therefore, modelling such process should capture any existing trapping mechanism, even if it happens after several hundreds of years, to ensure long-term secure storage of the CO2. Using our in-house simulator "GigaPOWERS", many sequestration scenarios were conducted to come up with a recommended guideline to maximize the volume of CO2 trapped in deep saline aquifers. This study used a giant synthetic anticline model with a variation in geological properties. The residual and soluble trapping mechanisms were captured through relative permeability hysteresis and extended water PVT tables respectively. Injecting CO2 into water aquifers is a dynamic process where drainage and imbibition cycles are likely to happen. Such processes cause the CO2 to be trapped in the middle of the pores as an immobile phase, which can be a favorable phenomenon maximizing the security of CO2 sequestration. Since CO2 is soluble in water, when it contacts the water phase it will form a carbonated water that is denser than water itself and migrates downward in a phenomenon known as "CO2 fingering". The CO2 solubility in water depends mainly on the salinity and temperature which both need to be accurately captured in the simulation model. Depending on the long-term objective of the sequestration project, the development strategy can be altered to maximize the outcome using the detailed simulation model. In this paper, the simulation best practices for modeling CO2 sequestration for maximum secure long-term storage (1000+ years) are suggested. Carbon dioxide, CO2, sequestration in deep saline aquifers is a well-known method to reduce carbon emissions. However, there is very little published literature on the simulation best practices for modeling the CO2 sequestration process. Therefore, this paper will be a pioneer to guide the industry for accurate simulation of such process.