Gas Compositional Effect on Fit-For-Purpose CO2 Storage Capacity Estimation: A Case Study in Malaysian Depleted Clastic Gas Reservoir

Abstract

Abstract Amidst growing concerns about global warming and climate change, there has been increasing attention given to the storage of CO2 using underground geological structures. Depleted gas reservoirs have been identified as one of the most promising geological solutions for CO2 storage, owing to their data accessibility, economic feasibility, and safety. Currently, extensive studies are being conducted to appraise the CO2 storage potential of offshore Malaysian Depleted Clastic Gas Reservoir. The aim of this paper is to examine the impact of gas properties on CO2 storage capacity estimation in depleted gas reservoirs. The scope of the study includes a numerical simulation (Dynamic CO2 storage capacity) approach to model the behaviour of CO2 in the subsurface and to assess the significance of gas properties on the storage capacity of the reservoir. The Material Balance analysis (MBAL) method is employed in this study to model the potential CO2 storage capacity in the subsurface, taking into account the impact of gas properties such as z-factor and Gas Formation Volume Factor (Bg). The simulation process starts with history matching the historical data by using improved workflow. It eventually continued to forecast the production and CO2 storage capacity. Gas properties, in particular z-factor and Bg, significantly impact CO2 storage capacity estimation in depleted gas reservoirs, mainly due to the dynamic of injected CO2 composition which is mixed with residual gas. The study observed that a gas properties difference (Bg at Pinit is from 0.0109 to 0.0122 ft3/scf) in the reservoir D resulted in a 15% difference in CO2 storage capacity, while for the reservoir I case, a difference in gas properties (Bg at Pinit of 0.00840 to 0.00894 ft3/scf) resulted in a 3% difference. Besides that, an improved technique for estimating fit-for-purpose CO2 storage capacity was established in this study by generating and assigning individual PVT models through flash and recombination processes for reservoir without sufficient PVT information. The models are matched to the initial saturation pressure using characterized fluid properties available in major reservoirs, resulting in a more accurate and effective estimation of CO2 storage capacity. The study concludes that, when using the Material Balance analysis method, gas properties must be considered and properly characterized for better understanding and accuracy of CO2 storage capacity estimation. This paper provides new insights into the role of gas properties (z-factor and Bg) in CO2 storage capacity estimation. In addition, this work has improved the workflow for fit-for-purpose CO2 storage capacity estimation using Material Balance analysis. The results of this study provide a fresh perspective on the optimization of fit-for-purpose CO2 storage capacity estimation.