Abstract

Abstract Permanent storage of carbon dioxide requires accurate estimation of trapped gas saturation and reservoir storage capacity. Hydrogen and gas storage in subsurface reservoirs involves injection and withdrawal cycles, which necessitates the accurate estimation of hysteresis in relative permeability (kr) and capillary pressure (Pc) data. Cyclic injections in the form of Water Alternating Gas (WAG) injection is an effective Enhanced Oil Recovery (EOR) method for improving volumetric sweep efficiency in the reservoirs. When simulating all these processes, subsurface reservoir engineers rely on commercial software to estimate trapped gas saturation and cyclic hysteresis in kr and Pc data. However, few researchers have investigated the reliability of the available hysteresis models implemented in commercial software for this purpose. To this aim, a thorough sensitivity analysis was performed to investigate the performance of three-phase hysteresis models available in the literature for simulating the measured data of cyclic experiments. The Water Alternating Gas (WAG) experiment used in this study was performed at near-miscible conditions on a mixed-wet sandstone sample, and the cyclic injection was started with drainage. The results show that when simulating WAG experiments performed at low injection rates, using a hysteresis model developed by Aghabozorgi and Sohrabi (2019) provides the most accurate results for pressure drop, fluid saturations, and gradual oil production. However, the model developed by Larsen and Skauge (1998) can be only used for experiments reaching maximum gas saturation in their first three-phase imbibition cycle, mostly representing the limited grid blocks near the wellbore. Even in this scenario, the dependence of the model on Land’s initial-residual relationship and trapping coefficient is questionable. This study highlights the possible pitfalls of using commercial software for estimating trapped saturation and hysteresis in relative permeability and capillary pressure. It also provides useful suggestions for improving the accuracy of performed simulations. The presented results are vital for the oil and gas experts as they can demand improvements in current approaches and promote constant growth and development of commercial software.

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