1887

Abstract

Summary

Reservoir simulation is traditionally based on the assumption that water is an inert phase, while hydrocarbon components split into oil and gas phases. This approach is usually reasonable when modeling conventional hydrocarbon recovery, but specific applications may require accounting for mass exchange between the water and hydrocarbon phases.

We here present the extension of our Graphics Processing Units (GPUs) compositional reservoir simulator (Esler et al., 2021) to support gas-water equilibrium. Specifically, the Søreide and Whitson equation of state (EOS) ( ) was implemented to compute mutual solubilities of hydrocarbon/brine mixtures. The impact of salinity on phase equilibrium is accounted for, with salt being treated as an active tracer. The simulator uses a mass-variables formulation, meaning that little modifications to the construction of transport equations and Jacobian assembly was required; most of the required code changes are localized in the EOS module for the computation of component fugacities, and phase properties such as partial molar fractions and partial molar volumes.

Treating salt as an active tracer instead of defining a further pseudo-component has an important advantage with the Søreide and Whitson EOS. If salinity changes as in water vaporization processes, our choice ensures that flash iterations can still be cast as a Gibbs Minimization problem with salt being a constant parameter. On the contrary, salinity would change as flash iterations progress, jeopardizing the thermodynamic consistency of the phase equilibria. The overall reservoir simulation system of equations is still accurate to first order in time, at the cost of possibly slight volume imbalances at the end of converged timesteps.

The accuracy of the implementation with respect to conventional CPU ones is proved using a wide range of problems where hydrocarbon-water mass exchange play an important role in the physics of the recovery/storage process. In particular, we focused on CO2 sequestration in saline aquifers, where solubility trapping is a key mechanism.

A key conclusion of this work is that the extreme performance of GPU-based reservoir simulation naturally transfers to new fields of study, which is critical when modeling saline aquifers whose extent is an order of magnitude larger than that of typical oil and gas fields.

© EAGE Publications BV
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2022-09-05
2026-04-10

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Implementation of Soreide and Whitson EoS in a GPU-based Reservoir Simulator
Conference Proceedings 2022, 1 (2022); https://doi.org/10.3997/2214-4609.202244014
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