Accelerating Flash Calculation using Compositional Space for Compositional Simulation
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© 2017 Elsevier B.V. Compositional simulation is often required for modeling complex oil recovery processes, such as CO2 enhanced oil recovery (Chen and Reynolds, 2016; Dai et al., 2014). Flash calculation using Equation of State (EOS) is very CPU expensive in compositional simulation. Conventional approaches for initial guess of K-values usually have several levels of limitations. This paper reports our research motivated to provide trustworthy initial guess for flash calculation and further improve flash performance in isothermal processes. Reservoir fluid composition changes are categorized into two different scenarios: (a) slightly varying or constant composition changes in depletion process; and (b) sharp varying composition in gas injection process. Scenario (a) is reasonably parameterized as a compositional space of K-value and vapor mole fraction varied with pressure. Considering the actual simulation of gas injection process, a compositional space is defined via introducing a key pseudo composition as a controlling variable in addition to pressure. Flash calculation is formulated through direct solution of those non-linear equations in phase-split calculation, and solved by combining successive substitution iteration (SSI) and Newton-Raphson (NR) method. Using interpolation from the constructed compositional space, it is found that the initial guess of K-values for flash calculation are always obtained with safeguard. A variety of fluid samples has been applied for testing this new flash technique. The results show that initial guesses of K-values based on Wilson's correlation results cause much more flash iterations and even failures in some gas injection examples. On the other hand, the proposed method shows significant advantages in reducing the number of flash iterations in all examples. In addition, the SSI procedure in flash can even be bypassed and only NR procedure and a simple Rachford-Rice Equation Preconditioning is sufficient.
author list (cited authors)
Yan, B., Wang, Y., Nasrabadi, H., Killough, J. E., & Wu, K.