@Article{icces.2023.09671,
AUTHOR = {Shuyu Sun},
TITLE = {Numerical Simulation of Multiphase Flow in Subsurface Reservoirs:  Existing Challenges and New Treatments},
JOURNAL = {The International Conference on Computational \& Experimental Engineering and Sciences},
VOLUME = {27},
YEAR = {2023},
NUMBER = {2},
PAGES = {1--2},
URL = {http://www.techscience.com/icces/v27n2/54163},
ISSN = {1933-2815},
ABSTRACT = {Two or multiple phases commonly occur as fluid mixture in petroleum industry, where oil, gas and water 
are often produced and transported together. As a result, petroleum reservoir engineers spent great efforts 
in the development and production of oil and gas reservoirs by conducting and interpolating the simulation 
of multiphase flows in porous geological formation. Meanwhile, environmental scientists use subsurface 
flow and transport models to investigate and compare for example various schemes to inject and store CO2
in subsurface geological formations, such as depleted reservoirs and deep saline aquifers. In this work, we 
first present an introduction of numerical simulation of subsurface multiphase flow and its challenges 
including multiscale heterogeneity, strong and unbalanced nonlinearity, solution discontinuity, local mass 
conservation, numerical stability and bound preservation. For example, bound preservation is a desired 
basic property of numerical solutions but often not easy to have. In this basic requirement, it is desired to 
have the predicted physical quantities sit within a physically meaningful range. Specifically, the predicated 
saturation should sit between 0 and 1 while the predicated molar concentration should sit between 0 and 
the maximum value allowed by the equation of state. Unfortunately, popular simulation methods used in 
the industries do not preserve physical bounds. A commonly used fix to this problem is to simply apply a 
cut-off operator (say, to the computed saturation) at each time step, i.e., to set the saturation to be zero 
whenever it becomes negative, and to set it to one whenever it becomes larger than one. However, this cutoff practice does not only destroy the local mass conservation, but it also damages the global mass 
conservation, which seriously ruins the numerical accuracy and physical interpretability of the simulation 
results. After going through a number of well-known challenges, we present three frameworks based on our 
recent works to address some of these challenges. The first one to present is our recently-proposed boundpreserving, phase-wise locally conservative IMPES-like semi-implicit method for two-phase flow in porous 
media [1]. In addition, we also present our framework on unconditionally bound-preserving, phase-wise 
locally conservative fully-implicit method for porous media multiphase flow [2,3]. Finally, we present our 
study on a series of deep learning methods as applied to phase behavior calculation, which can greatly speed 
up the compositional multiphase flow simulation [4].},
DOI = {10.32604/icces.2023.09671}
}