Subventions et des contributions :

Titre :
Utilization of Percolation Theory and Multiphysics’ Concept to Develop Dynamic Modeling and Accurate Upscaling Approaches for Two-Phase Flow during Immiscible Displacement of Heavy Oil in Porous Media
Numéro de l’entente :
RGPIN
Valeur d'entente :
120 000,00 $
Date d'entente :
10 mai 2017 -
Organisation :
Conseil de recherches en sciences naturelles et en génie du Canada
Location :
Saskatchewan, Autre, CA
Numéro de référence :
GC-2017-Q1-03530
Type d'entente :
subvention
Type de rapport :
Subventions et des contributions
Informations supplémentaires :

Subvention ou bourse octroyée s'appliquant à plus d'un exercice financier. (2017-2018 à 2022-2023)

Nom légal du bénéficiaire :
Torabi, Farshid (University of Regina)
Programme :
Programme de subventions à la découverte - individuelles
But du programme :

Heavy oil recovery is typically low, and a significant amount of unrecovered heavy oil is left in the reservoir. Heavy oil production requires enhanced oil recovery (EOR) processes, which fundamentally cause continuous two- or three- phase flow (immiscible or miscible displacement) in porous media. The successful applications of such EOR techniques require more detailed knowledge of flow mechanisms in porous media.
The objective of this study is to investigate the fundamental mechanisms of two phase flow (immiscible displacement) in porous media saturated with heavy oil using dynamic percolation network modeling, and its application in heavy oil reservoirs. Since there are many flow and transport mechanisms involved in various EOR techniques, the focus of this study will be on the dynamic immiscible displacement with hot-water, and solvent injection in heavy oil systems so that all proposed short and long term objectives can be achieved. This research program will help fill the knowledge gap in the area of multiphase flow in porous media.
Although dynamic pore-network modeling has been studied for years, its application in heavy oil systems has rarely been investigated. We will develop a multiphysical dynamic percolation network modeling method with integrated thermal conductivity of hot-water and solvent injection in heavy oil systems. With the help of this multiphysical dynamic percolation network modeling, the effects of pore scale heterogeneity, particularly pore connectivity and pore-size distribution, viscosity ratio M, capillary number Ca, gravity, thermal conductance and effects of properties of heavy oil and solvent (CO2) on the (hot-water and solvent) displacement will be studied.
A basic concept in percolation theory is that permeability k obeys the ‘universal’ scaling law (k~(z-zc)β, where z is coordination number of porous media, zc is percolation threshold and β is related to pore size distribution). ‘Universal’ scaling law is independent of network lattice and is valid in both regular and disorder networks (pore space of rocks is disorder network), which can be extended to two-phase flow. ’Universal’ properties and upscale relations (or mathematical models) between pore-scale heterogeneity, M, Ca, thermal conductance and some macroscopic properties (relative permeability, residual oil saturation, viscous fingering) in heavy oil systems can be derived based on network simulations. The upscaled relations and mathematical models will be validated with experiments on micromodel and sandpacks.
All results, including the multiphysical dynamic percolation network modeling and upscaling models, will enable study of more complex related phenomena in EOR processes, such as injection of solvent into pore space containing saline water. Such results allow researchers and industry engineers to optimize the performance of oil production.