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Random network modelling approach to investigate the single‐phase and quasi‐static immiscible two‐phase flow properties in the Mesaverde formation
Author(s) -
Bashtani Farzad,
Kryuchkov Sergey,
Bryan Jonathan,
Maini Brij,
Kantzas Apostolos
Publication year - 2016
Publication title -
the canadian journal of chemical engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.404
H-Index - 67
eISSN - 1939-019X
pISSN - 0008-4034
DOI - 10.1002/cjce.22629
Subject(s) - capillary pressure , relative permeability , porous medium , capillary action , wetting , mechanics , permeability (electromagnetism) , network model , two phase flow , displacement (psychology) , flow (mathematics) , materials science , surface tension , capillary number , phase (matter) , geotechnical engineering , porosity , thermodynamics , geology , computer science , physics , chemistry , composite material , database , membrane , psychotherapist , quantum mechanics , psychology , biochemistry
Understanding the microscopic flow behaviour of hydrocarbons and water in porous media gains importance as more and more reservoirs are being exploited. Network modelling techniques could be extended to tighter media as long as Darcy's law is applicable. 3D random networks are constructed in order to represent the Mesaverde formation which is located in north Wyoming, USA. The network modelling software solves the fundamental equations of single‐phase and two‐phase immiscible flow incorporating wettability and contact angle assuming a quasi‐static displacement mechanism. Macroscopic properties of the porous media network representation such as porosity, absolute permeability, and formation factor are calculated and whenever possible compared to experimental data. Subsequently, immiscible two‐phase flow properties such as capillary pressure, relative permeability, and resistivity curves are predicted and compared to available experimental data. The effect of interfacial tension alteration is also investigated as an attempt to demonstrate the capability of the network modelling technique to show physical fluid behaviour. It is observed that the capillary pressure curve obtained using MICP data can be used to calibrate and validate the network model generated to represent the sample. The study shows that the modified random network modelling technique is capable of modelling low permeable porous medium and predicting single‐phase and immiscible two‐phase flow properties assuming quasi‐static displacement mechanism.