Developing a new algorithm for numerical modeling of discrete fracture network (DFN) for anisotropic rock and percolation properties

The role of natural fractures in future reservoir performance is prominent. The fractured porous media is composed of an interconnected network of fractures and blocks of the porous medium where fractures occur in various scales and have a strong influence either when most of the flow is concentrate...

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Published inJournal of petroleum exploration and production technology Vol. 11; no. 2; pp. 839 - 856
Main Authors Hosseini, Erfan, Sarmadivaleh, Mohammad, Chen, Zhongwei
Format Journal Article
LanguageEnglish
Published Cham Springer International Publishing 01.02.2021
Springer Nature B.V
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Abstract The role of natural fractures in future reservoir performance is prominent. The fractured porous media is composed of an interconnected network of fractures and blocks of the porous medium where fractures occur in various scales and have a strong influence either when most of the flow is concentrated and them or when they act as barriers. A general numerical model for discrete fracture networks (DFN) is usually employed to handle the observed wide variety of fracture properties and the lack of direct fracture visualization. These models generally use fracture properties’ stochastic distribution based on sparse and seismic data without any physical model constraint. Alternatively, a DFN model includes usual numerical geomechanical approaches like boundary element and finite element. But here, a geostatistical methodology has been used to generate a DFN model. In this paper, an alternative modeling technique is employed to create the realization of an anisotropic fractured rock using simulated annealing (SA) optimization algorithm. There is a notable positive correlation between fracture length and position. There are three principal subjects in a study of fractured rocks. Firstly, the network’s connectivity, secondly, fluid flows through the system, and thirdly, dispersion. Here, connectivity of generated networks is considered. Continuum percolation is the mathematical model to study the geometry of connected components in a random subset of space. Different random realizations from the S.A. algorithm in four different sizes of L  = 100, 150, 200, 250 at post-threshold condition are used as disordered media in percolation theory to compute percolation properties using Monte Carlo simulation. The percolation threshold (critical fracture density) and two crucial scaling exponents ( β and υ ) that dictate the model’s connectivity behavior are estimated to over 200 realizations.
AbstractList The role of natural fractures in future reservoir performance is prominent. The fractured porous media is composed of an interconnected network of fractures and blocks of the porous medium where fractures occur in various scales and have a strong influence either when most of the flow is concentrated and them or when they act as barriers. A general numerical model for discrete fracture networks (DFN) is usually employed to handle the observed wide variety of fracture properties and the lack of direct fracture visualization. These models generally use fracture properties’ stochastic distribution based on sparse and seismic data without any physical model constraint. Alternatively, a DFN model includes usual numerical geomechanical approaches like boundary element and finite element. But here, a geostatistical methodology has been used to generate a DFN model. In this paper, an alternative modeling technique is employed to create the realization of an anisotropic fractured rock using simulated annealing (SA) optimization algorithm. There is a notable positive correlation between fracture length and position. There are three principal subjects in a study of fractured rocks. Firstly, the network’s connectivity, secondly, fluid flows through the system, and thirdly, dispersion. Here, connectivity of generated networks is considered. Continuum percolation is the mathematical model to study the geometry of connected components in a random subset of space. Different random realizations from the S.A. algorithm in four different sizes of L = 100, 150, 200, 250 at post-threshold condition are used as disordered media in percolation theory to compute percolation properties using Monte Carlo simulation. The percolation threshold (critical fracture density) and two crucial scaling exponents (β and υ) that dictate the model’s connectivity behavior are estimated to over 200 realizations.
The role of natural fractures in future reservoir performance is prominent. The fractured porous media is composed of an interconnected network of fractures and blocks of the porous medium where fractures occur in various scales and have a strong influence either when most of the flow is concentrated and them or when they act as barriers. A general numerical model for discrete fracture networks (DFN) is usually employed to handle the observed wide variety of fracture properties and the lack of direct fracture visualization. These models generally use fracture properties’ stochastic distribution based on sparse and seismic data without any physical model constraint. Alternatively, a DFN model includes usual numerical geomechanical approaches like boundary element and finite element. But here, a geostatistical methodology has been used to generate a DFN model. In this paper, an alternative modeling technique is employed to create the realization of an anisotropic fractured rock using simulated annealing (SA) optimization algorithm. There is a notable positive correlation between fracture length and position. There are three principal subjects in a study of fractured rocks. Firstly, the network’s connectivity, secondly, fluid flows through the system, and thirdly, dispersion. Here, connectivity of generated networks is considered. Continuum percolation is the mathematical model to study the geometry of connected components in a random subset of space. Different random realizations from the S.A. algorithm in four different sizes of L  = 100, 150, 200, 250 at post-threshold condition are used as disordered media in percolation theory to compute percolation properties using Monte Carlo simulation. The percolation threshold (critical fracture density) and two crucial scaling exponents ( β and υ ) that dictate the model’s connectivity behavior are estimated to over 200 realizations.
Author Hosseini, Erfan
Chen, Zhongwei
Sarmadivaleh, Mohammad
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CitedBy_id crossref_primary_10_1016_j_ijrmms_2021_104737
crossref_primary_10_32604_EE_2021_016645
crossref_primary_10_1007_s13202_023_01725_z
crossref_primary_10_1016_j_petsci_2024_01_007
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Keywords Simulated annealing (S.A.)
Numerical modeling
Discrete fracture networks (DFN)
Monte Carlo simulation
Fluid flow
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Snippet The role of natural fractures in future reservoir performance is prominent. The fractured porous media is composed of an interconnected network of fractures...
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springer
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SubjectTerms Algorithms
Anisotropic rocks
Computational fluid dynamics
Computer simulation
Connectivity
Constraint modelling
Earth and Environmental Science
Earth Sciences
Energy Systems
Fluid flow
Fractures
Geology
Geomechanics
Industrial and Production Engineering
Industrial Chemistry/Chemical Engineering
Mathematical analysis
Mathematical models
Modelling
Monitoring/Environmental Analysis
Monte Carlo simulation
Numerical models
Offshore Engineering
Optimization
Original Paper-Exploration Engineering
Percolation
Percolation theory
Porous media
Properties
Properties (attributes)
Reservoir performance
Scaling
Seismic data
Simulated annealing
Statistical methods
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Title Developing a new algorithm for numerical modeling of discrete fracture network (DFN) for anisotropic rock and percolation properties
URI https://link.springer.com/article/10.1007/s13202-020-01079-w
https://www.proquest.com/docview/2490403515
Volume 11
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