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 in | Journal of petroleum exploration and production technology Vol. 11; no. 2; pp. 839 - 856 |
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Main Authors | , , |
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Language | English |
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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. |
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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 |
Author_xml | – sequence: 1 givenname: Erfan orcidid: 0000-0003-1508-3577 surname: Hosseini fullname: Hosseini, Erfan email: e.hosseini19@gmail.com organization: Oil Industries Engineering and Construction Company (OIEC Group) – sequence: 2 givenname: Mohammad orcidid: 0000-0002-6369-3137 surname: Sarmadivaleh fullname: Sarmadivaleh, Mohammad organization: Department of Petroleum Engineering, Curtin University – sequence: 3 givenname: Zhongwei orcidid: 0000-0002-0782-0648 surname: Chen fullname: Chen, Zhongwei organization: School of Mechanical and Mining Engineering, Queensland University (UQ) |
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Cites_doi | 10.1088/1742-2132/3/3/003 10.1002/2015JB011879 10.1016/j.fuel.2016.11.094 10.1029/2019WR024944 10.1007/s10040-013-1080-2 10.1029/1999GL900419 10.1016/j.petrol.2018.09.028 10.1155/2019/3138972 10.1007/s00603-016-1064-3 10.1016/j.petrol.2018.07.013 10.1137/120865884 10.1144/SP292.21 10.1016/j.compgeo.2016.12.024 10.1126/science.220.4598.671 10.2118/107132-MS 10.2118/94186-MS 10.2118/53347-MS 10.1029/2003GL017174 10.1029/2002WR001628 |
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Keywords | Simulated annealing (S.A.) Numerical modeling Discrete fracture networks (DFN) Monte Carlo simulation Fluid flow |
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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 |
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