Combining a connected-component labeling algorithm with FILTERSIM to simulate continuous discrete fracture networks

Because modeling the flow of gas and oil in fractured media is increasingly important, multipoint geostatistics approaches, such as single normal equation simulation and FILTERSIM, have become a focus of research in the simulation of sedimentary faces. However, there are problems when these methods...

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Vydáno v:Environmental earth sciences Ročník 76; číslo 8; s. 1 - 13
Hlavní autoři: Jia, Ming, Zhang, Liehui, Guo, Jingjing
Médium: Journal Article
Jazyk:angličtina
Vydáno: Berlin/Heidelberg Springer Berlin Heidelberg 01.04.2017
Springer Nature B.V
Témata:
Algorithms
Biogeosciences
Computational fluid dynamics
Computer simulation
Earth and Environmental Science
Earth Sciences
Environmental Science and Engineering
equations
Fluid flow
Fractures
Geochemistry
Geology
Geostatistics
Hydrology/Water Resources
Image classification
Innovation
Innovations
Labeling
Mathematical models
Modelling
Natural gas
oils
Simulation
Subsurface Energy Storage II
Terrestrial Pollution
Thematic Issue
Training
Training image
CCL-FILTERSIM
Run-based connected-component algorithm
Discrete fracture network
Multipoint geostatistics
ISSN:1866-6280, 1866-6299
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Popis
Shrnutí:Because modeling the flow of gas and oil in fractured media is increasingly important, multipoint geostatistics approaches, such as single normal equation simulation and FILTERSIM, have become a focus of research in the simulation of sedimentary faces. However, there are problems when these methods are applied to the simulation of discrete fracture networks (DFNs). The biggest problem is that the generated fractures are discontinuous, behaving as separated and isolated points. This paper proposes an improved approach we call CCL-FILTERSIM, which combines FILTERSIM with a run-based, connected-component labeling algorithm to generate more continuous fractures. This paper focuses on the continuity of the simulated fracture network and adopts the scan of the training image, classification of the patterns, and the sequential simulation proposed by FILTERSIM. The principle innovation of the CCL-FILTERSIM approach is the choice of data pattern. Only patterns that form better continuous object patterns are chosen. This is realized by a connected-component labeling algorithm that calculates the connected runs of selected patterns and chooses the pattern with the least runs. Some cases are presented to compare realizations from CCL-FILTERSIM and FILTERSIM, which show that CCL-FILTERSIM yields more continuous objects than FILTERSIM. The DFNs generated by this method provide better conditions for subsequent fluid flow research.
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ISSN:1866-6280
1866-6299
DOI:10.1007/s12665-017-6647-0