Details
| Originalsprache | Englisch |
|---|---|
| Seiten (von - bis) | 22-37 |
| Seitenumfang | 16 |
| Fachzeitschrift | Advances in water resources |
| Jahrgang | 54 |
| Frühes Online-Datum | 14 Dez. 2012 |
| Publikationsstatus | Veröffentlicht - Apr. 2013 |
Abstract
Subsurface flow and solute transport simulations are performed using different scenarios of permeability fields generated from the sequential Gaussian simulation method (SGS), the multiple-point FILTERSIM algorithm and a new multiple-point wavelet-based simulation method (SWS). The SWS method is a multiple-point pattern-based simulation method which uses discrete wavelet transformation for the representation of geologic heterogeneity. For pattern-based simulation, patterns are generated by scanning a training image with a spatial template. The pattern classifications were performed after reducing the dimension of patterns by wavelet decomposition at the suitable scale and by taking only scaling components of wavelet decomposed patterns. The simulation is performed in a sequential manner by finding the best-matched class corresponding to the conditioning data and by randomly sampling a pattern from the best-matched class. The developed method is compared with two other multi-point simulation algorithms, FLTERSIM and SIMPAT. The comparative results revealed that the proposed method is computationally faster than the other two methods while the simulation maps are comparable. Numerical simulations of two flow problems are performed using SGS, SWS and FILTERSIM realizations. The numerical results show a superiority of the SWS method over SGS and FILTERSIM in terms of reproduction of the reference images main features, and agreement with flow and transport results obtained on reference images.
ASJC Scopus Sachgebiete
- Umweltwissenschaften (insg.)
- Gewässerkunde und -technologie
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in: Advances in water resources, Jahrgang 54, 04.2013, S. 22-37.
Publikation: Beitrag in Fachzeitschrift › Artikel › Forschung › Peer-Review
}
TY - JOUR
T1 - Geologic heterogeneity recognition using discrete wavelet transformation for subsurface flow solute transport simulations
AU - Mustapha, Hussein
AU - Chatterjee, Snehamoy
AU - Dimitrakopoulos, Roussos
AU - Graf, Thomas
PY - 2013/4
Y1 - 2013/4
N2 - Subsurface flow and solute transport simulations are performed using different scenarios of permeability fields generated from the sequential Gaussian simulation method (SGS), the multiple-point FILTERSIM algorithm and a new multiple-point wavelet-based simulation method (SWS). The SWS method is a multiple-point pattern-based simulation method which uses discrete wavelet transformation for the representation of geologic heterogeneity. For pattern-based simulation, patterns are generated by scanning a training image with a spatial template. The pattern classifications were performed after reducing the dimension of patterns by wavelet decomposition at the suitable scale and by taking only scaling components of wavelet decomposed patterns. The simulation is performed in a sequential manner by finding the best-matched class corresponding to the conditioning data and by randomly sampling a pattern from the best-matched class. The developed method is compared with two other multi-point simulation algorithms, FLTERSIM and SIMPAT. The comparative results revealed that the proposed method is computationally faster than the other two methods while the simulation maps are comparable. Numerical simulations of two flow problems are performed using SGS, SWS and FILTERSIM realizations. The numerical results show a superiority of the SWS method over SGS and FILTERSIM in terms of reproduction of the reference images main features, and agreement with flow and transport results obtained on reference images.
AB - Subsurface flow and solute transport simulations are performed using different scenarios of permeability fields generated from the sequential Gaussian simulation method (SGS), the multiple-point FILTERSIM algorithm and a new multiple-point wavelet-based simulation method (SWS). The SWS method is a multiple-point pattern-based simulation method which uses discrete wavelet transformation for the representation of geologic heterogeneity. For pattern-based simulation, patterns are generated by scanning a training image with a spatial template. The pattern classifications were performed after reducing the dimension of patterns by wavelet decomposition at the suitable scale and by taking only scaling components of wavelet decomposed patterns. The simulation is performed in a sequential manner by finding the best-matched class corresponding to the conditioning data and by randomly sampling a pattern from the best-matched class. The developed method is compared with two other multi-point simulation algorithms, FLTERSIM and SIMPAT. The comparative results revealed that the proposed method is computationally faster than the other two methods while the simulation maps are comparable. Numerical simulations of two flow problems are performed using SGS, SWS and FILTERSIM realizations. The numerical results show a superiority of the SWS method over SGS and FILTERSIM in terms of reproduction of the reference images main features, and agreement with flow and transport results obtained on reference images.
KW - Connectivity
KW - Geologic heterogeneity
KW - Geostatistical simulation
KW - Multiphase flow
KW - Spatial patterns
KW - Wavelet analysis
UR - http://www.scopus.com/inward/record.url?scp=84873863847&partnerID=8YFLogxK
U2 - 10.1016/j.advwatres.2012.11.018
DO - 10.1016/j.advwatres.2012.11.018
M3 - Article
AN - SCOPUS:84873863847
VL - 54
SP - 22
EP - 37
JO - Advances in water resources
JF - Advances in water resources
SN - 0309-1708
ER -