Abstract
The plurigaussian model is used in mining engineering, oil reservoir characterization, hydrology and environmental sciences to simulate the layout of geological domains in the subsurface, while reproducing their spatial continuity and dependence relationships. However, this model is well-established only in the stationary case, when the spatial distribution of the domains is homogeneous in space, and suffers from theoretical and practical impediments in the non-stationary case. To overcome these limitations, this paper proposes extending the model to the truncation of intrinsic random fields of order k with Gaussian generalized increments, which allows reproducing spatial trends in the distribution of the geological domains. Methodological tools and algorithms are presented to infer the model parameters and to construct realizations of the geological domains conditioned to existing data. The proposal is illustrated with the simulation of rock type domains in an ore deposit in order to demonstrate its applicability. Despite the limited number of conditioning data, the results show a remarkable agreement between the simulated domains and the lithological model interpreted by geologists, while the conventional stationary plurigaussian model turns out to be unsuccessful.
| Original language | English |
|---|---|
| Pages (from-to) | 893-913 |
| Number of pages | 21 |
| Journal | Stochastic Environmental Research and Risk Assessment |
| Volume | 31 |
| Issue number | 4 |
| DOIs | |
| Publication status | Published - May 1 2017 |
| Externally published | Yes |
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Keywords
- Generalized covariance function
- Geological domaining
- Intrinsic random fields of order k
- Subsurface heterogeneity
ASJC Scopus subject areas
- Environmental Engineering
- Environmental Chemistry
- Water Science and Technology
- Safety, Risk, Reliability and Quality
- Environmental Science(all)
Cite this
Plurigaussian modeling of geological domains based on the truncation of non-stationary Gaussian random fields. / Madani, Nasser; Emery, Xavier.
In: Stochastic Environmental Research and Risk Assessment, Vol. 31, No. 4, 01.05.2017, p. 893-913.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Plurigaussian modeling of geological domains based on the truncation of non-stationary Gaussian random fields
AU - Madani, Nasser
AU - Emery, Xavier
PY - 2017/5/1
Y1 - 2017/5/1
N2 - The plurigaussian model is used in mining engineering, oil reservoir characterization, hydrology and environmental sciences to simulate the layout of geological domains in the subsurface, while reproducing their spatial continuity and dependence relationships. However, this model is well-established only in the stationary case, when the spatial distribution of the domains is homogeneous in space, and suffers from theoretical and practical impediments in the non-stationary case. To overcome these limitations, this paper proposes extending the model to the truncation of intrinsic random fields of order k with Gaussian generalized increments, which allows reproducing spatial trends in the distribution of the geological domains. Methodological tools and algorithms are presented to infer the model parameters and to construct realizations of the geological domains conditioned to existing data. The proposal is illustrated with the simulation of rock type domains in an ore deposit in order to demonstrate its applicability. Despite the limited number of conditioning data, the results show a remarkable agreement between the simulated domains and the lithological model interpreted by geologists, while the conventional stationary plurigaussian model turns out to be unsuccessful.
AB - The plurigaussian model is used in mining engineering, oil reservoir characterization, hydrology and environmental sciences to simulate the layout of geological domains in the subsurface, while reproducing their spatial continuity and dependence relationships. However, this model is well-established only in the stationary case, when the spatial distribution of the domains is homogeneous in space, and suffers from theoretical and practical impediments in the non-stationary case. To overcome these limitations, this paper proposes extending the model to the truncation of intrinsic random fields of order k with Gaussian generalized increments, which allows reproducing spatial trends in the distribution of the geological domains. Methodological tools and algorithms are presented to infer the model parameters and to construct realizations of the geological domains conditioned to existing data. The proposal is illustrated with the simulation of rock type domains in an ore deposit in order to demonstrate its applicability. Despite the limited number of conditioning data, the results show a remarkable agreement between the simulated domains and the lithological model interpreted by geologists, while the conventional stationary plurigaussian model turns out to be unsuccessful.
KW - Generalized covariance function
KW - Geological domaining
KW - Intrinsic random fields of order k
KW - Subsurface heterogeneity
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U2 - 10.1007/s00477-016-1365-9
DO - 10.1007/s00477-016-1365-9
M3 - Article
AN - SCOPUS:85001022116
VL - 31
SP - 893
EP - 913
JO - Stochastic Environmental Research and Risk Assessment
JF - Stochastic Environmental Research and Risk Assessment
SN - 1436-3240
IS - 4
ER -