Plurigaussian modeling of geological domains based on the truncation of non-stationary Gaussian random fields

Nasser Madani, Xavier Emery

Research output: Contribution to journalArticlepeer-review

11 Citations (Scopus)


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 languageEnglish
Pages (from-to)893-913
Number of pages21
JournalStochastic Environmental Research and Risk Assessment
Issue number4
Publication statusPublished - May 1 2017
Externally publishedYes


  • 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)

Fingerprint Dive into the research topics of 'Plurigaussian modeling of geological domains based on the truncation of non-stationary Gaussian random fields'. Together they form a unique fingerprint.

Cite this