Multiple-point statistical simulations constrained by continuous auxiliary data

IAMG 2006 - 11th International Congress for Mathematical Geology: Quantitative Geology from Multiple Sources

Volumn , Issue , 2006, Pages

  Chugunova, T L ^a,b   Hu, L Y ^a  

^a IFP ENERGIES NOUVELLES   (France)

^b PSL RESEARCH UNIVERSITY   (France)

Author keywords

Geostatistical simulation; Multiple point statistics; Non stationarity; Training image

Indexed keywords

GEOLOGY; SALINITY MEASUREMENT;

ANALYTICAL APPROXIMATION; CONDITIONAL PROBABILITIES; DEGREE OF APPROXIMATION; GEOSTATISTICAL SIMULATION; MULTIPLE-POINT STATISTICS; NON-STATIONARITIES; STATISTICAL SIMULATION; TRAINING IMAGE;

NUMERICAL METHODS;

EID: 84902437027     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (6)

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2. Journel, A.G., 2002, Combining knowledge from diverse sources: An alternative to traditional data independence hypotheses. Math. Geol., 34(5), p.573-596.
3. Strebelle, S., 2000, Sequential Simulation drawing structures from training images. Ph.D thesis, Stanford University.
4. Strebelle, S., Payrazyan, K. and Caers, J. 2002, Modeling of a deepwater turbidity reservoir conditional to seismic data using multiple-point geostatistics. SPE 77425.
5. Strebelle, S. and Zhang, T., 2004, Non stationary multiple-point geostatistical models. In O. Leuangthong and C. Deutsch (Eds.), "Geostatistics Banff 2004", Springer, p.235-244.
6. Sunderrajan, K., Boucher, A. and Journel, A.G., 2004, Evaluating information redundancy through the TAU model. In O. Leuangthong and C. Deutsch (Eds.), "Geostatistics Banff 2004", Springer, p.1037-1046.