TiGenerator: Object-based training image generator

Computers and Geosciences

Volumn 34, Issue 12, 2008, Pages 1753-1761

  Maharaja, Amisha ^a  

^a STANFORD UNIVERSITY   (United States)

Author keywords

Multiple point geostatistics; SGeMS; Training images

Indexed keywords

BOOLEAN FUNCTIONS; COMPUTER SOFTWARE; COMPUTER SYSTEMS; GRAPHICAL USER INTERFACES; OPEN SYSTEMS;

CODE DESIGNS; IMAGE GENERATOR; MULTIPLE-POINT GEOSTATISTICS; NON-PARAMETRIC; OBJECT-BASED; OPEN SOURCE SOFTWARE; PLUG INS; SGEMS; TRAINING IMAGES; USER INTERFACES;

THREE DIMENSIONAL;

ALGORITHM; COMPUTER SIMULATION; GEOSTATISTICS; GRAPHICAL METHOD; IMAGE ANALYSIS; PARAMETERIZATION; SOFTWARE;

EID: 52049122828     PISSN: 00983004     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.cageo.2007.08.012     Document Type: Article

References (15)

1. Bowman S.A., and Vail P.R. Interpreting the stratigraphy of the Baltimore canyon section, offshore New Jersey with phil, a stratigraphic simulator. In: Harbaugh J., Watney W., Rankey E., Slingerland R., Goldstein R., and Franseen E. (Eds). Numerical Experiments in Stratigraphy: Recent Advances in Stratigraphic and Sedimentologic Computer Simulations (1999), SEPM Special Publication, Tulsa, OK 117-138
2. Cojan, I., Fouche, O., Lopez, S., Rivoirard, J., 2004. Processed-based reservoir modelling in the example of meandering channel. In: Proceedings of the 7th Annual Geostatistics Congress, Banff, Alberta, Canada, pp. 611-619.
3. Damsleth, E., Tjolsen, C., Omre, K., Haldorsen, H., 1990. A two-stage stochastic model applied to a north sea reservoir. In: 65th SPE Annual Technical Conference and Exhibition, New Orleans, LA, pp. 791-802.
4. Deutsch C., and Journel A. GSLIB: Geostatistical Software Library and User's Guide. second ed. (1998), Oxford University Press, New York 384pp
5. Deutsch C., and Tran T. Fluvsim: a program for object-based stochastic modeling of fluvial depositional systems. Computers & Geosciences 28 (2002) 525-535
6. Haldorsen H., and Chang D. Notes on stochastic shales: from outcrop to simulation model. In: Lake L., and Caroll H. (Eds). Reservoir Characterization (1986), Academic Press, London 445-485
7. Jones, T., Larue, D., 1997. Object-based modeling and deepwater depositional systems. in: Pawlowsky-Glahn (Ed.), Proceedings of International Association of Mathematical Geology, pp. 438-443.
8. Mackey S., and Bridge J. A revised fortran program to simulate alluvial stratigraphy. Computers & Geosciences 18 2 (1992) 119-181
9. Pyrcz, M., Strebelle, S., 2006. Event-based geostatistical modeling of deepwater system. In: Reservoir Characterization: Integrating Technology and Business Practices: Gulf Coast Section-SEPM 26th Annual Research Conference, Houston, TX, pp. 893-922.
10. Pyrcz M., Boisvert J., and Deutsch C. A library of training images for fluvial and deepwater reservoirs and associated code. Computers & Geosciences 34 (2008) 542-560
11. Remy, N., 2004. The stanford geostatistical earth modeling software (sgems): a tool for new algorithm development. In: Proceedings of the 7th Annual Geostatistics Congress, Banff, Alberta, Canada, pp. 865-871.
12. Shmaryan, L., Deutsch, C., 1999. Object-based modeling of fluvial/deepwater reservoirs with fast data conditioning: methodology and case studies. In: SPE Annual Technical Conference and Exhibition, SPE Paper 56821. Houston, TX.
13. Strebelle S. Conditional simulation of complex geological structures using multiple-point statistics. Mathematical Geology 34 7 (2002) 1161-1168
14. Tetzlaff D.M., and Harbaugh J.W. Simulating Clastic Sedimentation (1989), Van Nostrand Rheinhold, New York 202pp
15. Zhang, T., 2006. Filter-based training pattern classification for spatial pattern simulation. Ph.D. Dissertation, Stanford University, Stanford, CA, 137pp.