Abstract:
GEMS, the Geostatistical Earth Modeling Software, is an example of software built from scratch using the GsTL. The source code of GEMS serves as an example of how to use GsTL facilities.
GEMS was designed with two aims in mind. The first one, geared toward the enduser, is to provide a user-friendly software which offers a large range of geostatistics tools: the most common geostatistics ... algorithms are implemented, in addition to more recent developments such as multiple-point statistics simulation. The user-friendliness of GEMS mainly comes from its non-obtrusive graphical user interface, and the possibility to directly visualize data sets and results in a full 3-D interactive environment. The second objective was to design a software whose functionalities could conveniently be augmented. New features can be added into GEMS through a system of plug-ins, i.e. pieces of software which can not be run by themselves but complement a main software. In GEMS, plug-ins can be used to add new (geostatistics) tools, add new grid data structures (faulted stratigraphic grids for example) or define new import/export filters.
TYLER
B.
STEVENS Role:
SERF AUTHOR
Phone:
(301) 614-6898
Fax:
301-614-5268
Email:
Tyler.B.Stevens at nasa.gov
Contact Address:
NASA Goddard Space Flight Center
Global Change Master Directory City:
Greenbelt
Province or State:
MD
Postal Code:
20771
Country:
USA
ANDRE
G.
JOURNEL Role:
TECHNICAL CONTACT
Phone:
(650) 723-1594
Fax:
(650) 725-2099
Email:
journel at pangea.stanford.edu
Contact Address:
Department of Petroleum Engineering
Stanford University City:
Stanford
Province or State:
CA
Postal Code:
94305
Country:
USA
Publications/References
Almeida, A. and Journel, A.: 1994, Joint simulation of multiple variables with a markovtype coregionalization model, Mathematical Geology 26(5), 565-588.
Chiles, J. and Delfiner, P.: 1999, Geostatistics: Modeling spatial uncertainty, John Wiley & Sons, New York.
Deutsch, C. and Journel, A.: 1992, GSLIB: Geostatistical Software Library and User's Guide, ... Oxford University Press, New York.
Goovaerts, P.: 1994, Comparative performance of indicator algorithms for modeling conditional probability distribution functions, Mathematical Geology 26, 389-411.
Goovaerts, P.: 1997a, Geostatistics for natural resources evaluation, Oxford University Press, New York.
Goovaerts, P.: 1997b, Geostatistics for natural resources evaluation, Oxford University Press, New York.
Holden, L., Hauge, R., Skare, O. and Skorstad, A.: 1998, Modeling of fluvial reservoirs with object models, Mathematical Geology 30(5), 473-496.
Journel, A.: 2002, Combining knowledge from diverse sources: An alternative to traditional data independence hypotheses, Mathematical Geology 34(5), 573-596.
Mao, S. and Journel, A.: 1999, Generation of a reference petrophysical/seismic data set: the stanford v reservoir, Report 12, Stanford Center for Reservoir Forecasting, Stanford, CA.
Strebelle, S.: 2000, Sequential simulation drawing structures from training images, PhD thesis, Stanford University, Stanford, CA.
Tjelmeland, H.: 1996, Stochastic models in reservoir characterization and Markov random fields for compact objects, PhD thesis, Norwegian University of Science and Technology, Trondheim, Norway.
Tran, T.: 1994, Improving variogram reproduction on dense simulation grids, Computers and Geosciences 20(7), 1161-1168.
Zhu, H. and Journel, A.: 1993, Formatting and interpreting soft data: Stochastic imaging via the markov-bayes algorithm, 1, 1-12.
Creation and Review Dates
SERF Creation Date:
2005-04-21
SERF Last Revision Date:
2011-05-20
Links
