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Geostatistics Template Library (GsTL) to implement its geostatistical routines, including: Kriging; Multi-variate kriging (co-kriging); Sequential Gaussian simulation; Sequential indicator simulation; Multi-variate sequential Gaussian and indicator simulation; Multiple-point statistics simulation. For news, tutorials, and an FAQ,
Jul 23, 2015
Jun 26, 2007 These notes provide a brief introduction to geostatistical data analysis with the S-GeMS software, which is available from sgems.sourceforge.net/. For Windows, you can download and automatic installer. The download also includes an S-GeMS manual, sgems_manual.pdf, that ends up in the folder C:
Feb 25, 2014
This short tutorial describes a SGeMS session in which ordinary kriging is performed on a 100 ? 130 ? 30 Cartesian grid. The data consist of a set of 400 points in 3-D space, with a rock porosity value associated to each data point. This point-set object is called porosity data. The steps involved are the following: 1. Load the
This document presents an extract of an upcoming book written by Nico- las Remy, Alexandre Boucher and Jianbing Wu. The book has 10 chapters detailing how to use the SGeMS software. SGeMS is a software for 3D geostatistical modeling. It implements many of the classical geostatistics algorithms, as well as new
SGeMS Software. 67. 5. Spatial Statistics. 85. 6. Transformations. 98. 7. Semivariogram. 108. 8. Simple Kriging. 127. 9. Ordinary Kriging. 155. 12.Cokriging. 225. 13.Crossvalidation. 240. 14.Critical Review. 254. 15.Sequential Gaussian. Simulation. 266. 16.Simulated Annealing 282. 17.Filter Simulation. 298. 18.Reliability.
SGeMs adalah salah satu software open source yang dapat dipergunakan untuk mengestimasi sebaran bahan galian berdasarkan data pemboran. by edi_setiawan_32 in Types > Instruction manuals, tutorial, and sgems.
See tutorial 1.1.2 for more details about the Command Panel. 1.1.2 A simple tutorial. This short tutorial describes a GEMS session in which ordinary kriging is performed on a 100 ? 130 ? 30 Cartesian grid. The data consist of a set of 400 points in 3-D space, with a rock porosity value associated to each data point.
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