GeoSim: An R-package for plurigaussian simulation and Co-simulation between categorical and continuous variables

IF 2.6 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
George Valakas, Konstantinos Modis
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引用次数: 0

Abstract

Plurigaussian simulation is widely used to model geological facies in geosciences and is predominantly applied in mineral deposits and petroleum reservoirs exploration. GeoSim package builds geostatistical models of categorical regionalized variables via conditional or unconditional Plurigaussian simulation and co-simulation. Co-simulation between Gaussian Random Fields representing the geological facies and other numerical variables accounting for auxiliary hydrological or geophysical quantities, is also available in this package with the definition of a linear coregionalization model. The algorithm is not restricted by the number of simulated facies and the number of truncated Gaussians, while parts of the code requiring heavy computations are compiled in C++ taking benefits of the integration between R and C++. In this work, we introduce the GeoSim package and demonstrate its capabilities. We present a 3D application focused on a lignite mine in Greece, where we investigate the Plurigaussian simulation and co-simulation of five geological facies (categorical variables) and the lower calorific value (continuous variable). The findings of our study highlight the significant benefits of Plurigaussian and co-simulation to capture the geological spatial heterogeneity.

GeoSim:一个用于多高斯模拟和分类变量与连续变量之间的联合模拟的r包
Plurigussian模拟在地学中被广泛用于地质相建模,主要应用于矿床和油气藏勘探。GeoSim软件包通过有条件或无条件的Plurigussian模拟和联合模拟建立分类区域化变量的地质统计模型。代表地质相的高斯随机场和考虑辅助水文或地球物理量的其他数值变量之间的联合模拟也可在该软件包中使用,并定义了线性共区域化模型。该算法不受模拟相的数量和截断高斯数的限制,而需要大量计算的部分代码是利用R和C++之间的集成在C++中编译的。在这项工作中,我们介绍了GeoSim软件包,并展示了它的功能。我们介绍了一个以希腊褐煤矿为重点的3D应用程序,在该应用程序中,我们研究了五个地质相(分类变量)和低热值(连续变量)的Plurigussian模拟和联合模拟。我们的研究结果突出了Plurigaussian和联合模拟在捕捉地质空间异质性方面的显著优势。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Applied Computing and Geosciences
Applied Computing and Geosciences Computer Science-General Computer Science
CiteScore
5.50
自引率
0.00%
发文量
23
审稿时长
5 weeks
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