Confronting uncertainty in model-based geostatistics using Markov Chain Monte Carlo simulation
نویسندگان
چکیده
a Faculty of Agriculture, Food & Natural Resources, The University of Sydney, NSW 2006, Australia b Department of Civil and Environmental Engineering, University of California, Irvine, 92697 CA, USA c Institute for Biodiversity and Ecosystem Dynamics (IBED), University of Amsterdam, Nieuwe Achtergracht 166, 1018 WV, Amsterdam, The Netherlands d Earth and Environmental Sciences Division, Los Alamos National Laboratory, Los Alamos, 87545 NM, USA
منابع مشابه
New Approaches in 3D Geomechanical Earth Modeling
In this paper two new approaches for building 3D Geomechanical Earth Model (GEM) were introduced. The first method is a hybrid of geostatistical estimators, Bayesian inference, Markov chain and Monte Carlo, which is called Model Based Geostatistics (MBG). It has utilized to achieve more accurate geomechanical model and condition the model and parameters of variogram. The second approach is the ...
متن کاملJoint Bayesian Stochastic Inversion of Well Logs and Seismic Data for Volumetric Uncertainty Analysis
Here in, an application of a new seismic inversion algorithm in one of Iran’s oilfields is described. Stochastic (geostatistical) seismic inversion, as a complementary method to deterministic inversion, is perceived as contribution combination of geostatistics and seismic inversion algorithm. This method integrates information from different data sources with different scales, as prior informat...
متن کاملDistribution network design under demand uncertainty using genetic algorithm and Monte Carlo simulation approach: a case study in pharmaceutical industry
Distribution network design as a strategic decision has long-term effect on tactical and operational supply chain management. In this research, the location-allocation problem is studied under demand uncertainty. The purposes of this study were to specify the optimal number and location of distribution centers and to determine the allocation of customer demands to distribution centers. The m...
متن کاملgeoR and geoRglm: Software for Model-Based Geostatistics
The packages geoR and geoRglm are contributed packages to the statistical software system R, implementing methods for model-based geostatistical data-analysis. In this paper we focus on the capabilities of the packages, the computational implementation and related issues, and indicate directions for future developments. geoR implements methods for Gaussian and transformed Gaussian models. The p...
متن کاملDistribution network design under demand uncertainty using genetic algorithm and Monte Carlo simulation approach: a case study in pharmaceutical industry
Distribution network design as a strategic decision has long-term effect on tactical and operational supply chain management. In this research, the location– allocation problem is studied under demand uncertainty. The purposes of this study were to specify the optimal number and location of distribution centers and to determine the allocation of customer demands to distribution centers. ...
متن کامل