Articles tagged with gmm

Scenarios versus Parameter Uncertainty

Clayton Deutsch


An important goal of modern resource modeling is accurate and precise assessments of uncertainty for production volumes relevant for technical and economic decision making. Volumes of relevance often relate to weekly, monthly, quarterly or annual production. These volumes are large and, for the most part, short scale high-frequency variations cancel out. This explains why simulated realizations from a fixed modeling workflow with fixed parameters often understate uncertainty. Careful consideration of large scale geological uncertainty is required to provide realistic asessements of production uncertainty. There are alternatives to incorporate such larger scale uncertainty.


Trends in Geostatistics

Clayton Deutsch


A trend in geostatistics could be a general tendency in the direction industry is taking, such as towards automation. A trend in geostatistics is also a non-stationary or locally-varying mean in a regionalized variable, particularly for a continuous variable. This kind of trend is common and must be considered in probabilistic resource modeling; otherwise, high values are smeared into volumes they do not belong and low values dilute high valued volumes. Two questions arise: (1) how to model the trend? and (2) how to model with a trend?


The Gaussian Distribution in Geostatistics

Clayton Deutsch


Gaussian algorithms have infected virtually all corners of geostatistics: radial basis functions (RBF) for interpolation and implicit modeling, hierarchical truncated pluriGaussian (HTPG) for categorical variable modeling, detrending non-stationary variables with a Gaussian Mixture Model (GMM), projection pursuit multivariate transformation (PPMT) for multivariate modeling, and simulating regionalized variables based on turning bands, sequential or spectral algorithms...