Resource Modeling Solutions

Providing expert knowledge, software, and services in support of mining and petroleum companies.

Composites with shells


The Resource Modeling Solutions Platform is an easy to use Python library wrapping a high performance engine for modern geostatistics. Build auditable resource modeling workflows quickly using the latest in proven geostatistical algorithms.

The Resource Modeling Solutions Drill Hole Optimizer (DHO) is an optimization program that optimizes infill drilling plans to maximize return on investment. DHO takes practical site access and budget constraints supplied by mine geologists and engineers to plan optimized infill drill holes to convert resource to measured and indicated.

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Resource Modeling Solutions consults on geostatistics and geometallurgy challenges delivering custom solutions including expert technical work, custom software, and training solutions. Get in touch so we can discuss your project needs. The Resource Modeling Solutions Team are actively engaged in providing technical assistance and undertaking routine and advanced resource modeling. Extensive experience is available to address Mineral Resource Estimation and Reservoir Modeling challenges.

We consult on probabilistic resource modeling, risk management of mine tailings, prediction and optimization of mill performance with machine learning, micromodeling of formation image logs, automated modeling systems for tactical decision making, infill drill hole optimization, and high resolution ore control models among other areas in geostatistics and geometallurgy.

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Uncertainty in mill feed.
Gaussian Mixture Model Scatterplot


Resource Modeling Solutions offers training classes and workshops on introductory and advanced topics in geostatistics and geometallurgy. Teaching intensive short courses to industry has been an important part of the Team’s activities for many years. Many courses are actively taught internally for organizations and publicly. Subjects range from Fundamentals of Geostatistics to Advanced Multivariate Geostatistics in addition to mining, geometallurgy, and petroleum specific classes.

Public online classes on the Fundamentals of Geostatistics and Advanced Geostatistics were offered in May 2020. Sign up for our mailing list below to be notified of future course opportunities.

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Blog - 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. The Gaussian distribution is the correct limit distribution based on combinatorics or additive processes (like the sum of the numbers showing on three dice); however, the multivariate Gaussian distribution infects non-Gaussian variables by appropriate transformation. The properties of the multivariate Gaussian distribution are recalled and the clever adaptations to geostatistics are discussed.

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Dice and the Gaussian distribution
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We deliver solutions to resource modeling challenges in the mining, energy, and environmental sectors. Our solutions are custom designed to deliver expert technical work, software, and training. Find a solution for your resource modeling challenge.