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.
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.
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.
Resource Modeling Solutions in partnership with the Centre for Computational Geostatistics are offering a series of 14 short course modules to be streamed online in 2022. Modules are available on subjects ranging from an Introduction to Geostatistical Modeling to Practical Techniques for Machine Learning Applied to Geometallurgical Data were presented.
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Blog - To Impute or not to Impute
To impute is to put upon something or someone without their acceptance and, perhaps, without just cause. I always think about the trailer on many emails I receive: If you have received this message in error,… The sender imputes responsibility on the recipient without asking for or gaining acceptance. In statistics and, increasingly, geostatistics we use impute or imputation to describe the process of assigning values where values are missing in a set of data. The main advantage of this methodology is to facilitate techniques that require a full valued data table such as principal component analysis (PCA) or projection pursuit multivariate transformation (PPMT). This can be convenient; however, no technique should be used without due care and discrimination. There are alternatives to imputation. This brings the question about whether to impute or not to impute...
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.