Mineral Resource Estimation

The estimation of mineral resources is an important task for geoscientists and mining engineers. The approaches to this challenge have evolved over the last 40 years. This book presents an overview of established current practice. The book is intended for advanced undergraduate students or professionals just starting out in resource estimation. 1.1 Objectives and Approach Our objective is to explain important issues, describe commonly used geological and statistical tools for resource modeling, present case studies that illustrate important concepts, and summarize good resource estimation practice. Wherever possible a common thread will be maintained through the sections including details of theory and references to appendices and other authors, relevant examples, software tools available, required documentation trail for better practice, extensions to handling multiple variables, modeling of other less common variables such as metallurgical properties, and limitations and weaknesses of the assumptions and models used. There are a wide variety of minerals of interest including industrial minerals such as gravel and potash, base metals such as copper and nickel, and precious metals such as gold and platinum. There are other spatially distributed geological variables such as coal, diamonds, and variables used to characterize petroleum reservoirs. Often, the constituent of interest has variable concentration within the subsurface. A resource is the tonnage and grade of the subsurface material of interest. The resource is in-situ and may not be economic to extract. A reserve is that fraction of a resource that is demonstrated to be technically and economically recoverable. Estimation of resources and reserves requires the construction of long-term models (life of asset) for the entire deposit, which are updated every 1–3 years of operation. Medium-term models may be built for planning one to 6 months into the future. Short-term models are built for weekly or day-to-day decisions related to grade control or detailed planning. Constructing numerical models for long, medium or short-term resource assessment includes four major areas of work: 1. Data collection and management; 2. Geologic interpretation and modeling; 3. Grades assignment; and, 4. Assessing and managing geologic and grade uncertainty. Data collection and management involves a large number of steps and issues. There are books on drilling and sampling theory, such as Peters (1978) and Gy (1982). The richness and complexity of these subjects cannot be covered in detail; nevertheless, it is important that the resource estimator consider subjects that affect the quality of the ultimate estimates. Some background information is provided. Geologic interpretation and modeling requires that site specific geologic concepts and models are integrated with actual data to construct a three dimensional model of geological domains. This geologic model is a representation of those variables that control the mineralization the most and forms the basis for all subsequent estimation. Often, the geological model is the most important factor in the estimation of mineralized tonnage. The concentrations of different elements or minerals (grades) are assigned within geological domains. The grades within the different domains may be reasonably homogeneous; however, there is always some variability within the domains. The grades are predicted at a scale relevant for the anticipated mining method. The recoverable resources are calculated considering a set of economic and technical criteria. There are a wide variety of methods available and many implementation aspects must be considered. The chosen method will M. E. Rossi, C. V. Deutsch, Mineral Resource Estimation, DOI 10.1007/978-1-4020-5717-5_1, © Springer Science+Business Media Dordrecht 2014