This book provides a practical perspective of all the processes involved in estimating mineral resources and reserves, including mine-to-mill reconciliation. It provides an integrated step-by-step explanation of processes for performing each step, including insight from academic and industry practitioners. Each chapter details a specific aspect of the estimation processes in a practical manner. It contains examples and case studies to illustrate the practical application of geostatistics in mineral resource estimation, mineral reserve conversion, and reconciliation. Features Provides a step-by-step guide with over 10,000 lines of Python code for hands-on demonstration, from start to finish, for both linear and non-linear geostatistical methods. Explains practical geostatistics processes and functionality. Simplifies explanation of mathematical /statistical concepts and application. Discusses generalised examples to aid the process steps. Reviews processes involved in the mineral resources’ estimation and ore reserve conversion. This book is intended for third-year and postgraduate students in Mineral Resources Management, Geology, Spatial Statistics, and Mining Engineering, as well as practising professionals.

This book provides a practical perspective of all the processes involved in estimating mineral resources and reserves, including mine-to-mill reconciliation. It provides an integrated step-by-step explanation of processes for performing each step, including insight from academic and industry practitioners. Each chapter details a specific aspect of the estimation processes in a practical manner. It contains examples and case studies to illustrate the practical application of geostatistics in mineral resource estimation, mineral reserve conversion, and reconciliation. Features Provides a step-by-step guide with over 10,000 lines of Python code for hands-on demonstration, from start to finish, for both linear and non-linear geostatistical methods. Explains practical geostatistics processes and functionality. Simplifies explanation of mathematical /statistical concepts and application. Discusses generalised examples to aid the process steps. Reviews processes involved in the mineral resources' estimation and ore reserve conversion. This book is intended for third-year and postgraduate students in Mineral Resources Management, Geology, Spatial Statistics, and Mining Engineering, as well as practising professionals.

This brief will provide a bridge in succinct form between the geostatistics textbooks and the computer manuals for `push-button' practice. It is becoming increasingly important for practitioners, especially neophytes, to understand what underlies modern geostatistics and the currently available software so that they can choose sensibly and draw correct conclusions from their analysis and mapping. The brief will contain some theory, but only that needed for practitioners to understand the essential steps in analyses. It will guide readers sequentially through the stages of properly designed sampling, exploratory data analysis, variography (computing the variogram and modelling it), followed by ordinary kriging and finally mapping kriged estimates and their errors. There will be short section on trend and universal kriging. Other types of kriging will be mentioned so that readers can delve further in the substantive literature to tackle more complex tasks.

The Stanford Geostatistical Modeling Software (SGeMS) is an open-source computer package for solving problems involving spatially related variables. It provides geostatistics practitioners with a user-friendly interface, an interactive 3-D visualization, and a wide selection of algorithms. This practical book provides a step-by-step guide to using SGeMS algorithms. It explains the underlying theory, demonstrates their implementation, discusses their potential limitations, and helps the user make an informed decision about the choice of one algorithm over another. Users can complete complex tasks using the embedded scripting language, and new algorithms can be developed and integrated through the SGeMS plug-in mechanism. SGeMS was the first software to provide algorithms for multiple-point statistics, and the book presents a discussion of the corresponding theory and applications. Incorporating the full SGeMS software (now available from www.cambridge.org/9781107403246), this book is a useful user-guide for Earth Science graduates and researchers, as well as practitioners of environmental mining and petroleum engineering.

This text provides an advanced introduction to the theory and applications of geostatistics, including tools for description, modeling spatial continuity, spatial prediction, assessment of local uncertainty, and stochastic simulation.

Geostatistics for Engineers and Earth Scientists