Горная геология является специализированной областью прикладных геологических наук, которая исторически развивалась как поддержка эксплуатации рудников и оценки горных проектов. Основной задачей горной геологии является предоставление подробной геологической информации, а также проведение техникоэкономических исследований для оценки проекта горных работ. Когда начинается добыча, горные геологи обеспечивают геологическое сопровождение работы, обеспечивая экономически эффективную добычу ценных минералов и их точное отделение от пустых пород.

Subsurface fluid flow is critically dependent on the 3D distribution of petrophysical properties in rocks. In sequences of sedimentary rocks these properties are strongly influenced by lithology and facies distribution that stem from the geologic processes that generated them.

The natural resources on the earth seem to be randomly distributed but their variations over space and time are not all random. They exhibit a spatial correlation. This spatial correlation can be captured by geostatistics. Geostatistics deals with the analysis and modelling of geo-referenced data. The point observations are analyzed and interpolated to create spatial maps. For geostatistical interpolation, first the spatial correlation structures of the parameter of interest are quantified and then spatial interpolation is done using the quantified spatial correlation and optimal predictions at unobserved locations to create a map.

Пространство, структура и случайность. Вклад в честь Джорджа Матерона в области геостатистики, случайных множеств и математической морфологии

Personal Reminiscences of Georges Matheron Dietrich Stoyan
A few words about Georges Matheron (1930-2000) Jean Serra
Introduction From the editors
Part I Geostatistics

Optimal interpolation based on regression against observed z values of surrounding data points, weighted according to spatial covariance values. <...>

Accurate recoverable resource estimation and grade control procedures are the foundation of successful mining ventures. Long, medium and short term planning in a mining operation are all dependent upon precise estimations. For example, poor estimation may result in the long term in a pit being incorrectly optimised, in the medium term cashflow forecasts may be disastrously inaccurate, and in the short term the allocation of ore and waste material by grade control may be erroneous.

In this introductory chapter we describe general problems of spatial environmental data analysis, modeling, validation and visualization. Many of these problems are considered in detail in the following chapters using geostatistical models, machine learning algorithms (MLA) of neural networks and Support Vector Machines, and the Bayesian Maximum Entropy (BME) approach. The term “mapping” in the book is considered not only as an interpolation in two- or threedimensional geographical space, but in a more general sense of estimating the desired dependencies from empirical data.

Effectiveness of ore grade control at operating mines depends on both the quality and quantity of the samples used. Therefore, optimisation of grade control procedures requires analysis of sample quality and their spatial distribution. This approach, implying quantitative estimation of both these factors and quantification of their contribution to the grade control errors, was used for comparing two different grade control procedures at the Yandicoogina (Yandi) iron-ore open pit mine, located in the eastern part of the Pilbara region of Western Australia. At Yandi, pisolitic iron oxide mineralisation is distributed within a meandering palaeoriver channel, characterised by abundant clay pods that contain the deleterious components; in particular Al2O3 and SiO2.

В учебнике описаны математические методы решения промыслово-геологических задач при разработке нефти и газа, прежде всего оценки неоднородности продуктивного пласта и моделирования пространственного распространения неоднородностей