Geological modeling by an indicator kriging approach applied to a limestone deposit in Indiara city - Goiás

Abstract

The mineral exploration activity consists of a set of successive stages that are interdependent on each other, in which the main goal is to discover and subsequently evaluate a mineral deposit for the feasibility of its extraction. This process involves setting the shape, dimensions and grades for eventual production. Geological modeling determines the orebody's possible format in subsoil, which can be done by two approaches: vertical sections (deterministic methods) or geostatistical methods. The latter approach is currently being preferred, as it is a more accurate alternative and therefore, more reliable for establishing the physical format of orebodies, especially in instances where geologic boundaries are soft and/or with widely spaced sample information. This study uses the concept of indicator kriging (IK) to model the geologic boundaries of a limestone deposit located at Indiara city, Goiás State, Brazil. In general, the results indicated a good adherence in relation to samples. However, there are reasonable differences, particularly in lithological domains with a small number of samples in relation to the total amount sampled. Therefore, the results showed that there is a need for additional sampling to better delineate the geological contacts, especially between carbonate and non-carbonate rocks. Uncertainty maps confirmed this necessity and also indicated potential sites for future sampling; information that would not be obtained by usage of deterministic methods.

SGS method applied to damage location and uncertainty modeling for sensor grid in the ISHM

“…Geostatistics had its roots as an application of Georges Matheron's Theory of Regionalized Variables [25][26][27][28] and was first developed to address geological and mining engineering problems, and is widely used in these fields [29][30][31][32]. By gathering a finite number of samples, geostatistical methods are employed to create geological models by interpolating the sample values.…”

Modelagem implícita para detalhamento do Modelo Conceitual Temporal de Área Complexa com remediação de Plumas Combinadas na Região Metropolitana de São Paulo

“…Já a modelagem implícita é feita de forma automatizada, partindo de informações de posicionamento geográfico e de rápidas interpolações, podendo contemplar campanhas sucessivas de resultados. Vários algoritmos de modelagem implícita têm sido aplicados nas geociências, tais como Radial Basis Function (RBF), Inverso da Distância e Krigagem (Vollgger et al, 2015;Pereira et al, 2017).…”

The application of GIS in visualization of geotechnical data (SPT-Soil Properties): a case study in Eskisehir-Tepebaşı, Turkey

“…The interpolation effect of the GIK method shows that the distribution of the parameter is random. With GIK, a default grid is created (with a userspecified fineness) and this grid can be (and is in this case) defined between two geologic surfaces (e.g., ground surface and the bottom of gravel) (Pereira et al 2017). On the other hand, variables such as SPT-N values, porosity, hydraulic conductivity coefficients of units, pollutant concentration are modeled by continuous variable algorithms such as 3D kriging (Rockworks 2010) (Fig.…”