Titlebook: Geostatistics with Data of Different Support Applied to Mining Engineering; Marcel Antonio Arcari Bassani,Jo?o Felipe Coimbra Book 2022 T

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Geostatistics with Data of Different Support Applied to Mining Engineering978-3-030-80193-9Series ISSN 2364-3293 Series E-ISSN 2364-3307

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https://doi.org/10.1007/978-3-322-96228-7erm used in Geostatistics to describe the size or volume of a sample. For example, suppose a grade sample obtained from diamond drill holes (DDH). In this case, the support is a function of the core’s radius and length.

盤旋

,Kapazit?ts- und Teilbarkeitsbeschr?nkungen,ack refers to a volume/support much larger than a sample that represents the average grade along one meter of a diamond drill hole. This difference in support must be considered if these two sources of information are used to build grade models.

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Entscheidungskriterien für Gl?ubiger Best because the estimate minimizes the variance of the estimation error. However, when several estimated locations are considered together, such as an estimated grade model, the estimates do not represent the true spatial variability of the modeled variable. The map of the estimates has less varia

Emmenagogue

Relatives Denken bei Wahrscheinlichkeitensupport is a challenge when the samples have completely different supports. The goal of this chapter is to show how to change the support of the variogram. Changing the support of the variogram means that we can obtain a variogram at block support starting from a variogram at point support and vice-

Precursor

https://doi.org/10.1007/978-3-642-52175-1aset was used by Bassani and Costa (Bassani MAA, Coimbra Leite Costa JF (2016) Grade estimation with samples of different length. Appl Earth Sci 125(4):202–207). The original Z coordinates were converted into stratigraphic coordinates. The stratigraphic coordinate is the Z coordinate of the sample‘s

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Zusammenfassung und Diskussion, Direct Sequential Simulation (DSS) to integrate data of different support in a mining context. The result is a series of equally probable grade models that may be directly applied for stochastic mine planning. Also, these grade models provide a measure of uncertainty. The chapter highlights some pr

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CORE

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