What's the best way to sample and analyze a mining project?

1 Sampling methods

When collecting samples from a mining project, there are various methods to choose from, depending on the type, shape and depth of the ore body, the available equipment and the budget. Drilling is one of the most common methods; it involves using a drill rig to bore holes into the ore body and extract cylindrical cores of rock for analysis. Alternatively, trenching involves digging trenches across or along the ore body's strike and collecting samples from the exposed rock faces or excavated material. Channel sampling requires cutting channels or grooves into the rock surface and collecting samples from the resulting slabs of rock, while grab sampling involves randomly or selectively picking up pieces of rock from the surface or piles of material. Each method has its own advantages and drawbacks, so it is important to choose the most appropriate one for your project.

2 Sampling design

Designing a sampling program for a mining project involves considering various factors, such as sampling density, size, and orientation. Sampling density should be high enough to capture the variability of the mineralization, yet not too high to waste resources. Sampling size should be large enough to ensure that the sample is representative of the ore body, but not too large for handling and transport. Additionally, sampling orientation should be perpendicular to the ore body's main axis or plane in order to avoid biasing the grade and thickness measurements. These decisions can depend on the scope and scale of the project, geological characteristics of the ore body, type of sampling method used, grain size and distribution of minerals, analytical techniques used, topography of the site, and access and safety conditions.

3 Sampling quality control

The quality control of a sampling program involves ensuring that the samples collected are accurate, precise, and reliable, and that they reflect the true characteristics of the ore body. To achieve this, there are several measures that should be implemented in a sampling program. These include sampling protocols, which should be consistent, clear, and documented to minimize potential sources of error or contamination. Sampling duplicates should also be collected at regular intervals or randomly throughout the sampling program, to check the reproducibility and variability of the sampling method. Furthermore, sampling standards of known grade and quality should be inserted into the sample stream to check the accuracy and performance of the analytical method. Lastly, sampling blanks of zero or negligible grade should be inserted before and after each batch of samples to check for contamination or cross-contamination of the samples or the analytical method.

5 Data analysis

Data analysis of a mining project requires processing, interpreting, and reporting the results of sampling and analytical methods, and using them to estimate and classify the mineral resource. To ensure accuracy, data validation is done using spreadsheets, databases, or statistical packages. Data visualization is then done using GIS, CAD, or 3D modeling to display and explore the data and identify patterns, trends, or anomalies. Mathematical or statistical methods are then used to create models or equations that describe the relationships between variables, which are used for data estimation to estimate grade, tonnage, and quality of the mineral resource. Finally, data reporting summarizes and presents the data and estimates in a clear format that follows standards and guidelines of relevant codes or regulations; this can be done using word processors, tables, or charts.