Although the enargite is obvious, the white rock… less so. Using tools, such as hyperspectral can help resolve this for fundamentally better models.
Over the course of a project hundreds of thousands to millions of meters are collected, representing a significant financial investment. Core is the exploration industry’s greatest asset and core logging fundamentally underpins the entire mining value chain.
The History of Core Logging
Core logging is a labor-intensive process that requires geologists to “see” subtle mineralogical changes that may serve as important alteration vectors or indicative of metallurgical challenges. Core logging is often delegated to junior geologists, as well geologists tend to change over the course of a project. These factors contribute to the difficulties of standardizing core logging databases.
These databases are fundamentally flawed if companies are interested in mining their data; data collected during this process is typically hierarchical. Data is logged across many columns (not including observations and notes!) that is difficult to model and mine in advanced machine learning programs. This data is also reliant on pre-set logging codes developed during prior campaigns and may not allow for local variations, thus logs are generally subjective, non-quantitative and sparsely sampled.
Changing the Way The Mining Industry Collects Core Logging Data
One of the cornerstones of LKI Consulting is to improve core logging in the mining industry. Using data like geochemistry and hyperspectral data provides information that is objective, repeatable, quantitative, and scalable. This allows geologists to focus on “geology,” using their time more effectively to interpret the mineral system.
At LKI our objective is to use your geologist’s knowledge of the rocks and your geochemistry and hyperspectral data to help your geologists log with more certainty, ultimately creating better 3D models.
Through thoughtfully planned logging campaigns, the collection of the right geochemical packages and strategic application of hyperspectral technology, as well as other ancillary datasets, this can lead to the interpretation of core in a way that is fit for purpose for wholistic 3D models required by the modern mining value chain.
