Optimizing Data Collection from Project Development to Mining

CIM Montreal 2015
Jenni Pfeiffer (Kinross Gold Corporation)
Data collected in the core shack and through subsequent analytical analysis is the basis for all interpretation, modeling, and resource estimation downstream. The type and detail of data collected from drilling varies by project stage and deposit type. Often an inappropriate level or type of data are collected for the project stage/deposit type or logging information remains on paper, unusable for modeling, resulting in more funds having to spent later in the project to digitize these data to make it usable.

Understanding your digital logging strategy and optimizing it for the type of project will add value by collecting the key data essential for subsequent modeling. Likewise, understanding the overall genesis of the deposit and then selecting the correct analytical techniques and sampling strategy is crucial to the successful modeling of the deposit. Having an appropriate QA/QC program and chain-of-custody procedures in place is also critical to generating usable, value-adding data. Case examples will be presented which highlight the importance of optimizing drilling data collection for project development stage and type; data requirements evolve as the project moves towards and into operation. Software companies are constantly developing new digital data capturing, validation, and reporting tools which now recognize that data requirements in mining are considerably different from exploration, where most original logging software were focused. Using these tools can help to optimize the drilling and grade control data collection process.
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