Geology is, at its heart, a science rooted in observation. A competent geologist studying a rock first takes careful notes on their observations (minerals, textures, alteration, etc.) and then uses them to make inferences and interpretations on the processes that have formed and modified that rock. In core logging, the distinction between observation and interpretation is often blurred in the interest of saving time. Geologists have to work quickly in the core shack, and with limited access to data they have to rely on judgment calls and heuristics to create their logs. This means that two geologists logging the same core inevitably end up with different results.
Same observations, but codified differently
The scale of the problem is amplified by the fact that the many permutations for rock nomenclature can result in the same observations being codified differently, which is why some projects end up having thousands of lith codes and require expensive consultants to come in to sort through the mess.
Core logs are the base inputs in 3D models, in designing mine plans, and are used in making important decisions, such as which intervals to send for assay. The people who use the core logs for these tasks are blindly relying upon observations and interpretations made by someone else. Wouldn’t it be useful for them to have easy access to high-quality photos of the core beside the core log, beside their assay results, and even inside their 3D models?
Are you making the most of your drill core photos?
In both mining and exploration, photographs are regularly captured:
- in the field,
- in the core shack,
- from drones,
- around open pits,
- and underground.
For some it is a form of insurance and for others just a part of the prescribed procedures… but how often is this imagery used as part of a regular workflow? And when it is, how often is its utility hindered by poor image quality, inconsistent lighting conditions, out of focus regions of interest, etc.?
Core imagery should be part of a regular workflow, especially NOW
Imagery should be captured as part of a regular core logging workflow and delivered in a way that makes it useful to the dynamic teams that characterize modern mining and exploration companies. The importance of doing so NOW is paramount as advances in the use of Artificial Intelligence for image analysis and classification will allow those who are prepared to extract tremendous value from their image data at very low cost.
The vision behind Imago‘s ‘Rig to Model’ workflow is to make it as easy as possible to capture high-quality, consistent photos, and to enable anyone on your team to make use of this imagery within a user-defined context that is relevant to the task at hand: from QAQC, to sampling, to building better 3D models.