So you want to dig a hole: how geologists use data to make decisions

Published in

Unearthed Community

6 min readMar 27, 2019

Written by Holly Bridgwater and Jesse Robertson, compiled by Yhana Lucas for the Explorer Challenge

Over the life of a project, exploration geologists collect a vast array of different datasets, all aimed at providing them with different information on rock characteristics. They use this information to assess an area of land for the potential to host economic quantities of the mineral or element they are looking for, like copper or gold. Economic mineral deposits are rare, and over time are becoming harder to find (all the easy ones have been found), so geologists are continuously looking for new data sources and techniques to give them an additional edge.

These datasets can feel a bit intimidating at times, as it may appear that you need an unattainable amount of specialist knowledge to interpret them. Here, we give an overview for those new to geology data — of some commonly collected datasets, how they are obtained, how geologists typically use them and what to watch out for.

The Exploration Lifecycle

Before we jump into the datasets, it’s useful to get a snapshot view of how exploration geologists approach looking for deposits. A really great infographic on mineral exploration is provided here by Visual Capitalist and Orix Geoscience. It’s a great place to get started to get a feel for the overall process.

A very worthwhile infographic — https://www.visualcapitalist.com/mineral-exploration-roadmap/

Planet Earth itself

If you’re totally totally new, here’s an exciting (we think) video on how earth was formed.

Everything You Need to Know About Planet Earth — Kurzgesagt

Okay, so onto the data.

Geological Reports

In Australia, exploration and mining companies have been required by the government to submit annual reports of their activities back into the 1970’s. In the last 15 years or so, they have also been required to submit all their datasets digitally, so you can imagine there is a wealth of knowledge in these historical exploration reports! The government have done their best to digitise most of this data, but geologists will always review the historical reports to look for extra clues that might have been missed!

The reports that companies have submitted, will relate to the land which they have been exploring over. Companies are granted a permit to explore over a specific area of land, which is called a tenement. Each report is associated with a tenement, or multiple tenement numbers.

Geophysics

As the name implies, geophysics is the study of physical properties of the earth. Ore bodies often (but frustratingly not always!) have distinctly different physical characteristics to the rocks around them. They may be more dense, more magnetic, more conductive or resistive. Geologists use a suite of different airborne and ground surveys to measure these characteristics both at surface and at depth. The needle in a haystack analogy is pretty applicable in this case, considering the very different physical properties of the needle and the hay.

Common geophysical surveys include; seismic, magnetics, radiometrics, gravity, IP (induced polarisation), resistivity, EM (electromagnetic induction) and magnetotellurics.

Geophysical surveys are carried out on a range of different scales. You’ll find merged Australia wide and state surveys at Geoscience Australia and the SARIG portal, and small scale surveys carried out over project areas.

When a geophysical survey is conducted, we are typically putting energy into the ground and recording the response. That response is caused by the distribution of physical properties in the rocks. What we really want to know though, is the physical properties that gave rise to the response, not the response itself. The process to get to that is called inversion, which is a mathematical process applied to the raw data based on prior knowledge about the region. Several methods effectively measure the same physical property but at different scales to trade off between the penetration and resolution of the method (generally speaking, longer wavelengths penetrate deeper in the earth but at lower resolution). In the various datasets you will notice you have access to a combination of the raw and inverted results, and gridded images of those inversions.

Remote Sensing

Remote Sensing as a general term refers to the acquisition of data without physically touching the object you are acquiring data from. In geology, this is largely satellite data, or data captured via airborne surveys. Although remote sensing would also include some of the geophysical surveys mentioned above, geologists are usually referring to a couple of types of data: Landsat (satellite imagery) and spectral data like ASTER that give us information about the earth’s surface, usually at a 10–50 metre resolution (for currently-available public data). Geologists frequently use spectral data to indicate what minerals are present on the surface and subsurface. Different minerals have distinct emission and reflection spectra. This type of data is most regularly used to identify alteration minerals around deposits, which may extend many 100’s of metres away from the deposit itself, but can also be used to provide predictive covariates for surface geochemical samples.

Surface Geochemistry and Geological Mapping

From the early phases of exploration geologists will often take field surface samples, from rocks or soils. Surface geochemistry results will indicate if anomalous levels of an element are present, be that the ore element itself or proxies/vectors. This is a fairly cheap and quick way to assess an area of land. Geological mapping often occurs in conjunction with surface geochemistry surveys. Geologists record their observations in the field to create geological maps which can be used to identify prospective features for mineralisation locations.

At many sites, the majority of the tenement is undercover, by this we mean that the older, prospective rock units are covered by more recent sediments. There is therefore little surface geochemistry or field mapping for these projects.

Drillhole Database

This is where you get to dig a hole!

Geologists often referring to drilling as the truth machine. It is the one surefire way to demonstrate if mineralisation is present under the surface, through collecting subsurface samples. Drilling is expensive, so geologists will only carry this out once they have used some of the techniques above to identify prospective areas.

Drillhole databases (DHDB) include all the information that was recorded about the samples collected and the drilling process including; chemical assays, geology logs, surveys and often much more.

For chemical assays, when drillhole samples are submitted to a laboratory for analysis, the geologist will select what elements they want to know the concentrations of and what analysis method they would like used. Different analysis methods have different limits of detection (the lowest concentration detectable) for different elements. This has also changed through time, so historic results will usually have higher detection limits than more modern results, where the detection limits have improved with new technologies and methods.

Assay results are almost never normalised for a project, so always look out for different analytical method codes and detection limits when you are comparing results. The is particularly obvious in gold exploration, where different methods may be used for surface sampling compared to drilling samples.

It’s also worth noting that drillholes rarely go as smoothly and straight as we’d like — you can read more about how coordinates are computed to allow for this here.

Want to have a crack at picking where to dig? Join the Explorer Challenge, main or Data Science stream.

What else?

We’ve just gone through the major dataset types — but this is absolutely not an exhaustive list.

To generate new insights, we encourage the use of other datasets that are commonly not used by geologists in their exploration programs.

Here’s a quick hitlist of public datasets to get started with: