Exploration battleships provided interesting feedback to your scribe last week.

In response to the “fun for all ages” exploration targeting game introduced in last week’s column, a number of colleagues expressed their frustration at the lack of available tools across our industry to more effectively target exploration drill programs in a rigorous manner.

Spurred into action, Strictly Boardroom this week worked closely with a mathematical engineering colleague, Jose Saavedra-Rosas, to throw some numbers at the problem.

However, rather than looking at regional exploration targeting like last week, this week we get down to the nitty gritty of drill spacing at a tightly defined prospect.

“Tightly defined” is always a relative term, of course.

Whereas last week the search area was some 50km by 100km, this week we’re down to just 600m by 600m. Surely we can’t miss?

Before you think that the job is done though, some numbers illustrate the difficulty of hitting small targets even within such a modest search area.

Here’s this week’s analogy: faced with a regolith-covered terrain in the Eastern Goldfields and a reasonable drill budget in an area of good gold host-rocks and structure, what drill pattern would you recommend for initial drill testing of the targeted area to pick up a regolith gold signature?

Let’s be hard on ourselves and suggest that the target is a mere 50m by 50m horizontal plate at the base of the regolith.

Would you favour laser-like reverse circulation drilling of structurally defined targets?

What about grid-based aircore first perhaps?

If the latter is your preference, then what grid spacing do you recommend?

The maths behind such a conundrum is not difficult to solve – and in fact was solved long ago for ellipsoid targets by the Russians way back during the Space Race – but the exploration industry has yet to widely adopt that methodology.

Part of determining an answer is to look at the statistical likelihood of hitting the said geometric target.

Here are some quick results.

If you chose a broad 400m by 80m drill-pattern then your chances of getting a hit would be under 8% (based upon iterative sampling of computer-generated drill-grid patterns of those dimensions covering the entire search area).

Those that opted for 320m by 160m would be looking at a statistical result below 5%.

Those selecting 320m by 80m would hit roughly one time in 10, so 10% – whereas an 80m by 80m grid raises the statistical likelihood to around 40%.

Those explorers with a preference to use fence-lines and existing tracks for easy access pay a statistical penalty for doing so – with random drill-spacings performing below regular grids on average hit-miss rate for an equivalent number of drill tests.

None of the above bode too well for confidence in hitting the target.

Of course those willing to commit to a 50m by 50m grid-spacing will always hit their target by definition – so that selection yields 100% success but at the cost of more drill metres.

Critically, the grid spacing does not need to widen much in order to lower one’s probability of success materially, however.

At just a 55m by 55m grid, the probability of a successful drill hit has already declined to just 83%.

Would you change your drill pattern armed with the above statistical information?

At the least you are now better informed and have an extra decision-making tool at your disposal.

Of course this example is over-simplistic – but such tools can be made far more sophisticated to estimate outcomes for other geological analogies.

It depends whether your target more closely resembles a rectangle (in areas of known strike/structure), a cylinder, an inclined, plunging pipe, or perhaps an ellipse – you name it.

So why have we not advanced towards the use of such tools over the last 50 years?

Your feedback would be welcomed to answer that conundrum.

In order to lift the cost efficiency of exploration drilling – and more critically improve the discovery rate when testing new target areas, we first need to accept that the industry has a problem.

So do we?

Good hunting.

Allan Trench is a Professor at Curtin Graduate School of Business and Professor (Value & Risk) at the Centre for Exploration Targeting, University of Western Australia, a non-executive director of several resource sector companies - and the Perth representative for CRU Strategies, a division of independent metals & mining advisory CRU group (allan.trench@crugroup.com).

Jose Saavedra-Rosas is a mathematical engineer at the Department of Mineral & Energy Economics and senior lecturer at the Curtin Graduate School of Business and also senior research fellow at the Centre for Exploration Targeting, University of Western Australia. (J.Saavedra-Rosas@curtin.edu.au)