Author: Mike O’Brien, Senior Principal Consultant, P.Geo., Pr.Sci.Nat.
There are increasing numbers of effective tools in the mineral industry that enable professionals to do their jobs, better and quicker than ever before. Enablers, like Lidar, sonic drilling, portable XRF and implicit modelling are four of a flock of tools that have been unleashed over the last decade or two.
In the old days (sometimes that seems like only a couple of weeks ago), if a geology model was built in three dimensions, we were pretty satisfied if we felt the major lithology and alteration units had been approximated and were in the right province. A couple of grainy maps in the technical report with plenty of coloured lines and a scale bar and you’re done. Generally if it was a mine scale model, the level of complexity was rationalised on two grounds; ‘we don’t have enough detailed data’ or ‘we’ve mined that bit out, so fugeddaboudit’. Nowadays we are beguiled by not only having seemingly endless amounts of data but numerous tools that are going to ‘help us’. For example, we can be distracted into days of building hectares of sub millimetre topography thanks to the wonders of Lidar. Looks fantastic but is it useful?3D implicit modelling has been developed to a level of elaboration where faulting can be easily superimposed on 3D models to compartmentalise into fault-bounded blocks. These blocks can be generated using alternative relationships between blocks. Then it is a matter of choosing the most ‘realistic’ or ‘plausible’ result… Cool! Oh wow, can’t wait to start generating all those alternatives.
But, think about it; simplistically there are two alternatives that can apply when two faults interact with one another, A is younger than B, or B is younger than A (or there is no effect so A and/or B is not a fault). Fundamentally, if there are n faults there will be n! [factorial] ways that the fault sequence can be built. So if your project or your mine contains say eight major faults (not an outrageously large number of planar features) there are 40,320 possible alternative interpretations. Good luck with generating all these options and discarding the 40,319 less attractive answers. An extreme example, assuming there is no other information except for the geometry of the faults. In reality, outcrop patterns and the extents of downhole lithologies will certainly reduce the odds a little.
However, there is a magic answer. Instead of puzzling over a warm computer screen, how about you put your boots on and amble out to the coreshed or into the field and start picking up some real data; those relative age indicators that you’ve heard about and that people never seem to have time to sketch in their logs and field books? Just saying…. There are always exceptions, so I imagine most people who read this do this as a matter of course and are all over sequencing their faults and stratigraphy. Good for you guys!
For three decades Mike has been making a difference to Mineral Resources and mines. On the technical front, he has extensive experience in Mineral Resource estimation and geological modelling. He has managed technical teams to achieve results in mining companies and in consultancies. While the majority of his experience has been in gold deposits, he has expertise in the uranium, base metals and multi-product environment. A qualified geologist and geostatistician, he has been a team member and reviewer of due diligence and feasibility exercises in South Africa, Brazil, Ghana, Namibia, DRC, Russia, Kazakhstan, Uzbekistan, Colombia, Peru and the United States. Specialties: Mineral Resource estimation, geostatistics, Mineral Resource classification, Mineral Resource reporting codes, SAMREC, JORC.
March 2, 2016
Author: Mike O’Brien, Senior Principal Consultant, P.Geo., Pr.Sci.Nat.
There are increasing numbers of effective tools in the mineral industry that enable professionals to do their jobs, better and quicker than ever before. Enablers, like Lidar, sonic drilling, portable XRF and implicit modelling are four of a flock of tools that have been unleashed over the last decade or two.
In the old days (sometimes that seems like only a couple of weeks ago), if a geology model was built in three dimensions, we were pretty satisfied if we felt the major lithology and alteration units had been approximated and were in the right province. A couple of grainy maps in the technical report with plenty of coloured lines and a scale bar and you’re done. Generally if it was a mine scale model, the level of complexity was rationalised on two grounds; ‘we don’t have enough detailed data’ or ‘we’ve mined that bit out, so fugeddaboudit’. Nowadays we are beguiled by not only having seemingly endless amounts of data but numerous tools that are going to ‘help us’. For example, we can be distracted into days of building hectares of sub millimetre topography thanks to the wonders of Lidar. Looks fantastic but is it useful? 3D implicit modelling has been developed to a level of elaboration where faulting can be easily superimposed on 3D models to compartmentalise into fault-bounded blocks. These blocks can be generated using alternative relationships between blocks. Then it is a matter of choosing the most ‘realistic’ or ‘plausible’ result… Cool! Oh wow, can’t wait to start generating all those alternatives.
But, think about it; simplistically there are two alternatives that can apply when two faults interact with one another, A is younger than B, or B is younger than A (or there is no effect so A and/or B is not a fault). Fundamentally, if there are n faults there will be n! [factorial] ways that the fault sequence can be built. So if your project or your mine contains say eight major faults (not an outrageously large number of planar features) there are 40,320 possible alternative interpretations. Good luck with generating all these options and discarding the 40,319 less attractive answers. An extreme example, assuming there is no other information except for the geometry of the faults. In reality, outcrop patterns and the extents of downhole lithologies will certainly reduce the odds a little.
However, there is a magic answer. Instead of puzzling over a warm computer screen, how about you put your boots on and amble out to the coreshed or into the field and start picking up some real data; those relative age indicators that you’ve heard about and that people never seem to have time to sketch in their logs and field books? Just saying…. There are always exceptions, so I imagine most people who read this do this as a matter of course and are all over sequencing their faults and stratigraphy. Good for you guys!
About Mike O’Brien
Senior Principal Consultant, P.Geo., Pr.Sci.Nat. ARANZ Geo Limited – Expert Services (formerly QG Consulting)
For three decades Mike has been making a difference to Mineral Resources and mines. On the technical front, he has extensive experience in Mineral Resource estimation and geological modelling. He has managed technical teams to achieve results in mining companies and in consultancies. While the majority of his experience has been in gold deposits, he has expertise in the uranium, base metals and multi-product environment. A qualified geologist and geostatistician, he has been a team member and reviewer of due diligence and feasibility exercises in South Africa, Brazil, Ghana, Namibia, DRC, Russia, Kazakhstan, Uzbekistan, Colombia, Peru and the United States. Specialties: Mineral Resource estimation, geostatistics, Mineral Resource classification, Mineral Resource reporting codes, SAMREC, JORC.
This article on LinkedIn: 👍Like 54 | Comment 12
Share this:
Like this: