MINING SOFTWARE
about breaking down operational and data silos and some spare cash thanks to an upturn in commodity prices , the industry requirements are vast and varied .
Modular Mining says it is being tasked – and is ready to deliver – a whole suite of optimisation solutions for mining companies . Miners are putting pressure on them to not only deliver data , but to make it “ relevant and actionable ”.
RPMGlobal says powerful simulation capabilities that miners can use for their own internal projects are often requested . A recent example of this is a solution to simulate electric vehicles with an aim to quantify different haulage options for an operation , Beesley explained .
“ We are working with industry partners ( OEMs and mine operators ) to ensure that we are able to model all options available in this shift towards a carbonneutral future ,” he said .
The company is also increasingly asked to come up with solutions that not only augment existing expertise within the mining company environment but fill in some industry skill gaps .
“ With a shortage of mining engineers in a lot of countries , together with limited capabilities in CADbased design products , RPMGlobal ’ s Strategic Design Optimiser tool combines the complex tasks of optimised stope and development design into a single , coherent automated process ,” Beesley said . “ SDO uses parametric design principles and optimisation algorithms that enables users to make small tweaks to designs in one area that lead to the change rippling through the rest of the design — a task that would otherwise take days because each edit would need to be done manually .”
Maptek ’ s Coloma says the company is continually seeking to understand the customer challenge first and then find the right technology or a better way to solve it with an expanding array of tools . This is where the development of sophisticated algorithms is helping it deliver higher-level optimisation and an integrated approach to areas such as mine scheduling .
This demand for enhanced optimisation tools has led to the development of Maptek ’ s BlastMCF solution , which , according to Coloma , optimises drill , charge and timing designs to suit site conditions and
Geostatistical simulations allow the quantification of grade variability and the exploration of various scenarios from many different resource estimation standpoints , according to Geovariances .
Yet , despite the inherent ability to tackle risk analysis , a series of factors have prevented simulations being incorporated into the mainstream chain of information processing prevalent in the sector , the applied geostatistics company says .
“ The main technical block to the widescale use of simulations has undoubtedly been performance : it still takes a length of time to produce simulation realisations in sufficient numbers to allow meaningful risk analysis to be performed . This problem is made worse when the size of the dataset increases .”
To get over this problem , the latest version of Geovariances ’ geostatistical software , Isatis . neo , introduced a high-performing simulation methodology , SPDE .
This approach , unique to Isatis . neo , addresses multiple issues users face today . It helps integrate more and more data , boost productivity and deduce an answer quickly , the company says .
“ At the same time , this outcome is enriched with an assessment of the uncertainty that can be attached to that answer ,” it added .
The tests conducted at Geovariances using Isatis . neo have shown users can obtain simulation realisations up to 50 times faster in 2D and three times faster in 3D than running the standard Turning Bands method . The key ingredient to allow that quantum leap in performance is the solving of Stochastic Partial Differential Equations , hence the name given to the new algorithm ( SPDE ).
This algorithm came from a two-year research consortium Geovariances conducted in partnership with the Center for Geostatistics from MINES ParisTech and major mining companies including Anglo American , BHP , Eramet , Kinross , Newcrest and Orano .
“ With Isatis . neo , it is also possible to extract a representative subset of simulations selected among a more extensive set to evaluate projects ,” the company said . “ Indeed , even if the production and post-processing of multiple simulation realisations are now more than ever a practical solution to many resource estimation problems , the ability to still focus on a few realisations remains very appealing to all practitioners .”
Machine-learning algorithms have been implemented into Isatis . neo to speed up processes and deal with even bigger datasets . An example is the Sample Clustering functionality , which is used to define geological domains . This is an essential step in the mineral resource modelling process , according to the company .
Alongside this , Geovariances , in late 2020 , launched a new research consortium to accommodate bigger datasets by “ putting geostatistics in the cloud ”.
A probability map of exceeding a grade cutoff derived from geostatistical simulations in Geovariance ’ s Isatis . neo
“ The aim is to speed up results and free users from computer limits regarding performance and storage capacity ,” the company said .
Geovariances is starting with the simulation functions , which will be provided as “ microservices ” or “ libraries ” to be recalled from Isatis . neo or companies ’ own in-house applications .
Another advantage is that users will be able to connect multiple software solutions in a cloud environment without the need for their interfaces , the company added .
Geovariances is additionally working on developing robust implicit geological domain modelling , with an alternative already available in Isatis . neo being the multiple-points statistics ( MPS ) methodology .
“ MPS allows modelling complex relationships between facies and geological body shapes ,” the company explained .
The principle is to mimic a reference image . This image can be an analogue if the geological environment is known or derived from knowledge of a previous mining area . From the facies model , it is easy to then derive the estimation domains , the company says .
Geovariances recently applied MPS for a senior gold mining company with the objective of the study to assess resources and quantify risk in planned extensions .
The work resulted in a realistic 3D facies model built with data from several hundred drill holes and constrained by specific geological features such as shear lenses .
“ Geovariances is striving to make these rather complex techniques accessible ,” the company said . “ It is what led us to develop Isatis . neo , a userfriendly software solution .”
International Mining | FEBRUARY 2021