DiscoverMine Radio podcast – Episode 24: Conditional simulation and uncertainty in the ore body by David Barry

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David Barry, Senior Geostatistician and a Geovariances’ Perth-based consultant, has been invited by DiscoverMine Radio to explain conditional simulation as one method used in the mining operation to better estimate the ore body. Listen to the recording and learn what conditional simulations are, how they differ from classic mining geostatistics techniques.

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What are recoverable resources? (2/2)

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David Barry, Senior Geostatistician and a Geovariances’ Perth-based consultant, has been invited by Optiro, a resource consulting group, to participate in a podcast about recoverable resource estimation. Listen to this 2nd recording and learn more about the alternatives to uniform conditioning, such as MIK and conditional simulations, and their pros and cons.

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The importance of being … consistent

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The search for productivity improvements is pervasive in the mining industry and MRE software are no strangers to the quest for speed seen in all operational processes. But that quest, whilst valid and sound, should not come at the price of quality, optimality or consistency in the manner information is treated.

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Can you afford to bypass geostatistics for the sake of productivity?

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Anyone involved with today’s mining industry understands that the sector is facing very tough challenges. And it is under enormous pressure from due cost control and budgetary management constraints that innovation and ingenuity must still find their way to propose new ways of tackling traditional issues. Mineral Resource Estimation (MRE) is no stranger to that conundrum and their practitioners all know the multi facets of the game: integrate more and more data, boost productivity, and come up with an answer fast and at the same time enriched with an assessment of the uncertainty that can be attached to that answer. All of that in a fraction of the time they used to have at their disposal and less resources to double check…

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Use genetic models to constrain facies models and ensure accuracy and realism

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Geological modeling in Isatis can be achieved using MPS methodology or Flumy, our applications for meandering system modeling. Do you know that you can combine both of them to ensure model accuracy and realism? See the tests done for a NOC.

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Isatis manages several million data sets

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Through the years, Geovariances has always endeavored to improve Isatis performances to answer their client constraints related to the always increasing size of their data sets. Most of the algorithms in Isatis are thus optimized and parallelized to run on multi-threaded computers and decrease computation time in a significant manner.

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