Tag: Mineral resource estimation
Geostatistical simulations, what for? Geovariances’ consultants give examples of use
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We asked some of our consultants to tell us about recent studies in which they used conditional simulations for specific issues. Here are the examples they gave us.
Drilling optimization through DHSA
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Read how Geovariances’ consultants help a copper mine in Brazil to reduce the grade uncertainty of ore concentrates to better meet customers’ requirements.
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.
DiscoverMine Radio podcast – Episode 23: An introduction about geostatistics in a mining operation by Marlene Woligroski
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Marlene Woligroski, geologist and business development manager for the Asia Pacific region, has been invited by DiscoverMine Radio to introduce and explain the interests of geostatistics and the benefits offered by our software Isatis.neo.
Isatis.neo Resources Workflow can be used for audit and desktop review of Mineral Resource Estimation projects
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Auditing and reviewing a Mineral Resource Estimate either internally or publicly is a multifaceted process for which no software can pretend it will provide all the required tools to tick all the boxes. But some solution will provide better adapted platforms than others. Isatis.neo Resource Workflow falls in that category.
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.
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…
Mining (14)
Nuclear Decommissioning (9)
Contaminated sites (7)
Oil & Gas (6)
Hydrogeology (5)
TAGS:
2D/3D (2)
Background images (1)
Big data (1)
Conditional simulations (7)
Contaminated sites (2)
Contamination (2)
Drill Hole Spacing Analysis DHSA (3)
Excavation (2)
Facies modeling (2)
Flow modeling (1)
Geological modeling (3)
Gestion des sites pollués (2)
H2020 INSIDER (1)
Horizon mapping (1)
Ice content evaluation (1)
Isatis (11)
Isatis.neo (16)
Kartotrak (8)
Machine Learning (2)
Mapping (3)
MIK (2)
Mineral resource estimation (7)
Monitoring network optimization (1)
MPS (2)
Ore Control (1)
Pareto (2)
Pollution (2)
Post-accidental situation (2)
Recoverable resource estimation (3)
Resource classification (2)
Resources workflow (1)
Resource workflow (3)
Risk analysis (3)
Sample clustering (1)
Sampling optimization (3)
Scripting procedures (3)
Simulation post-processing (1)
Site characterization (2)
Soil contamination mapping (4)
Time-to-Depth conversion (1)
Uncertainty analysis (2)
Uniform Conditioning (5)
Variography (2)
Volumes (2)
Water quality modeling (1)
AUTHORS:
David Barry (3)
Pedram Masoudi (2)
Yvon Desnoyers (2)
Pedro Correia (1)
Catherine BLEINES (1)
DATES:
2023 (2)
2022 (3)
2021 (2)
2020 (2)
2019 (8)
2018 (4)
2017 (3)
2016 (3)