• views: 39
• date: 11 September 2026
• posted by: voska89

Modeling Statistics and Geostatistics using Leapfrog Geo + Leapfrog Edge applied to Copper and Moly porphyry estimation

What you'll learn

⚡ Modeling sedimentary, intrusive and brecciated units related to Cu-Mo porphyry mineralization
⚡ Statistic analysis to outlier detection, estimation domains merge and grade capping
⚡ Geostatistical analysis in each estimation domain and executing an estimation plan for Cu-Mo estimation
⚡ Calculate the probability to be above a cut-off grade, using a critical grade Indicator and Ordinary Kriging

Requirements

❗ Geochemistry zonation and description of copper porphyry knowledge
❗ Intermediate knowledge in statistics
❗ Basic knowledge in geostatistics
❗ Basic knowledge in resource estimation

Description

Global copper (Cu) demand continues to grow while supply shrinks, as fewer mineral deposits are discovered each year worldwide. A fundamental outcome of mineral exploration is delivering to the market a reliable estimate of Cu tonnage in the subsurface, one that provides confidence and minimizes uncertainty.
This nearly 14-hour course offers a series of high-quality videos, carefully designed to take participants from the core concepts of geological modeling and resource estimation all the way to the industry best practices that today's market demands.
The course walks step by step through a complete resource estimation workflow applied to copper porphyry deposits, covering
✨ Geological modeling
✨ Statistical analysis, outlier detection, and compositing
✨ Resource modeling and contact analysis
✨ Gaussian anamorphosis
✨ Geostatistical analysis and variography
✨ Resource estimation using Ordinary Kriging, Inverse Distance Weighting, and Nearest Neighbor — with a multi-pass estimation plan
✨ Resource classification and reporting
Another point to consider during resource estimation is the uncertainty quantification, this is not possible if you don't have a conditional simulation module, but to top it all off, the scorecard methodology (from Rocha and Bassani, 2023) is applied to identify blocks of higher and lower confidence, giving you a complete, market-ready resource estimation workflow. This methodology is used in the course to give more insights about resource confidence

Who this course is for

⭐ Geologist and Miners working with modeling and resource estimation
⭐ People in general who wants to learn modeling and resource estimationwith cutting-edge software

Homepage

https://www.udemy.com/course/leapfrog-geo-edge-para-modelar-y-estimar-porfidos-cupriferos

   
   
   

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