What are recoverable resources? (2/2)
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.
What are recoverable resources? (1/2)
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 the recording and learn what are recoverable resources, how they differ from reserves, and what are the main techniques to compute them. The focus in on Uniform Conditioning. Other possible techniques will be presented in a further podcast.
Sample clustering in Isatis.neo has proven to be efficient with big datasets
Isatis.neo quickly groups borehole samples into homogeneous classes (e.g., facies, geological or mining domains) in an automatic way. Those who have seen the tool run qualifies it as impressive.
Can you afford to bypass geostatistics for the sake of productivity?
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…
Use genetic models to constrain facies models and ensure accuracy and realism
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.
Isatis manages several million data sets
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.
Oil & Gas (5)
Nuclear Decommissioning (3)
Contaminated sites (1)
2D erodability map
Airborne flight line
Complex geometric relationships
Conversions & Uncertainties
Flight line spacing
Flow path lines
Geostatistical Hierarchical Clustering
Multi-Acquisition Factorial Kriging
Recoverable resource estimation
Soil contamination mapping
Support Vector Machine
turbiditic depositional system