Tag: Support Vector Machine

Isatis.neo - Sample clustering

Sample clustering in Isatis.neo has proven to be efficient with big datasets
Posted on by Geovariances

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.

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INDUSTRIES:
Mining (10)
Oil & Gas (5)
Nuclear Decommissioning (3)
Hydrogeology (3)
Contaminated sites (1)

TAGS:
2D erodability map (1)
Airborne flight line (1)
Complex geometric relationships (1)
Conditional simulations (5)
Contamination diagnostic (1)
Conversions & Uncertainties (1)
Corporate (1)
Data analysis (1)
Drill hole spacing analysis (1)
Facies modeling (1)
Flight line spacing (1)
Flow path lines (1)
Flumy (1)
Genetic model (1)
Geological modeling (2)
Geostatistical Hierarchical Clustering (1)
Geostatistical simulations (1)
Image filtering (1)
Isatis (10)
Isatis.neo (11)
Kartotrak (2)
Kriging (1)
Mapping (2)
MIK (2)
Mineral resource estimation (4)
MPS (1)
Multi-Acquisition Factorial Kriging (1)
Multivariate geostatistics (1)
Post-accidental situation (2)
Post-processing (1)
Recoverable resource estimation (3)
Reservoir modeling (1)
Resource classification (1)
Resources workflow (2)
Risk analysis (2)
Sampling optimization (2)
Scripting procedures (3)
Seismic cubes (1)
Soil contamination mapping (1)
Statistics (1)
Support Vector Machine (1)
Turbiditic depositional system (1)
Uncertainty analysis (1)
Uniform Conditioning (4)
Variography (2)

AUTHORS:

DATES:
2021 (2)
2020 (2)
2019 (7)
2018 (2)
2017 (2)
2016 (2)