Geovariances: Where no one has gone before

 Overview

Isatis is a fully integrated and operational geostatistical package which offers geoscientists a wide range of tools for in-depth data analysis, estimation and risk analysis.

Its interfaces with standard data formats (Excel, GIS, etc.) allow you to easily integrate Isatis in your day-to-day workflow.

 Benefits

• Valuate your data by a secure quality process
• Optimize your sampling strategies and investigation costs
• Take advantage of multiplicity of data sources
• Get accurate and reliable mapping
• Quantify the uncertainties and assess the risks
• Automatically update your communication media

 Solution

Geostatistics helps estimate and localize the contaminated soil volumes with greater accuracy and to quantify the uncertainty on these volumes.

• Valuate your data
  
  
  • Investigate and clean your data with Isatis unique Exploratory Data Analysis interactive module.
  • Identify and handle data anomalies and anisotropies using appropriate statistical representations (basemap, histogram, q-q plot, variogram map).
  • Identify homogeneous areas.

• Optimize your investigation data
  
  
  • Optimize your sampling strategies.
  • Fully integrate all qualitative and quantitative available data (historical information, geophysics, chemical kits) so that no information is either unused or lost.

• Get a reliable mapping of the pollution
  
  

  

  Delineation of an organic contamination by hydrocarbons (visualized with Isatis 3D Viewer)

• Characterize the spatial behavior of your pollutant concentrations through variogram analysis.
• Take the sampling representativity into account.
• Compute accurate maps using appropriate kriging algorithms and variogram models.
• Assess the precision of your map with the kriging variance.
• Refine your pollutant map using correlated pollutants data and indirect information
• Take advantage of different series of measurement of a same pollutant.

• Quantify the uncertainties on contaminated volumes
  
  
  • Compute the probability of exceeding a pollution threshold over a given remediation block using non linear techniques.
  • Have a reliable estimate of contaminated volumes to be cleaned up from probabilistic models.
  • Obtain results which are consistent with the remediation technology and objectives.
  • Get the probability distribution of contaminated materials and assess the uncertainty on the volumes.
  • Classify the materials as contaminated or safe according to statistical criteria.
  • Avoid overspending by quantifying the uncertainty on your remediation budget.
  • Adjust your remediation strategy

Geovariances is co-founder of GeoSipol, a French association for promoting geostatistics for efficient contaminated site characterization.