Isatis for geological modeling and hydrogeology

November 23, 2017

Isatis builds accurate and reliable 3D models of subsurface properties, taking into account their spatial behavior and heterogeneities. Quantifying model uncertainties is critical when managing projects dealing with water resources, natural risks, flow simulations, geotechnics, optimization of measurement networks, assessment of efficiency and safety of underground storage, ...

Isatis helps you address various issues:

Aquifer modeling

  • Optimization of piezometric networks
  • Mapping of top and bottom of geological layers
  • Distribution of hydraulic head
  • Petrophysical (permeability/porosit), mechanical or hydrogeological properties modeling
  • Facies data modeling

Water quality

  • Modeling of pollutants using numerical modeling tools (initialization, data assimilation)
  • Temporal analysis, help for a better understanding of the phenomenon

Uncertainty quantification

  • Sensibility and uncertainty analysis linked to a numerical modeling
  • Quantification of water volumes inside aquifers

 

Hereafter are some examples of issues Geovariances’ customers and consultants addressed with Isatis:

TNO | GEOLOGICAL MODELING

Context / Objectives

  • 3D geological model of the upper 30 m of the subsurface of the Netherland
  • To provide a sound basis for subsurface related questions on groundwater extraction and infrastructural issues

Methods

  • SGS and SIS for facies modeling
  • Isatis batch procedures to automate the worflow

Outcomes

  • 3D geological framework models and 3D volume models of which secondary products for applications can be extracted

 

Read the complete success story →

CEA | WATER QUALITY MODELING

 

Context / Objectives

  • Regional modeling of water quality

Methods

  • Collocated cokriging using available measurements, atmospheric deposits and the output of a numerical model of hydrogeology

CEA | HYDROGEOLOGICAL MODELING

 

Context / Objectives

  • Environmental monitoring of CEA sites

Methods

  • Kriging of hydraulic head with Digital Elevation Model as external drift
  • Special approach for permeabilities

Outcomes

  • Hydraulic head estimates and permeability fields used as input/output data for solving the inverse problem
  • Approach automated by CEA

Further reading: Renard F., N. Jeannée (2008), Estimating transmissivity fields and their influence on flow and transport: The case of Champagne mounts. In Water Resources Research, 44, W11414, doi:10.1029/2008WR007033.
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RHODIA – ARCADIS | HYDRAULIC BEHAVIOR OF A FORMER MINE

 

Context / Objectives

  • Former mine, now flooded
  • Better knowledge of the hydraulic behavior
  • Use of rainfall, water level of the Loire river, piezometric and water levels inside the mine

Methods

  • Statistitical tools, variograms, correlograms
  • Temporal variations: delay between water levels, periodicities …

Outcomes

  • Importance to work with 30-days means rather than instantaneous data
  • Cyclic behavior between the Loire and the mine
  • Different delays during the year

EDF | UNCERTAINTY EVALUATION

 

Context / Objectives

  • Complex hydrogeological model used to predict discharges in the Loire during low water level periods
  • Uncertainties inventory, errors quantification
  • New transmissivity fields

Methods

  • Comparisons between data and simulation outputs
  • New transmissivity fields using kriging

Outcomes

  • Thorough list of uncertainties sources
  • Tools for errors quantification assessment
  • New calibration of the model using the kriged transmissivity fields

CREALP | ICE CONTENT EVALUATION WITHIN A GLACIER

 

Context / Objectives

  • Slow downward constant creep which constitutes an environmental hazard
  • Lithology and ice content data

Methods

  • Comparison of global ice volume between statistical estimation, 3D simulation and 3D simulation taking the lithology into account
  • Facies modeling, plurigaussian simulations

Outcomes

  • Statistical approach: ignore the data redundancy due to the spatial structure
  • Plurigaussian Simulations produce more realistic results

ONDRAF | HYDROGEOLOGICAL MODELING

 

Context / Objectives

  • Deep repository of radioactive waste within geological barrier
  • 3D modeling of key hydrogeological parameters to assess the quality of the geological barrier

Methods

  • Review of database consistency
  • 1D/3D modeling of target parameters using geophysical logs as auxiliary variables

Outcomes

  • Validation of database
  • Recommendations for further sampling locations & strategy

Further reading: Jeannée N., A. Berckmans, L. Wouters, J. Deraisme, J.-P. Chilès (2010), Quantifying the transferability of hydraulic parameters using geostatistics: the Boom Clay case, In Proceeding of the conference « Clays in Natural & Engineered Barriers for Radioactive Waste Confinement », Nantes, March 2010.

BRGM – SUEZ/LYONNAISE DES EAUX | GEOLOGICAL MODELING

 

Context / Objectives

  •  RIVIERA project
  • Assessment of the risk of water infiltration into the wastewater system

Methods

  • Plurigaussian simulations
  • 3D modeling of permeabilities

CREALP – COLENCO | OPTIMIZATION OF MONITORING NETWORK

 

Context / Objectives

  • Hydrogeological monitoring network of the Rhône-Alps valley
  • Goal: reduce monitoring cost while preserving estimation quality

Methods

  • Intrinsic kriging
  • Kriging variance

Results

  • 20% decrease of the total number of piezometers

Mines ParisTech | WATER QUALITY MONITORING

 

Context / Objectives

  • Nitrates modeling

Methods

  • Kriging and estimation of related confidence interval
  • Evaluation of inconsistencies between data and model

Further reading: Flipo N., N. Jeannée, M. Poulin, S. Even, E. Ledoux. 2005. Assessment of nitrate pollution in the Grand Morin aquifers (France): combined use of geostatistics and physically-based modeling. In Environmental Pollution, 146 (2007) 241-256.