Geostatistics for optimizing reservoir characterization

Geostatistics provides the most efficient framework to build accurate and reliable static models of reservoirs.

Geostatistics is valuable at all steps of the geomodeling process:

  • Seismic data quality control and enhancement;
  • Time-to-depth conversion and optimal mapping of horizons;
  • Structural uncertainty quantification;
  • Rock-typing;
  • Facies distribution in various geological environments;
  • Petrophysical properties distribution;
  • Uncertainty quantification on Volumetrics.

Geovariances puts its Oil & Gas industry knowledge, continuous innovation and geostatistical expertise at your service to guarantee the quality and reliability of your geological models.

Hear from our customers

"I really recommend this day of discovery of geostatistics as it gives a rather comprehensive introduction and practical operational applications to lot of domains of the E&P industry."

Nicolas Nosjean-Gorgeu, Project Leader - Senior Geoscientist - Engie
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"The online training was conducted in 10 sessions of 2 hours over 2 weeks. This gave me the time I needed to fully digest the course between 2 sessions and the opportunity to be critical about what I was doing. I definitely recommend Geovariances online training."

Gabrielle Rumbach, Geologist - Vermilion
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"Thanks to the skills of the trainers and the quality of the documents provided, the training was a very successful experience, one which I would strongly recommend for other E&P teams."

Antoine Benedini, Head of Geophysics – Integrated projects - Foxtrot International, Ivory Coast
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"Being able to exchange data between Petrel and Isatis in a seamless and quick way is crucial for us. We are very satisfied with the the new capabilities of Isatis-Petrel interface introduced in 2014"

Olinto Gomes de Souza Jr., Geologist - Petrobras, Brazil
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“Best Geostatistical toolbox on earth! You can’t beat the reliability and the variety of the tools and methods available to solve literally any spatial problem. It’s great to use in conjunction with larger commercial earth modeling packages, or simply on its own.”

Jeffrey Yarus, Senior Manager of Earth and Reservoir Modeling - Landmark / Halliburton
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What is happening in your industry?


January 22, 2021

You're a user of Isatis.neo? Your experience and opinion are most valuable! We invite you to be part of our user panel and have your say i...

December 8, 2020

Geovariances, with Isatis.neo, brings the most performing geostatistical simulation algorithm to the market: SPDE. This new approach adds ...

November 21, 2019

Our experts Jean-Marc Chautru and Hélène Binet will give the lecture "Fundamentals of Petroleum Geostatistics" at the IFP School using I...

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Sept. 2-6, 2024
Geovariances is sponsoring the 2024 Geostats Congress! Join us for engaging presentations and an interactive workshop. See you there!
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Hydrogeological Facies Modeling

Stochastic Methods for geological modeling and links with fluid flow simulations

Whatever the application domain – oil & gas production, aquifer pollution characterization, uranium production by lixiviation – characterizing the geological parameters and capturing their variability is essential to ensure realistic flow modeling…

Time to Depth Conversion

Time to depth conversion of geological surfaces is critical for structural model building. Quantifying the uncertainty attached to the conversion is also of primordial importance for assessing GRV uncertainties. Traditional velocity models used in time to depth conversion could benefit from geostatistical techniques used in data integration. The advantage of using geostatistical methods is that they fit the data in one step and allow quantifying the uncertainty attached to the prediction by mean of the generation of equiprobable realizations.

Through Geovariances long-lasting experience in geostatistical depth conversion studies, learn how geostatistics helps you improve the accuracy of your reservoir structural model and assess the uncertainties on surfaces.

Mapping with auxiliary data

Through this white paper, discover how you canimprove significantly map reliability and quality by incorporating various sources of information in the interpolation process.

This document details the different methods for assimilating various sources of information, taking into account the reliability of each source and how the uncertainty associated with any mapping result can be estimated and reduced.

Geological Facies Simulations

Whatever the resource involved – oil & gas, coal or metallic resources – capturing the variability of the geological parameters is essential at the modelling stage as the characteristics of the distributions of key parameters conditioning the resource recovery (e.g. rock properties, grades, etc.) are informed by the geological context. A large variety of simulation techniques is available to model geological facies.

Through Geovariances strong experience in developing successfully simulation strategies for different geological environments (e.g. kimberlite pipes, turbiditic and carbonate reservoirs, porphyry copper, hydrothermal type deposits, etc.), learn how to choose the best facies modelling technique according to the specific geological depositional environment. Analyse each method advantages and drawbacks.

How to Capture Trend Uncertainty with Bayesian Kriging

In presence of trends, kriging with Bayesian drift bridges the gap between the traditional kriging with external drift and a simple kriging of the residuals, allowing a better trend control. The method has wide ranges of applications, an important one being its ability to deal with time to depth conversion.

Through this white paper, find out how the technique benefits from the prior knowledge gained from similar fields regarding the trend shape to produce coherent estimates, especially when the data are sparse and traditional geostatistical data analysis may lack robustness.

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