Isatis Essentials for Oil & Gas

Gain the skills you need to start using Isatis with confidence

Objective

Get acquainted with Isatis geostatistical tools. The course covers a broad range of topics, including Data Import/Export, Exploratory Data Analysis, Kriging and Simulations, Batch Processing.

Key Features

The course is designed as an Isatis training with detailed descriptions of the algorithms. It is based on computer exercises applied to real datasets coming from the petroleum industry. Isatis projects material given to attendees (database, graphics, journal files, etc.) can provide templates to use in subsequent work.

Who should attend

Since Isatis is a general purpose geostatistical tool, learning how to use it is of benefit to any geoscientist or engineer who works on spatial data: geologists, geophysicists, reservoir engineers. Attendees will practice either alone or by pair.

Course content

This session covers the following topics:

  • Presentation of the Isatis concepts and tools: User Interface, types of data manipulated and organization of the database, graphical capabilities, HTML on-line manual, batch capabilities.
  • Exchanging data with other software: loading data into the database.
  • Data management inside Isatis.
  • Classical statistics and Exploratory Data Analysis.
  • Computing experimental variograms and an introduction to variogram modeling.
  • Applying Ordinary Kriging.
  • Introduction to simulations.
  • Graphics and reporting.
  • Exchanging data with other software: saving results outside of Isatis.

Prerequisites

It is required to have knowledge of the basic concepts of geostatistics (understanding of spatial data analysis, variogram and kriging), however the course does not make use of mathematics and therefore can be followed by beginners in geostatistics as well as by confirmed geostatisticians.

Additional information

Optional days could be reserved for practicing on the attendant’s own dataset, with a particular focus on Data Loading and Exploratory Data Analysis. In such case datasets should be sent to Geovariances beforehand in order to make sure that they can properly be used during the training.