Course Schedules

Classroom 7 Sessions
Online / Live
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Training Course Overview

Geostatistics – Using Software for Geospatial Analysis Training Course introduces powerful statistical and computational techniques used to analyze spatial data in geology and oil and gas exploration. Geostatistics plays a critical role in understanding subsurface structures, reservoir properties, and spatial relationships between geological variables.

This training course focuses on applying geospatial analysis using accessible tools such as Excel and the open-source R programming environment. Participants will learn how to interpret spatial data, build predictive models, and overcome limitations of standard software by using flexible analytical approaches.

With a strong emphasis on practical application, the course bridges theory and real-world exploration challenges. It enables professionals to enhance decision-making in reservoir modelling, data interpretation, and resource evaluation using advanced geostatistical techniques and software-based analysis.

Training Course Objectives

Geostatistics Training Course objectives are designed to build strong analytical and technical skills in spatial data interpretation and geospatial modeling for oil and gas and geological applications. This course strengthens the ability to use software tools for advanced data-driven insights.

By the end of this training course, participants will be able to:

  • Understand core concepts and methodologies of geostatistics and spatial data analysis
  • Use Excel and R programming tools for geospatial data processing and interpretation
  • Apply R packages for spatial analysis, modeling, and statistical computation
  • Import, analyze, and interpret geological and spatial datasets effectively
  • Perform advanced techniques including Monte Carlo simulation and clustering analysis
  • Develop skills in kriging, variogram analysis, and spatial prediction methods

Designed for

Geostatistics and Geospatial Analysis Training Course is designed for professionals working with spatial data, geological modeling, and oil and gas exploration. It supports individuals seeking to improve their analytical capabilities using modern software tools.

This training course is suitable for:

  • Data scientists and data analysts working with spatial datasets
  • Geologists involved in exploration and reservoir studies
  • Petroleum engineers focused on subsurface modeling and interpretation
  • Reservoir engineers working with geological and production data
  • Professionals involved in geospatial analysis and oil and gas exploration

Learning Methods

Geostatistics Training Course learning methods are designed to provide a balanced mix of theoretical understanding and hands-on software application. The course ensures participants gain practical experience in geospatial analysis using real datasets and industry-relevant tools.

Participants will begin with structured presentations covering key geostatistical concepts, spatial modeling techniques, and software fundamentals. Video-based explanations will support understanding of complex topics such as variograms, kriging, and spatial statistics.

Guided exercises using Excel and R will allow participants to directly apply analytical techniques to real geological data. Step-by-step practical tasks include data import, correlation analysis, clustering, and simulation methods.

Advanced hands-on sessions focus on Monte Carlo simulation, Bayesian concepts, and spatial prediction techniques. This interactive approach ensures participants develop strong technical competence in geostatistics and confidently apply software-based solutions to real-world oil and gas exploration challenges.

Course Content

Day 1

Geostatistics - Concepts and Introduction to Software

  • Basics of Geostatistics
  • Geostatistical reservoir modelling
  • Short introduction to Excel
  • Short introduction to R and R studio
  • Exercise: importing well log data into excel and creating GR vs Depth plot
  • Exercise: importing well log data into R and initial analysis
Day 2

Spatial Data Analysis

  • Spatial Data Sampling
  • Spatial Resolution Gap
  • Spatial Weight Matrices
  • Basis of data analysis: statistical measures, correlation and autocorrelation
  • Exercise: determining correlation and autocorrelation in well log data using Excel
  • Exercise: Plotting Spatial connectivity
Day 3

Steps in Geostatistics - The Variogram and Kriging

  • Variogram and Modelling
  • Sampling for the Variogram
  • Nested Sampling
  • Geostatistical Prediction: Kriging
  • Exercise: Performing ANOVA in Excel, Kriging Example in Excel
  • Exercise: Variogram and Kriging in R studio
Day 4

Big Data Analytics and its Relation to Oil and Gas

  • Big Data Concepts
  • Clustering analysis
  • Spatial Variance and Covariance
  • Data distributions
  • Exercise: Variance and covariance calculation in Excel
  • Exercise: Clustering analysis in R studio
Day 5

Advanced Topics in Spatial Statistics

  • Bayesian Theory and Spatial Data
  • Monte Carlo Analysis
  • Markov Chains
  • Exercise: Monte Carlo Simulation for Oil and Gas reserves simulation in Excel
  • Exercise: Monte Carlo Simulation in R
  • Fuzzy Logic, Machine Learning and generative algorithms and the future of prediction

The Certificate

Recognition
  • Anderson Certificate of Completion for delegates who attend and complete the training course
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