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Geostatistics - Using Software for Geospatial Analysis

Using R and Excel for Analysis of Spatial Data

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Why Choose Us

The Geostatistics - Using Software for Geospatial Analysis training course introduces statistical methods for analysing, visualising and interpreting spatial data effectively. It is designed for geoscience professionals, with practical applications focused on oil and gas exploration. Participants develop hands-on skills using Excel and R, supported by relevant theoretical foundations and practical exercises. This combination enables learners to apply geostatistical methods confidently to real-world spatial data challenges.

The course helps data analysts, geologists and oil and gas professionals move beyond the limitations of pre-packaged commercial software. Although these tools offer useful models, they can restrict customisation and more advanced analysis. Participants learn to use free or low-cost software, apply their own analytical approaches and gain deeper insights from spatial datasets. They also examine core geoscience concepts, combine information from multiple sources and relate measurements to reservoir properties using advanced geostatistical techniques.

This Geostatistics - Using Software for Geospatial Analysis training course will highlight:

Applying statistical methods to spatial data analysis
Analysing and visualising geospatial data with Excel and R
Integrating information drawn from multiple sources
Establishing relationships between measurements and reservoir properties
Using semi-variograms, kriging and Monte Carlo simulation
Applying clustering, numerical facies modelling and fuzzy logic

Why Choose Geostatistics - Using Software for Geospatial Analysis

Course Goals

What are the Goals?

Upon completing this Geostatistics - Using Software for Geospatial Analysis Training Course, participants will be able to:

Comprehend the fundamental principles and techniques of geostatistics.
Develop proficiency in using Excel and R to analyse spatial data.
Become familiar with key R packages used in geospatial analytics.
Import, process and interpret spatial data obtained from various sources.
Use statistical measures, correlation and autocorrelation to examine spatial relationships.
Carry out Monte Carlo simulations to forecast oil and gas reserves.
Undertake clustering analysis, kriging and variogram modelling.
Examine advanced approaches, including fuzzy logic, Bayesian methods and generative algorithms.

This training course provides professionals with foundational understanding and advanced hands-on capabilities, allowing them to make decisions based on data and enhance predictive modelling in geoscience and reservoir analysis.

Who is this Training Course for?

This Geostatistics - Using Software for Geospatial Analysis training course is designed for:

Geostatisticians
GIS Analysts
Geospatial Analysts
Spatial Data Analysts
Data Scientists
Geologists
Geophysicists
Environmental Scientists
Mining Engineers
Surveyors

Learning Approach

How will this Training Course be Presented?

The Geostatistics - Using Software for Geospatial Analysis Training Course combines several teaching approaches to maximise participation and knowledge retention:

Interactive Lectures: Practical examples are used to explain concepts clearly.
Hands-on Exercises: Learners gain practice in importing and analysing spatial data using Excel and R.
Guided Projects: Structured, step-by-step activities cover variograms, kriging, Monte Carlo simulations, clustering, and fuzzy logic.
Real-world Applications: Activities concentrate on oil and gas exploration and reservoir modelling.
Video Demonstrations: Brief videos demonstrate software techniques and statistical methods.

Through the integration of theory and practical activities, this training course enables learners to apply geostatistical methods immediately to real-world problems, strengthening their analytical abilities and confidence in spatial data analysis.

The Course Content

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

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

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

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

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

Recognition

Certificate

• Wallstreet Development Academy Certificate of Completion for delegates who attend and complete the training course.

Frequently Asked Questions

This course covers geostatistics and software-based geospatial analysis. It focuses on analysing spatial data using R and Excel. The course title and subtitle do not specify individual statistical methods or topics.

The course focuses on spatial data. Participants use R and Excel to support the analysis of data with a geographic or spatial dimension. Specific datasets or application areas are not stated in the course information.

R is used as one of the course’s tools for analysing spatial data. Its use is positioned within geostatistics and geospatial analysis. The available course description does not list the specific R packages, functions or techniques covered.

This course is relevant to people seeking to use R and Excel for geostatistical or geospatial analysis of spatial data. It may suit learners whose work or studies involve spatial information and software-based analysis. The available course information does not specify particular job roles or experience levels.

The course uses R and Excel for spatial data analysis. Both tools are presented within the broader context of geostatistics and geospatial analysis. No additional software is identified in the available course information.

The training builds skills in using software to analyse spatial data. Its stated focus is the application of R and Excel within geostatistical and geospatial analysis. More detailed learning objectives are not provided.

Excel is used as one of the software tools for spatial data analysis. The course connects its use with geostatistics and broader geospatial analysis. Specific spreadsheet features or analytical procedures are not identified.

The available course information does not state any prerequisites. It identifies R and Excel as the tools used for spatial data analysis but does not specify a required proficiency level. Prospective participants should therefore check the course’s entry guidance, if available, before enrolling.