Using R for Geostatistical Geospatial Modeling

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Using R for Geostatistical Geospatial Modeling

This course is part of Practical Geospatial Geostatistical Modeling Specialization

Instructor: Jeffrey Yarus

Included with

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6 modules

Gain insight into a topic and learn the fundamentals.

Intermediate level

Recommended experience

2 weeks to complete

at 10 hours a week

Flexible schedule

Learn at your own pace

6 modules

Gain insight into a topic and learn the fundamentals.

Intermediate level

Recommended experience

2 weeks to complete

at 10 hours a week

Flexible schedule

Learn at your own pace

Skills you'll gain

Tools you'll learn

Details to know

Shareable certificate

Add to your LinkedIn profile

Assessments

13 assignments

Taught in English

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This course is part of the Practical Geospatial Geostatistical Modeling Specialization

When you enroll in this course, you'll also be enrolled in this Specialization.

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There are 6 modules in this course

Using R for Geostatistical Geospatial Modeling is the second course in a series of three, designed to teach you the art and science of geostatistical geospatial modeling. In this course, you will delve into the world of geostatistical geospatial modeling, using R, a widely-used interpretive coding language that is both user-friendly and immensely powerful.

This course builds upon the foundations laid in Course #1, Basic Principles of Geostatistical Modeling, taking your understanding of geostatistical geospatial modeling to the next level. You will learn how to code basic machine learning algorithms and geostatistical spatial models to solve real-world problems. By the end of this course, you will have a solid understanding of the principles and techniques of geostatistical geospatial modeling, and be able to apply them in your own work with confidence.

What's included

3 readings

What's included

17 videos17 readings5 assignments

17 videos Total 93 minutes

Introduction to the Module 3 minutes
Introduction to R 5 minutes
History of R 5 minutes
About R & Python 6 minutes
Git and Git Commands 6 minutes
R as a Tool 4 minutes
R Packages 6 minutes
R Studio 4 minutes
Installing R and R Studio 10 minutes
Working in R Studio 6 minutes
More Work in R Studio 7 minutes
R Markdown 5 minutes
Object Classes and Hashtags 7 minutes
Chunk & YAML Headers 5 minutes
Checking Attributes 6 minutes
Dataframes, Tibbles & Lists 4 minutes
Writing, Reading & Presenting Files 5 minutes

17 readings Total 165 minutes

Module Two Overview 5 minutes
Introduction to R 10 minutes
History of R 10 minutes
About R and Python 10 minutes
Git and Git Commands 10 minutes
R as a Tool 10 minutes
R Packages 10 minutes
R Studio 10 minutes
Installing R and R Studio 10 minutes
Working in R Studio 10 minutes
More Work in R Studio 10 minutes
R Markdown 10 minutes
Object Classes and Hashtags 10 minutes
Chunk and YAML Headers 10 minutes
Checking Attributes 10 minutes
Dataframes, Tibbles & Lists 10 minutes
Writing, Reading and Presenting Files 10 minutes

5 assignments Total 150 minutes

Quiz: Introduction to R 30 minutes
Quiz: Working with Git and R 30 minutes
Quiz: R Studio and R Markdown 30 minutes
Quiz: More R Markdown 30 minutes
Quiz: Writing, Reading & Presenting Files 30 minutes

What's included

9 videos1 reading2 assignments

9 videos Total 62 minutes

Introduction to the Module 3 minutes
Lecture: Introduction to Exploratory Data Analysis & Descriptive Statistics 7 minutes
Demo: Introduction to Exploratory Data Analysis & Descriptive Statistics 11 minutes
Lecture: Data Cleaning Part One 2 minutes
Lecture: Data Cleaning Part Two 5 minutes
Demo: Data Cleaning 8 minutes
Lecture: Data Visualization 5 minutes
Demo: Data Visualization 13 minutes
Data Modeling 6 minutes

1 reading Total 5 minutes

Module Three Overview 5 minutes

2 assignments Total 120 minutes

Analytics for Geostatistical Modeling 60 minutes
Analytics for Geostatistical Modeling 60 minutes

What's included

8 videos4 readings2 assignments

8 videos Total 56 minutes

Introduction to the Module 3 minutes
Data Preprocessing 6 minutes
Database Creation 5 minutes
The Experimental Semi-Variogram 6 minutes
Variogram Models 8 minutes
Modeling Experimental Semi-Variograms 11 minutes
The Directional Variogram 10 minutes
Variogram Maps 6 minutes

4 readings Total 125 minutes

Module Four Overview 5 minutes
2D Case Study 30 minutes
Teacher's aide variogram interpretation and modeling 60 minutes
Flexible Lag Definition for Experimental Variogram Calculation 30 minutes

2 assignments Total 120 minutes

Variograms 60 minutes
Variograms 60 minutes

What's included

7 videos2 readings2 assignments

7 videos Total 39 minutes

Introduction to the Module 3 minutes
Kriging Fundamentals 8 minutes
Kriging Components: Grids & Neighborhoods 8 minutes
Error Variance Map 3 minutes
Impact of Variogram Model on Kriging 6 minutes
Methods for Assessing Accuracy 6 minutes
Co-Kriging 5 minutes

2 readings Total 35 minutes

Module Five Overview 5 minutes
Cokriging: multivariable analysis in petroleum exploration 30 minutes

2 assignments Total 90 minutes

Kriging 60 minutes
Quiz: Kriging 30 minutes

What's included

7 videos3 readings2 assignments

7 videos Total 56 minutes

Introduction to the Module 3 minutes
Introduction to Conditional Simulation 6 minutes
Understanding Conditional Simulation 12 minutes
Data to Discoveries: Conditional Simulation in R 12 minutes
Selecting Appropriate Simulation Methods Based on Objectives & Data Categories 7 minutes
Collocated Co-Simulation 7 minutes
Post-Processing 8 minutes

3 readings Total 55 minutes

Module Six Overview 5 minutes
Practical Geostatistics- An Armchair Overview for Petroleum Reservoir Engineers 45 minutes
Course Conclusion 5 minutes

2 assignments Total 150 minutes

Conditional Simulation with Directional Variograms 60 minutes
Quiz: Conditional Simulation and Post-Processing 90 minutes

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Instructor

Jeffrey Yarus

Case Western Reserve University

3 Courses 1,091 learners

Offered by

Case Western Reserve University

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To access the course materials, assignments and to earn a Certificate, you will need to purchase the Certificate experience when you enroll in a course. You can try a Free Trial instead, or apply for Financial Aid. The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.

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