Introduction to Python for Geoscientists

Course Description

In today's data-driven world, the ability to analyze and visualize complex datasets is essential for geoscientists. This course is designed for geoscientists seeking to leverage the power of the Python programming language and enhance productivity in their daily work. Over three days, participants will gain foundational knowledge in Python, focusing on statistical analysis, data processing, and graphical visualization techniques tailored to the specific needs of the geoscience industry.

The first two days of the course will introduce participants to the fundamentals of Python programming. We will begin with an overview of the Python programming language, including its importance and versatility in data analysis. Participants will learn how to set up their Python environment, including the installation of essential tools like Jupyter Notebook, which provides an interactive platform for coding. We will also cover an overview of useful Python libraries that are particularly relevant to geoscience, such as NumPy, Pandas, and Matplotlib. These libraries enable users to perform data manipulation, statistical analysis, and visualization tasks with ease.

The hands-on coding sessions will include practical exercises using geological datasets. Participants will explore basic programming concepts such as importing functions, understanding variable types, and implementing loops. Additionally, we will delve into data structures like lists, dictionaries, and tuples, emphasizing their importance in organizing and manipulating geoscientific data. Participants will also learn how to navigate Python library documentation effectively, a crucial skill for any aspiring programmer.

On the third day, we will shift our focus to data preparation and exploratory data analysis (EDA). Participants will learn how to load, filter, clean, and visualize data using key Python libraries specifically chosen for applications in geosciences. We will cover practical techniques for preparing datasets, ensuring they are ready for analysis.

The course will explore various file formats commonly used, including CSV, LAS, SEG-Y, and shapefiles (SHP). Participants will engage in hands-on exercises to practice loading and cleaning these datasets, allowing them to apply the concepts learned in the previous sessions.

Throughout the course, we will emphasize the importance of data visualization. Using libraries such as Matplotlib, Plotly, or Seaborn, participants will learn how to create compelling graphical representations of their data, facilitating better communication of findings and insights.

By the end of this three-day course, participants will have a solid foundation in Python programming tailored to the geoscience field. They will possess the skills needed to analyze complex datasets efficiently, automate their workflows, and produce high-quality visualizations, ultimately enhancing their productivity and effectiveness in their geoscientific work.

Course Outline

Day 1 & Day 2: Python Basics

• Introduction to Python programming language
• Python environment installation
• Introduction to Jupyter notebook and alternatives
• Overview of useful Python libraries and illustrations
• Python coding basics & practice on geological datasets:
  • Importing functions
  • Variable types
  • Loops “for/while”
  • List management, dictionary, and tuples
  • Reading Python library documentation

Day 3: Data Preparation & EDA

• Data loading, filtering, cleaning, and visualization
• Use of key Python libraries in geoscience:
  • Pandas, GeoPandas, Matplotlib, Plotly, Seaborn libraries
• Exercises on geophysical and geological datasets (*.csv, *.las, *.xlsx, *.seg-y, *.shp, etc.)

Participants’ Profile

The course is designed for geoscientists and engineers who want to develop powerful Python-based methods to enhance efficiency in managing, analyzing and processing geological data.

Prerequisites

No background in coding is required, but willingness to learn programming is essential.

About the Instructor

Claude Cavelius holds a Master's degree in Numerical Geology from the École Normale Supérieure de Géologie (Nancy, France), earned in 2007. A geologist by training, Claude has always been passionate about software development, technology, and innovation. He began his career at Chevron, where he spent 9 years as a software engineer and research geologist. During this time, he specialized in geostatistics and structural geology, contributing to the development of advanced geological models and tools to support exploration and production activities. Claude's dual expertise in geology and programming allowed him to bridge the gap between complex geoscientific challenges and efficient software solutions.

In 2016, Claude joined Belmont Technology as the product manager, where he focused on delivering advanced, cloud-based AI solutions tailored for the oil and gas industry. His role involved designing and implementing AI-driven tools that enabled more efficient data analysis and decision-making, helping clients optimize their operations through innovative technology.

Today, Claude serves as the CEO/CTO of DeepLime. DeepLime operates at the crossroads of geology, IT, and data science, empowering businesses by unlocking the full potential of their geological data. Claude leads the software development team, which focuses on creating cutting-edge tools and solutions that transform the way geoscientists work.