COURSE SCHEDULE
| Code | Date | Location | price (€)* |
|---|---|---|---|
| DAT 603 | 7 - 9 Oct 2026 | Online | 1980 |
| DAT 603 | 24 - 26 Nov 2026 | Amsterdam | 2640 |
COURSE OVERVIEW
Python offers significant advantages over Excel and includes powerful, readily available tools for importing and exporting data to and from spreadsheets. This course provides a practical introduction to using Python for common geoscience and reservoir engineering tasks. Rather than being a purely programming-focused course, it is structured around solving real-world technical problems efficiently using Python.
As the industry moves beyond spreadsheet-based workflows, many data analysis requirements faced by geoscientists, petrophysicists, geophysicists, geologists, and geomodellers exceed the practical limits of Excel—or are unnecessarily complex within it. Python provides a flexible, scalable alternative for handling large datasets, automation, and advanced analysis.
By the end of the course, participants will have installed a Python environment on their laptops and created a series of notebooks to automate repetitive tasks, perform data analysis, and interface seamlessly with Microsoft Excel. They will also learn how to produce high-quality data visualizations and plots, either as standalone outputs or integrated into technical reports and presentations.
COURSE OUTLINE
2 days
Day 1: Using wireline data
o Python syntax
o General introduction to Python
o Data types and their basic operations
o Data structures
o Statements (if, for, while)
o Loops using the range function
o Defining functions
o Python tools
o Visualisations
oAdvanced statistics
Day 2: Using mapping data
o“Scientific” Python
o NumPy (arrays, numeric data processing, indexing)
o SciPy (SciPy.stats, SciPy.spatial)
o Pandas
o Data visualization using Matplotlib
Day 3: Interfacing with MS Office
o Automating Word
o Automating Powerpoint
o Creating Word documents and Powerpoint presentations from Excel
INSTRUCTOR

Professor Stephen Tyson
Stephen Tyson is a Chair Professor in Petroleum Engineering at Universiti Teknologi Brunei, where he leads the development of teaching and research in the discipline. Previously, he served as Chair of Subsurface Modeling at the Centre for Coal Seam Gas and as Director of the Centre for Geoscience Computing in the School of Earth Sciences at The University of Queensland.
He has more than 30 years of industry experience in reservoir characterization and modeling, covering both conventional and unconventional reservoirs. His work has been primarily focused in the Asia-Pacific region and Australia.
His current research interests include model validation, verification and acceptance criteria for static and dynamic models, upscaling, uncertainty modeling, and non-linear geostatistics. He is also an Honorary Professor in Petroleum Engineering at the University of New South Wales and serves as an EAGE instructor.
FAQ
DESIGNED FOR
The course is designed for geologists and reservoir engineers who want to become more effective at manipulating data, automating repetitive tasks in MS Office, and produce better visualisations of numerical information.
COURSE LEVEL
o Beginner to Intermediate
LEARNING OBJECTIVES
The learning objectives of this course are for students to develop:
o An understanding of the opportunities that Python offers to geoscientists
o An ability to easily migrate data between Excel and Python using Pandas
o Understanding of basic Python syntax
o Understanding of packages that give additional functionality to Python; Numpy, SciPy, Matplotlib, etc.
o An ability to display data using richer visualization tools
o Sufficient knowledge of Python so that the participant can easily extend their capabilities using readily available tutorials and sandboxes
REGISTER
Registration is now OPEN!
* Prices are subject to VAT and local terms. Ph.D. students, groups (≥ 3 persons) and early bird registrants (8 weeks in advance) are entitled to a DISCOUNT!
For more details and registration please send email to: register@petro-teach.com
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