Python For Oil and Gas Professionals
After completing this course, participants will gain the ability to perform a wide range of geoscientific tasks using Python, including well log analysis, basic petrophysics, machine learning applications, seismic data reading and visualization, seismic interpretation, and seismic well tie. This course is designed to equip professionals with the foundational skills needed to leverage Python for advanced geophysical modeling and other geosciences practices. Participants will learn to apply Python programming to analyze and interpret subsurface data, enabling them to develop more sophisticated algorithms and workflows for tasks such as reservoir characterization, seismic attribute analysis, and predictive modeling. By the end of the course, attendees will be well-prepared to tackle complex geoscientific challenges using Python, enhancing their efficiency and innovation in the oil and gas industry.
H. Data Management Course/Data Management
3 days
Skilled
Classroom
DAY 1 – Python Basics & Well Log Analysis
Morning Session: Python Fundamentals
- Python Installation and Environment Setup
- Introduction to Containers and Lists
- Control Structures: if, for, while, try, except
- Introduction to numpy and pandas for Data Manipulation
- Data Visualization with matplotlib
Afternoon Session: Well Log and Basic Petrophysics
- Loading LAS data into/from SQLite Database
- Well Log Data Visualization
- Basic Petrophysical Calculations (Vsh, PHIT, PHIE, SW)
- Introduction to Machine Learning (ML) Concepts
- Overview of ML Algorithms: KNN, Random Forest (RF), SVM
- Model Evaluation: GridSearchCV and Accuracy Testing
DAY 2 – Seismic Data Handling and Visualization
Morning Session: Seismic Data Reading and Visualization
- Introduction to SEG-Y Data Format
- Reading and Parsing SEG-Y Data
- Saving and Querying Seismic Data in SQLite Database
- Seismic Data Visualization Techniques
Afternoon Session: Seismic Attributes and Interpretation Basics
- Generating Seismic Attributes
- Introduction to Seismic Interpretation
- Manual Horizon Picking
- Fault Picking Basics
DAY 3 – Advanced Seismic Interpretation and Mapping
Morning Session: Seismic Interpretation
- Advanced Horizon and Fault Picking Techniques
- Editing and Refining Horizons and Faults
- Saving Horizon and Fault Data in Files and Databases
Afternoon Session: Time Structure Maps
- Generating Time Structure Maps
- Incorporating Faults into Time Structure Maps
- Practical Exercises on Seismic Interpretation and Mapping
DAY 4 – Well-Seismic Tie and Integration
Morning Session: Acoustic Impedance and Synthetic Seismograms
- Generating Acoustic Impedance
- Creating Synthetic Seismograms
- Extracting Seismic Traces at Well Locations
Afternoon Session: Well-Seismic Tie and Final Applications
- Performing Well-Seismic Tie
- Practical Applications and Case Studies
- Q&A Session and Course Wrap-Up
Our Trainer is a geologist and data scientist with advanced expertise in Artificial Intelligence (AI), Python, and Machine Learning (ML), particularly in geology and petroleum geoscience. He has developed AI-driven tools like Lentera_2 for geomechanics and Img-to-Seis for seismic data conversion. Epo has led projects using deep learning for fossil identification and hydrocarbon prospectivity, leveraging large datasets for reservoir modeling. Proficient in Python, he conducts workshops on its application in geology and has published on ML-based lithology prediction and facies identification. His work bridges geoscience and data science, showcasing innovative AI/ML solutions for exploration and reservoir development.
For more details, please contact our administrator