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Python for Oil & Gas Professionals
After completing this course, participants will have the ability to run well log, basic petrophysics, machine learning, seismic reading and visualization, seismic interpretation, seismic well tie using Python programming language. The participants with the basic knowledge of this could develop the next level or use another algorithm for geophysical modeling and other practices for geosciences.
Course Info
Schedule
Day 1: Python The Basic
• Python Installation
• Environment Setup
• Containers and lists
• if… for… while… try… except…
• numpy and pandas
• Matplotlib
• Las data loading into/from SqliteDB
• Data Visualization
• Well-log calculation (vsh, phit, phie, sw)
• Basics of Machine Learning
• Several algorithms of ML (KNN, RF, SVM)
• GridSearch CV, accuracy test
Day 2: Seismic Data Handling & Visualization
Introduction to SEG-Y Data Format | Reading and Parsing SEGY Data | Saving & Querrying Seismic Data in SQ Lite Database | Seismic Data Visualization Techniques | Generating Seismic Attributes | Introduction to Seismic Interpretation | Manual Horizon Picking | Fault Picking Basics
Day 3: Advance Seismic Interpretation and Mapping
Advanced Horizon and Fault Picking Techniques | Editing and refining Horizons and Faults | Saving Horizon and Fault Data in Files and Database | Generating Time Structure Maps | Incorporating Faults into Time Structure Maps | Practical Exercises on Seismic Interpretation and Mapping
Day 4: Well Seismic Tie and Integration
Generating Accoustic Impedance | Creating Syntethic Seismograms | Extracting Seismic Traces at Well Locations | Performing Well-Seismic Tie | Practical Applications and Case-Studies | Q&A Session & Wrap-Up
This course is intended for those who want to learn how to use Python programming language to run basic seismic data processing
Epo P. Kusumah
Epo P. Kusumah Have more than 8+ years experience in working and research about subsurface geology, especially petrophysics and reservoir modeling. Some of his scientific papers have been published in national and international publications.