Geophysics for Data Scientists
Consultant/Trainer: Jaap Mondt
The Petrogenium (in collaboration with EPTS) Geophysics for Data Scientists participants will gain practical experience applying machine and deep learning techniques to geophysical problems. Building on their existing knowledge of mathematics and statistics, they will explore advanced topics in seismic and non-seismic data acquisition, processing, and interpretation. By the end of the course, they will be able to apply modern AI and deep learning workflows to predict lithology, pore fluids, and facies, gaining a solid, practice-driven understanding of data-driven geophysical interpretation.
Participants
This Petrogenium course aims at Data Scientists who will be cooperating with geoscientists to develop AI methods for exploration and development of hydrocarbons or mineral resources. Also, application for geothermal and CO2 storage are discussed.
Learning Objectives
At the end of the course participants will have a clear idea of what goes on in Geophysics and how Artificial Intelligence will impact the future of Geosciences. Interactive quizzes using “Mentimeter” are used to enhance the learning.
Day 1
1. Program, Biography, Teams
2. Moodle, Geophysical Methods
3. Seismic Data
4. Non-Seismic Data
5. Ex Shot raypaths
6. Gravity
7. Magnetics
8. Ex Sampling and Aliasing
9. Ex Field Record
10. Quiz 1
11. Team A preparation
Day 2
1. Team A: Summary Day 1
2. Seismic Acquisition
3. Ex Gravity & Magnetics
4. Wave propagation
5. Ex Reflection & Transmissio
6. Seismic Processing
7. Stacking & Migration
8. Ex Correlation & Convolution
9. Ex Diffraction
10. Quiz 2
11. Team B preparation
Day 3
1. Team B: Summary Day 2
2. Ex Migration diffraction curves
3. Quantitative Interpretation
4. Ex Migration wavefronts,
5. AVO/AVA
6. Ex Time-Depth-Conversion: Stretch
7. Ex Amplitudes
8. Ex Time-Depth-Conversion: Raytracing
9. Ex Direct Hydrocarbon Indicators
10. Quiz 3
11. Team C preparation
Day 4
1. Team C: Summary Day
2. Machine Learning for Geophysics
3. Ex Lith Classification
4. Clustering
5. Ex Facies Clustering
6. DL 4D Brazil
7. Ex Facies-Merged_Reload_Test-Well_Classification
8. Deep Learning for Geophysics
9. Ex Oil Saturation Regression
10. Quiz 4
11. Team D preparation
Day 5
1. Team D: Summary Day 4
2. You ain’t seen nothing yet
3. Ex Salt-Segmentation-CNN
4. Semi-supervised Learning in Geophysics
5. Ex Salt-Segmentation-U-net
6. Inversion versus AI
7. VOI-Geothermal & CO2 Sequestration
8. Ex AI Inversion
9. Quiz 5
10. ChatGPT: questions you never dared to ask!
Programme
Day 1
1. Program, Biography, Teams
2. Moodle, Geophysical Methods
3. Seismic Data
4. Non-Seismic Data
5. Ex Shot raypaths
6. Gravity
7. Magnetics
8. Ex Sampling and Aliasing
9. Ex Field Record
10. Quiz 1
11. Team A preparation
Day 2
1. Team A: Summary Day 1
2. Seismic Acquisition
3. Ex Gravity & Magnetics
4. Wave propagation
5. Ex Reflection & Transmissio
6. Seismic Processing
7. Stacking & Migration
8. Ex Correlation & Convolution
9. Ex Diffraction
10. Quiz 2
11. Team B preparation
Day 3
1. Team B: Summary Day 2
2. Ex Migration diffraction curves
3. Quantitative Interpretation
4. Ex Migration wavefronts,
5. AVO/AVA
6. Ex Time-Depth-Conversion: Stretch
7. Ex Amplitudes
8. Ex Time-Depth-Conversion: Raytracing
9. Ex Direct Hydrocarbon Indicators
10. Quiz 3
11. Team C preparation
Day 4
1. Team C: Summary Day
2. Machine Learning for Geophysics
3. Ex Lith Classification
4. Clustering
5. Ex Facies Clustering
6. DL 4D Brazil
7. Ex Facies-Merged_Reload_Test-Well_Classification
8. Deep Learning for Geophysics
9. Ex Oil Saturation Regression
10. Quiz 4
11. Team D preparation
Day 5
1. Team D: Summary Day 4
2. You ain’t seen nothing yet
3. Ex Salt-Segmentation-CNN
4. Semi-supervised Learning in Geophysics
5. Ex Salt-Segmentation-U-net
6. Inversion versus AI
7. VOI-Geothermal & CO2 Sequestration
8. Ex AI Inversion
9. Quiz 5
10. ChatGPT: questions you never dared to ask!