This Petrogenium course aims at Geologists, geophysicists, petroleum and reservoir engineers, involved in exploration and development of hydrocarbon fields. That means not only those involved in the production side but also geoscientists designing the acquisition of seismicandnon-seismic data needed for Quantitative Interpretation.
At the end of the course participants will have a solid foundation in Seismic Quantitative Interpretation. The aim of the course is to provide a solid conceptual understanding without going into mathematical detail. It uses a mixture of lectures, practical exercises and direct (workshop-like) participant involvement, complemented with case histories. Use of laptops for exercises and WIFI internet access in the classroom is mandatory.
1. Biography, Program, Moodle, 52 Things, How a Geophysicist, Teams
2. Geophysical Methods, Seismic Acq & Proc, Workflow, Seismic for QI
3. Exercise: Resolution I (paper)
4. Rock Physics
5. Videos: Rock Physics (26:30)
6. Effective Media
7. Seismic Resolution: Point-Spread or Resolution Functions
8. Exercise: (Resolution) Resolution II (computer)
9. Team a: Preparation Summary of day 1
1. Team a: Summary of day 1
2. Structural & Stratigraphic Interpretation, Tuning: Simmons & Backus
3. Exercise: (Tuning) Tuning Wedge, Tuning AVA (computer)
4. Exercise: Effective Media (paper)
5. Videos: EAGE Gassmann Fluid Replacement, EAGE AVO
6. Effective Media, Anisotropy, AVA
7. Exercise: AVA (computer)
8. Preparation Summary of day 2
1. Team b: Summary of day 2
2. EI, EEI, EPI, Lambda-Mu-Rho
3. Exercises: AVA (ΔRPP, ΔRSS) (computer)
4. Inhomogeneity & Anisotropy
5. ML Tutorial I
6. Exercise: AVA Rps (computer)
7. Videos: EAGE Wave Equation AVO, Activation Functions
8. Exercise: V-NMO-azi
9. Exercis: AVA VTI HTI (computer)
10. Exercise: AVA HTI Ortho (computer)
11. Team c: Preparation Summary of day 3
1. Team c: Summary of day 3
2. AVAz Fractures, Machine learning,
3. Exercise: (Fractures) AVA lith1,lith2 (computer)
4. ML AVO Tutorial II, Inversion
5. Exercise: ML Classification (computer)
6. Videos: Classification, Inversion vs Machine learning I, Clustering
7. Exercise: ML AVA Tutorial II (computer)
8. SOM
9. Exercise: ML Clustering (computer)
10. Supervised, Unsupervised and Semi-Supervised learning
11. Team d: Preparation Summary of day 4
1. Team d: Summary of day 4
2. Videos: Hydrocarbon Indicators, Gassmann
3. Exercise: Gassmann Fluid Replacement (computer)
4. ML Keras, TensorFlow
5. Exercise: ML Regression (computer)
6. Video: You ain’t seen nothing yet.
7. Exercise: Google Colab I
8. Gassmann subsalt rock
9. Exercise: Google Colab II
10. Course evaluation
This course can be tailored and delivered at your own facility — adapted to your specific units, equipment, and team experience level. We come to you, wherever you are in the world.
All content can be customised for awareness, intermediate, or experienced staff. Post-course consultancy and help-desk support is also available.
Request In-House TrainingAll courses can be tailored, combined, or run exclusively for your team — anywhere in the world.
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