COURSE OVERVIEW
Rock physics links seismic properties to the underlying rock and fluid characteristics, enabling better understanding of subsurface reservoirs. It integrates geology, petrophysics, and geophysics to interpret how variations in lithology, porosity, and fluids affect seismic responses. This makes it a key tool for improving reservoir characterization, reducing uncertainty, and supporting exploration and production decisions.
The course emphasizes rock-physics model building and ways to use and verify the models using seismic data. It starts with designing effective media in interactive notebooks with Python code using Differential Effective Medium (DEM). In DEM we start with an effective background medium and successively change the rock properties. The module allows the calculation of elastic parameters for different proportions of lithology mixtures and by adding sequentially different kinds of features. For clastic reservoirs interparticle and aligned cracks describe an anisotropic medium quite well, but for carbonates vugs, solution cavities, might be added. It will be shown in an exercise that the order in which features are added influences the end result. Then various aspects of AVA will be discussed: forward modelling, attribute ranking and inversion aiming at a further understanding of what can be derived from seismic in terms of reservoir properties, be it clastics (sand/shale), carbonates (limestone/dolomite) or unconventional (shale) in combination with rock physics. Each day the participants are invited to give a summary of the main learning points of the previous day and the day will be closed by a quiz, again empathizing the learning points.
COURSE SCHEDULE
| Code | Date | Location | price (€) |
|---|---|---|---|
| GEO 154 | 15 - 19 Jun 2026 | Online | 3300 |
| GEO 154 | 14 - 18 Sep 2026 | Amsterdam | 4400 |
COURSE OUTLINE
5 days
Day 1:
o Geophysical Methods
o Comparison Rock-Physics Models
o Seismic for Rock-Physics
o Effective Media / DEM
o Colab Voight Reuss Hill
Day 2:
o AI, EI, EEI, EPI
o Ex: Colab DEM Shale
o Inhomogeneity, Anisotropy
o EAGE Improved rock property estimation from joint inversion
o Ex: Colab DEM Sandstone
o Carbonate Iran Sharifi
o Ex Colab DEM Carbonate
Day 3:
o Lambda-Mu-Rho
o Ex: Excel AVA HTI Ortho
o Demo Colab AVO Tuning
o Ex: Colab Clastic Additions
o AVA & Well Seismic Profiling
o Videos: EAGE AVO
o Ex: Colab Carbonate Additions
o AVA & Facies Prediction
o Ex: Colab AVA Clastic
Day 4:
o AVAz Fractures, Machine learning
o Ex: Colab Permeability Clastic
o ML AVO Tutorial II, Inversion
o Colab AVO Classes
o Videos: Inversion vs ML
o Ex: AVA Inversion I
o SOM
o Ex: Colab AVA 5-Attributes Ranking
Day 5:
o AVA & Well Seismic Profiling
o Ex: Colab Permeability Carbonate
o New Rock-Physics model
o Ex: Colab AVA Attribute Expansion
o Video: You ain’t seen nothing yet
o Ex Colab AVA All-Attributes Ranking
o Ex Large Language Model (LLM)
INSTRUCTOR
Instructor Profile
Instructor has a PhD from Utrecht University on “Full wave theory and the structure of the lower mantle” and joined Shell Research in the Netherlands to develop methods to predict lithology and pore-fluid based on seismic, petrophysical and geological data. Subsequently worked for Shell in London to interpret seismic data from the Central North Sea Graben.
He has extensive experience in quantitative interpretation, leading teams in well seismic profiling and advanced 3D interpretation using statistical and pattern recognition methods. He later contributed to geophysics training and academia, while developing potential field and EM methods for hydrocarbon exploration. His work includes leadership in CSEM technology for marine acquisition, processing, and interpretation.
FAQ
DESIGNED FOR
The course is designed for geoscientists active in promoting and designing supportive non-seismic data acquisition and the integration with seismic data using joint inversion methods.
COURSE LEVEL
o Intermediate
LEARNING OBJECTIVES
o Understand the fundamental principles of rock physics and effective media modelling for subsurface characterization
o Apply rock-physics models and AVA/AVO analysis to interpret seismic responses and reservoir properties
o Evaluate the effects of lithology, fractures, anisotropy, and fluids on elastic and seismic properties
o Integrate rock physics, seismic data, and machine learning techniques for quantitative reservoir interpretation and facies prediction
REGISTER
Registration is now OPEN!
Ph.D. students, group and early bird registrants are eligible to DISCOUNT!
For more details and registration please send email to: register@petro-teach.com
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