Practical Quantitative Interpretation (PQI)
Utilizing Pre-Stack Seismic Data for Rock Physics and Classification
Traditional seismic processing involves “stacking” seismic traces. Although effective in reducing noise, this procedure eliminates valuable information contained within the “pre-stack” seismic volume. Quantitative interpretation (QI) is the modern way to leverage pre-stack seismic data and, combined with rock physics, reveal rock properties and classify lithologies. Unique properties within a zone of interest can then be correlated to production performance to drive field development planning.
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Chapter 1 - Overview of Quantitative Interpretation
Chapter 2 - Seismic Data
2.01 Seismic Data
2.02 Seismic Data - Well Ties
2.03 Seismic Data Condition and Conditioning
2.04 Case Study - Can Interpolation Improve QI?
2.05 AVO
2.06 Velocity Modeling
2.07a AVO Tutorial
2.07 Sonic Log
2.08 Inversion
2.09 Pre-stack Inversion
2.10 Case Study
2.11a Inversion Tutorial
2.11 Stochastic Inversion
Chapter 3 - Classification Using QI
3.01 Multi-Attribute Analysis
3.02 Classification Intro
3.03a Classification Example
3.03 Classification
Chapter 4 - Advanced Topics
4.01 4D Reservoir Monitoring
4.02 Multi Component Data
4.03 QI Summary
Chapter 1 - Overview of Quantitative Interpretation
Chapter 2 - Seismic Data
2.01 Seismic Data
2.02 Seismic Data - Well Ties
2.03 Seismic Data Condition and Conditioning
2.04 Case Study - Can Interpolation Improve QI?
2.05 AVO
2.06 Velocity Modeling
2.07a AVO Tutorial
2.07 Sonic Log
2.08 Inversion
2.09 Pre-stack Inversion
2.10 Case Study
2.11a Inversion Tutorial
2.11 Stochastic Inversion
Chapter 3 - Classification Using QI
3.01 Multi-Attribute Analysis
3.02 Classification Intro
3.03a Classification Example
3.03 Classification
Chapter 4 - Advanced Topics
4.01 4D Reservoir Monitoring
4.02 Multi Component Data
4.03 QI Summary
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