Practical Quantitative Interpretation (PQI) Course

Utilizing Pre-Stack Seismic Data for Rock Physics and Classification

Laurie Weston

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Practical Quantitative Interpretation (PQI) is a comprehensive course designed to equip interpreters with a modern approach to seismic data analysis. Unlike traditional seismic processing that stacks traces and loses valuable information, PQI leverages pre-stack seismic data and integrates rock physics to reveal detailed rock properties and classify lithologies. This powerful technique transforms seismic volumes into geological models that improve well planning and production outcomes. The course covers key topics such as seismic attributes, well data analysis, rock physics, classification, and the overall QI workflow. It is structured into fundamentals, intermediate, and advanced levels to progressively build competency in geoscience disciplines.Read more...

Who Should Take This Course
• Oil and gas exploration teams
• Geoscience interpreters and analysts
• Professionals in geology and geophysics
• Individuals involved in field development planning

What You Will Learn
• Workflow and interpretation pitfalls
• Methods for seismic data classification
• Integration of well data and rock physics
• How to transform seismic data into geological models

Why This Course Works
• Increase accuracy of reserve estimations
• Reduce drilling risks and costly mistakes
• Enhance decision-making in oil and gas projects
• Improve well planning and production efficiency

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Course contents

    Chapter 2 - Seismic Data

    2.01 Seismic Data (19 min.)

    2.02 Seismic Data - Well Ties (18 min.)

    2.03 Seismic Data Condition and Conditioning (36 min.)

    2.04 Case Study - Can Interpolation Improve QI? (27 min.)

    2.05 AVO (25 min.)

    2.06 Velocity Modeling (23 min.) Quiz

    2.07 Sonic Log (37 min.) Quiz

    2.07a AVO Tutorial (29 min.)

    2.08 Inversion (31 min.) Quiz

    2.09 Pre-stack Inversion (19 min.)

    2.10 Case Study (17 min.)

    2.11a Stochastic Inversion (9 min.)

    2.11b Inversion Tutorial (16 min.)

    Chapter 3 - Classification Using QI

    3.01 Multi-Attribute Analysis (23 min.)

    3.02 Classification Intro (27 min.)

    3.02a Classification (32 min.) Quiz

    3.02b Classification Example (1:12 hours)

    Chapter 4 - Advanced Topics

    4.01 4D Reservoir Monitoring (9 min.)

    4.02 Multi-Component Data (43 min.)

    4.03 QI Summary (21 min.)