The digital learning ecosystem An efficient management approach to capability development, delivering smarter teams, improved productivity and better business outcome for the managers.
Bridging industry with academia An immersive and collaborative learning experience event, using OilSim simulator, providing highly relevant industry knowledge and soft skills.
The digital learning ecosystem Digitally and seamlessly connecting you, the learner, with pertinent learning objects and related technologies ensuring systematic, engaging and continued learning.
Industry and client recognition
Best Outreach Program Finalist: WorldOil Awards
Overall Customer Satisfaction Score
Training provider of the year: 2013, 14 and 15
Upstream learning simulator With more than 50,000 participants instructed in various disciplines, data driven OilSim runs real-world oil and gas business scenarios and technical challenges.
Engaging. Educational. EnjoyableUpstream learning simulator With more than 50,000 participants instructed in various disciplines, data driven OilSim runs real-world oil and gas business scenarios and technical challenges.
Engaging. Educational. EnjoyableBridging industry with academia An immersive and collaborative learning experience event, using OilSim simulator, providing highly relevant industry knowledge and soft skills.
The digital learning ecosystem Digitally and seamlessly connecting you, the learner, with pertinent learning objects and related technologies ensuring systematic, engaging and continued learning.
We’re here to help!
Ask a question or leave a
comment using our Contact Us
form.
Upstream learning simulator With more than 50,000 participants instructed in various disciplines, data driven OilSim runs real-world oil and gas business scenarios and technical challenges.
Engaging. Educational. EnjoyableUpstream learning simulator With more than 50,000 participants instructed in various disciplines, data driven OilSim runs real-world oil and gas business scenarios and technical challenges.
Engaging. Educational. EnjoyableBridging industry with academia An immersive and collaborative learning experience event, using OilSim simulator, providing highly relevant industry knowledge and soft skills.
Develop measurable skills and capabilities
Depth conversion (domain conversion) of seismic time interpretations and related data within Petrel is a critical skill set for interpreters. However, there is no single methodology that is optimal for all cases, since the available seismic and geologic control varies in quantity and quality within each project. To impart an effective approach to depth conversion, the first part of this course prioritizes understanding the nature of velocity fields and practical approaches to velocity representation. Next, present appropriate (vertical) time-to-depth conversion methods suitable for time migration in case history and exercise form. Review single-layer and more sophisticated multi-layer approaches along with structural-uncertainty analysis.
Depth conversion must also embrace the process of database validation. The database QC issues reviewed will include incorrect well locations and deviations, improper assessment of seismic polarity and phase, mis-correlated seismic horizons, and inconsistent formation tops. The issues above compromise the interpretation, introduce distortions in the implied velocity field, and can result in false structures. Next, address database validation via the formation of synthetic seismograms to confirm horizon correlations and the use of intuitive QCs such as seismic horizon versus well-top cross plots to detect inconsistencies.
Prestack depth migration is now commonplace, and there is always the need to calibrate the depth volumes with well tops. We will leverage the same basic QCs and methods used for vertical time-to-depth conversion to validate the fidelity of the formation tops and the seismic depth surfaces used for calibration. This is particularly important during anisotropic depth migration where inconsistencies between well control and the seismic interpretation impact the estimation of anisotropic parameters, resulting in a compromised depth-imaging project.
This course emphasizes the formation of velocity models appropriate for the available data. This is in context to creating Petrel Velocity Models suitable for initializing reservoir characterization employing depth-calibrated seismic inversions and other attribute cubes precisely integrated with the well information. Finally, cover structural uncertainty analysis using various approaches to provide a critical metric for depth estimation accuracy.
The course agenda can be shortened if required.
Module 1: Overview of Depth Conversion
Learning Objectives and Importance:
Topics:
Module 2: Sources of Velocity
Learning Objectives and Importance:
Topics:
Module 3: Defining Velocity Types
Learning Objectives and Importance:
Topics:
Module 4: Functional Representation of Velocities
Learning Objectives and Importance:
Topics:
Module 5: Gridded Representation of Velocities
Learning Objectives and Importance:
Topics:
Learning Objectives and Importance:
Topics:
Module 7: Well and Seismic Data Integration
Learning Objectives and Importance:
Topics:
Learning Objectives and Importance:
Topics:
Module 9: Vertical Time-to-Depth Conversion (Advanced)
Learning Objectives and Importance:
Topics:
Module 10: Petrel Models and Uncertainty Analysis
Learning Objectives and Importance:
Topics:
Module 11: Pitfalls of Vertical Depth Conversion
Learning Objectives and Importance:
Topics:
Module 12: Calibration of Depth Migration with Well Tops
Learning Objectives and Importance:
Topics:
Geoscientists involved in seismic interpretation and subsequent time-to-depth conversion or well-top calibration of depth-migration and inversion data.
Attendees will gain an understanding of depth conversion methodologies, QCs for validating the methods employed, and tools for quantitative-uncertainty estimation. They will also learn to:
Petrel Fundamentals and Petrel Geophysics courses.
Your course has been added to the wishlist
Customize your own learning journey and track your progress when you start using a defined learning path.