The Interpreter’s Guide to Depth Imaging 

Dr. Scott MacKay       
Duration and formats:
1 day

Course Description

An intuitive approach to understanding the interpretive aspects of depth imaging, and the risk of using time migration. The course reviews depth-conversion goals and compares time and depth migration using case histories.

Next is an overview of depth migration algorithms in common use, Kirchhoff (ray) versus RTM (wave). Industry methodologies are presented for tomographic velocity updates and full-waveform inversion. This course demonstrates intuitive QC sand provides spreadsheet analysis tools for planning and ensuring realistic velocity-resolution goals and stable imaging solutions. The importance of defining the polarity and phase of the seismic is presented as part of the database-validation process used to identify and remove inconsistencies between interpreted surfaces and well tops before deriving anisotropic parameters.

The course continues with a robust approach to well-top calibration of the final depth-imaging deliverables. Freeware is provided to provide a statistical method of depth calibration and estimating depth uncertainty. Finally, there is are view of using attributes from depth imaging for azimuthal stress definition and implementing machine learning for classification and estimation.

Participants’ Profile 

Intended for seismic interpreters incorporating depth imaging intotheir evaluations, and depth-processing imagers looking to betterinteract with interpreters. Training is conducted with a combinationof lectures, demonstrations, and illustrative datasets.

Course Objetives

Upon completion of the course, the participants will be able to: 

• Appreciate time-to-depth conversion methodologies

• Differentiate between time and depth migration

• Distinguish between commonly used depth migration algorithms

• Appraise methods for velocity updating (tomography/FWI) appropriate for the geology

• Define target velocity resolution for tomography and related imaging grids

• Establish consistency between well tops and horizons in an interpretive database

• Plan and review QCs for iterative velocity updates

• Assess the methods used for determining anisotropic parameters

• Perform well-top calibration of depth-imaging volumes

• Evaluate the validity/uncertainty of advanced seismic attributes

• Review practical

Course Outline

Upon completion of the course, the participants will be able to:

1. Review of Vertical Depth Conversion Goals

• Velocity field representation

• Depth-uncertainty analysis and risks of using time migration

2. Time and Depth Migration: Comparisons

• Concepts and contrasts in time and depth migration

3. Depth Migration Algorithms: Theory and Practice

• Kirchhoff, Gaussian Beam, 1-way, and 2-way (Reverse Time)Wave Equation

• Anisotropy and Multi-component considerations

4. Depth Migration: Parameter Selection

• Kirchhoff travel times, aliasing, and aperture

• Wave Equation imaging parameters

5. Tomographic Velocity Analysis and FWI

• Layer- and grid-based ray methods

• Full waveform inversion (FWI) and FWI Imaging

6. Depth Imaging Grids

• Defining the mandatory grids: Image trace spacing and depth increment, travel-time tables, tomographic grid sizes

7. Well/Seismic Database Validation

• Determining seismic data polarity and phase

• Creating synthetic seismogram ties

• Identifying and correcting database inconsistencies

8. Iterative Depth Imaging: Quality Control

• Creation and QC of the initial velocity model

• Iterative tomographic and FWI updates

• Case histories

• Setting up an intuitive review of the iterative velocity-update process

9. Anisotropy

• Anisotropic parameterization (Vz, Delta, Epsilon, VTI/TTI…)

• Initial Vz model, velocity and anisotropic parameter updates

• Multiparameter and Elastic FWI applications

10. Well Calibration

• Conversion of time data to calibrated depth

• Depth uncertainty measures (Stochastic modeling, freeware supplied and demonstrated)

11. Depth-Imaging Attributes

• Azimuthal AVO and other HTI property cubes

• Practical applications of machine-learning algorithms

About the Instructor

Scott MacKay is an independent consultant with over 40 years of experience. He is an acknowledged expert in interpretation, depth conversion, and depth imaging. After graduating from Colorado. School of Mines with an MS in Geophysics he joined a major oilcompany where he worked ten years as an exploration geophysicist.Scott next joined Schlumberger where he became Manager of R&Dand a Schlumberger Advisor. His other roles included World-wideCoordinator for Depth Imaging, Manager of Time-lapse ReservoirCharacterization and Multi-component Imaging. During this time,he earned a PhD in Geology and Geophysics from the University ofHouston. Scott later became an independent consultant workinginternational interpretation projects and advising on the applicationof new technologies and their impact on risk reduction. His mainspecialty is the application of depth imaging to unconventional playsand CCUS planning to quantify reservoir properties. Scott has fiveU.S. patents and numerous publications on applying innovative andpractical solutions to exploration and exploitation challenges.




More information coming soon!