Watch videos of Presentations from SEG 2017
Using Attributes to Interpret the Environment of Deposition - A Video Course. Taught by Kurt Marfurt, Rocky Roden, and ChingWen Chen
Dr. Kurt Marfurt and Dr. Tom Smith featured in the July edition of AOGR on Machine Learning and Multi-Attribute Analysis
Rocky Roden and Ching Wen Chen in May edition of First Break - Interpretation of DHI Characteristics using Machine Learning
Seismic interpretation and machine learning by Rocky Roden and Deborah Sacrey, GeoExPro, December 2016

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Course Overview


 

 

 

 

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Course Overview


 

 

 

 

Course Overview

The 10 videos below have a total run-time of 4 hours and 45 minutes. They can be watched at your own pace, but we do recommend they be watched sequentially.  Below, you will see each segment has the video instruction on the left and the slides on the right.  If you have two monitors and wish to view slides along with the video, both windows can be undocked and expanded to fit each screen. Each video should be stopped before going on to the next.  

Please remember you have 7 days to complete the course, starting from the date and time you registered for the course. 

Summary

The evaluation of seismic attributes is a powerful tool in the interpretation of different geologic environments of deposition.  Seismic attributes, specifically geometric and spectral decomposition attributes, provide a framework for interpreting geologic features that define depositional environments.  This video course identifies the appropriate seismic attributes for various geologic settings and describes how these attributes are applied. Lecture and demonstrations cover the use of attributes in interpretation workflows and manipulate attribute parameters to highlight geologic features.  The last video segment of the course describes how sets of attributes are analyzed and classified using multi-attribute, Machine Learning processes to extract more information from the seismic response. 

Learning Outcomes:
 
Participants will learn to:

  1. Assess the appropriate seismic attributes and associated parameters to improve images for different geologic features.
  2. Systematically incorporate seismic attribute evaluations in a comprehensive interpretation of the environment of deposition.
  3. Utilize Attribute Generator in Paradise software to generate appropriate attribute volumes.
  4. Conduct multi-attribute analysis via different visualization tools and machine learning techniques.

Introduction


Introduction


Introduction

Review of the course content and the instructors.

 

1. Faults and Folds


1. Faults and Folds


1. Faults and Folds

This chapter will layout the fundamental tools, methodology and concepts for attribute analysis. Curvatures, Dip Scan, Similarity and the associated attributes will be discussed in detail with algorithm and case studies for highlighting faults and folds. The attribute images result from different parameters set will be demonstrated to see the effect on changing the window sizes. 

 

2. Seismic Stratigraphy


2. Seismic Stratigraphy


2. Seismic Stratigraphy

The instructors will demonstrate seismic stratigraphy with reflector convergence volume and different spectral components. Several spectral decomposition and the reflector convergence methods will also be addressed.

 

3. Fluvial-Deltaic Systems


3. Fluvial-Deltaic Systems


3. Fluvial-Deltaic Systems

The instructors propose a list of attributes that will bring out geologic features in fluvial-deltaic system. 3D geometric attributes and spectral decomposition attribute volumes will be discussed in detail and applied with multi-attribute visualization techniques. The methods of energy-weighted amplitude gradients and texture (glcm) attributes will be addressed.

 

4. Shallow and Deepwater Depositional Systems


4. Shallow and Deepwater Depositional Systems


4. Shallow and Deepwater Depositional Systems

The instructors will demonstrate the use of geometric attributes and spectral decomposition for channels, mass transport complexes and shale dewatering features. Properties of the geologic features in different regions will be highlighted by single attribute or multi-attribute visualization techniques.

 

5. Diapirs


5. Diapirs


5. Diapirs

The instructors will illustrate the application of geometrical attributes for mapping diapir structures and the associated faults and slumps. Reflector convergence will be utilized for mapping onlaps onto diapirs.

 

6. Carbonates


6. Carbonates


6. Carbonates

This chapter will address the geomorphology of carbonate environments in different regions. The attributes and visualization techniques to highlight those carbonate features will also be discussed. 

 

7. Mapping Fractures and Geohazards in Unconventional Resevoirs


7. Mapping Fractures and Geohazards in Unconventional Resevoirs


7. Mapping Fractures and Geohazards in Unconventional Reservoirs

Dr. Kurt Marfurt will illustrate the features such as karst and fracture system that could become geohazards for drilling activities. He will also discuss the development of nature fractures and how attributes can bring out different properties of the fracture system.

 

8. Attributes Computed from Suboptimum Seismic Data


8. Attributes Computed from Suboptimum Seismic Data


8. Attributes Computed from Suboptimum Seismic Data

Dr. Kurt Marfurt will discuss and demonstrate the pitfalls of seismic data processing and how different processing affects attribute results.

 

9. Multi-Attribute SOMRR


9. Multi-Attribute SOMRR


9. Multi-Attribute SOM

Rocky Roden will illustrate the concept of Self Organizing Map and the application with different case studies.