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.
In this 10-part video series, leading experts demonstrate the applications of attributes. The $99 registration fee allows access to all course content – both videos and powerpoints, for 7 days. Click the link to purchase your access.
Course Learning Objectives:
- Assess the appropriate seismic attributes and associated parameters to improve images for different geologic features.
- Systematically incorporate seismic attribute evaluations in a comprehensive interpretation of the environment of deposition.
- Utilize Attribute Generator in Paradise software to generate appropriate attribute volumes.
- Conduct multi-attribute analysis via different visualization tools and machine learning techniques.
- Faulting and Folds
- Seismic stratigraphy
- Architectural elements of fluvial-deltaic systems
- Architectural elements of deep water systems
- Shale resource drilling (“geo”) hazards
- Attribute and suboptimum seismic data
- Examples of Multi-attribute visualization vs. Mulit-attribute SOM
1. Faults and Folds
Attributes Computed from SuboptimuThis 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
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
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
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.
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.
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 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
Dr. Kurt Marfurt will discuss and demonstrate the pitfalls of seismic data processing and how different processing affects attribute results.
9. Multi-Attribute SOM
Rocky Roden will illustrate the concept of Self Organizing Map and the application with different case studies.