Waveform Classification Workflow using Machine Learning with SeisEarth

This course teaches you how to use a unique machine learning approach to delineate subtle variations in the seismic response associated with reservoir characteristics with Aspen SeisEarth. You will understand how to use the Waveform Classification workflow in Integrated Canvas, which uses a neural network approach to create facies volumes from input seismic attributes.

Audience:

SeisEarth users, interpreters

Training Details

  • Course Id:

    SEI113

  • Duration:

    1 day(s)

  • CEUs Awarded:

    0.7

  • Level:

    Introductory

Approach

  • Instruction on basic topics
  • Discussion about the general approach
  • Instructor-guided demonstrations of features
  • Hands-on workshops that apply learned concepts
  • Detailed course notes

Pre-requisites

Agenda

  • Introduction
  • How It Works
  • The Waveform Classification in Integrated Canvas
    • Unsupervised Waveform Classification
    • Supervising the Waveform Classification using Seismic Traces or Well Logs
    • Supervising the Waveform Classification using a 2D (Wedge) Model
  • Next Steps?
  • Appendices
    • Using Workflows in Integrated Canvas
    • Preparing the Data and Displays for the Exercises
    • Using PCA During the Training and Classification Process

Register for a Class

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Aspen Technology, Inc. awards Continuing Education Units (CEUs) for training classes conducted by our organization. One CEU is granted for every 10 hours of class participation.