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Geolog - Electrofacies Analysis (Facimage)

Objectives:
This course covers the Facimage functionality in Geolog.  It introduces Facimage methodology and provides hands-on experience with electrofacies analysis and data modeling. It focuses on Facimage MRGC (Multi Resolution Graph Based Clustering) and KNN (K-Nearest Neighbor) approach. This method allows a simple, fast, and effective integration of all types of petrophysical and geological information: conventional logs, array and image logs, core measurement, and core description. This training course teaches you how to:
• Identify and select Training Datasets for use with the application dataset.
• Analyze Training Datasets for coherence with the application dataset.
• Perform Facies propagation to create electrofacies.
• Perform log prediction: log reconstruction and core data prediction.
• Perform comparison among cluster models using various methods.

Duration:
2 days

Prerequisites:
Background in geosciences, some prior experience with Geolog® is recommended.

Who Should Attend?
Geolog users, new Facimage users

Contents:

  • Define Objectives
  • Data Preparation
  • Basic Workflow
    • Create a Facimage Project
    • Insert a Cluster Model
    • Facies Propagation
  • Features
  • Training Data
  • Comparing MRGC Electrofacies to a Lithology Log
  • Similarity Modeling
  • Log Prediction
  • Electrofacies Ordering -CFSOM
  • NMR T2 Electrofacies
  • Synthetic Clustering

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