Geolog - Electrofacies Analysis (Facimage)
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.
Background in geosciences, some prior experience with Geolog® is recommended.
Who Should Attend?
Geolog users, new Facimage users
- Define Objectives
- Data Preparation
- Basic Workflow
- Create a Facimage Project
- Insert a Cluster Model
- Facies Propagation
- 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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