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Shape-based Well Log Auto-interpretation
By Schlumberger
Plug-in Attributes
Platform:
Petrel
Lifecycle
Exploration
ECCN:
Russia Origin, EAR99
Version
  • 2019 | 2020 | 2021
Supporting Documents
Installation Guide
Release Notes
User Manual
Others
Overview
This plug-in is designed to predict logs based on a supervised machine learning algorithm. Prediction is done on a field scale based on an ensemble of Decision Trees algorithm associated with gradient boosting. This method substantially increases the quality of the classification that is a key to further modelling and simulations, which help to reduce the risk of inefficient operations.
Specifications
  • Data integrity assessment
  • Automatic data scaling
  • Identification and correction of gaps in data
  • Log processing
  • Feature engineering
  • Tuning hyperparameters on the validated set of data
Features
A rather straightforward algorithm: select data sources (wells), select desired logs, specify parameters and filters, and get the result. Saved search and advanced input/output filtering tricks can be applied. Custom shifts can be used for different logs.