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Automatic Lithofacies Classification From Well-Logs Data Using The Walsh Transform Combined With The Self-Organizing Map
- Publisher: European Association of Geoscientists & Engineers
- Source: Conference Proceedings, ECMOR XVI - 16th European Conference on the Mathematics of Oil Recovery, Sep 2018, Volume 2018, p.1 - 9
Abstract
The main goal of this paper is to implement an automatic lithofacies classification algorithm based on the Walsh transform and the Kohonen’s Self-Organizing Map neural network machine. The first stage is to apply the Walsh transform to a set of well-logs data, the output is a set of different segmentations each one is based on the type of the well-log. The second stage is to use the different output of the Walsh transform applied to different logs as an input, the output of the SOM machine is the different lithological classes. Application to well-logs data recorded in vertical wells located in the Algeria Sahara clearly shows that the output of the proposed combination is more powerful compared to the Self-Organizing map with the well-logs data as an input since this combination is able to attenuate the high frequency components in the well-logs data which can affect the output of neural network machines.