ABSTRACT

In this work we describe a machine learning pipeline for facies classification based on wireline logging measurements. The algorithm has been designed to work even with a relatively small training set and amount of features. The method is based on a gradient boosting classifier which demonstrated to be effective in such a circumstance. A key aspect of the algorithm is feature augmentation, which resulted in a significant boost in accuracy.

The algorithm has been tested also through participation to the SEG machine learning contest.

Presentation Date: Wednesday, September 27, 2017

Start Time: 3:05 PM

Location: 350D

Presentation Type: ORAL

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