Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
8124921 | Journal of Petroleum Science and Engineering | 2018 | 14 Pages |
Abstract
We present a method for predicting rock types. The method is based on continuous high-resolution thermal logging along full-size core samples and being applied for rocks from a major unconventional formation. The method utilizes spatial spectral decomposition and machine learning approaches allowing automatic classification of the core samples over lithological groups within an isolated stratigraphic depth interval of a wellbore. The core samples are basically classified to the particular lithotypes by means of spectral representation of profiles of thermal properties obtained by a modern contactless method.
Related Topics
Physical Sciences and Engineering
Earth and Planetary Sciences
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Authors
Yury Meshalkin, Dmitry Koroteev, Evgeniy Popov, Evgeny Chekhonin, Yury Popov,