Application of convolutional neural networks in the lithological description of the core

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Abstract

The article describes a method for training a convolutional neural network for rock lithology recognition based on images of core material. High Resolution (Hi-Res) photos were used for training models. The principles of convolutional neural networks and their practical application in geology are considered. As an outcome of this work, the model of neural networks for recognizing rock lithology was created and applied in practice using a smartphone. It was established that many ML and DL technologies potentially can be applicable for oil and gas industry.

About the authors

I. D. Murtazayev

ТОО «КМГ Инжиниринг»

Author for correspondence.
Email: i.murtazayev@niikmg.kz

инженер департамента промысловой геологи и геологического моделирования

Kazakhstan, г. Нур-Султан

N. Zh. Konyssov

ТОО «КМГ Инжиниринг»

Email: n.konyssov@niikmg.kz

старший инженер департамента промысловой геологи и геологического моделирования

Kazakhstan, г. Нур-Султан

N. B. Saliyev

ТОО «КМГ Инжиниринг»

Email: n.saliyev@niikmg.kz

директор департамента промысловой геологи и геологического моделирования

Kazakhstan, г. Нур-Султан

References

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  3. https://ru.wikipedia.org/wiki/Свёрточная_нейронная_сеть.
  4. Aphex34 – собственная работа: https://commons.wikimedia.org/w/index.php?curid=45679374.
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  8. Утилита для обучения ИНС TeachebleMachine. https://github.com/googlecreativelab/teachablemachine-community.
  9. Andrew G. Howard, Menglong Zhu, Bo Chen, Dmitry Kalenichenko, Weijun Wang, Tobias Weyand, Marco Andreetto, Hartwig Adam MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications. https://arxiv.org/abs/1704.04861.
  10. Приложение TFL Classify. https://github.com/tensorflow/examples/tree/master/lite/examples/image_classification/android.
  11. Портативный формат TensorFlow для мобильных устройств. https://www.tensorflow.org/lite.

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Copyright (c) 2020 Murtazayev I.D., Konyssov N.Z., Saliyev N.B.

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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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