Method of Creation of “Core-Gisseismic Attributes” Dependences With Use of Trainable Neural Networks
1 Krasnoyarsk Research Institute of Geology and Raw Materials, 660049, Krasnoyarsk, Russia
2 International Laboratory of Vision Systems, Tomsk State University, 634050, Tomsk, Russia
* Corresponding author: email@example.com
The study describes methodological techniques and results of geophysical well logging and seismic data interpretation by means of trainable neural networks. Objects of research are wells and seismic materials of Talakan field. The article also presents forecast of construction and reservoir properties of Osa horizon. The paper gives an example of creation of geological (lithological -facial) model of the field based on developed methodical techniques of complex interpretation of geologicgeophysical data by trainable neural network. The constructed lithological -facial model allows specifying a geological structure of the field. The developed methodical techniques and the trained neural networks may be applied to adjacent sites for research of carbonate horizons.
© The Authors, published by EDP Sciences, 2016
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.