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Method of Creation of 'Core-Gisseismic Attributes' Dependences With Use of Trainable Neural Networks

Bibliographic Details
Title: Method of Creation of 'Core-Gisseismic Attributes' Dependences With Use of Trainable Neural Networks
Authors: Gafurov, Denis, Gafurov, Oleg
Source: MATEC Web of Conferences, Vol 79, p 01055 (2016)
MATEC Web of conferences. 2016. Vol. 79. P. 01055 (1-10)
Publisher Information: EDP Sciences, 2016.
Publication Year: 2016
Subject Terms: геофизический каротаж, Талаканское нефтегазоконденсатное месторождение, TA1-2040, Engineering (General). Civil engineering (General), литолого-фациальные модели
Description: 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.
Document Type: Article
Other literature type
File Description: application/pdf
ISSN: 2261-236X
DOI: 10.1051/matecconf/20167901055
Access URL: https://www.matec-conferences.org/articles/matecconf/pdf/2016/42/matecconf_imet2016_01055.pdf
https://doaj.org/article/1064b2113a924e75b0ee74a57d509032
http://vital.lib.tsu.ru/vital/access/manager/Repository/vtls:000616437
Rights: CC BY
Accession Number: edsair.doi.dedup.....a494048507da99f12bc43d385c44dafc
Database: OpenAIRE
Description
ISSN:2261236X
DOI:10.1051/matecconf/20167901055