Prediction of Fluid–Brine Event Zones by Artificial Intelligence Methods Based on New Generation RTH Seismic Attributes and Drilling Data at the Kovykta Gas Condensate Field

Prediction of Fluid–Brine Event Zones by Artificial Intelligence Methods Based on New Generation RTH Seismic Attributes and Drilling Data at the Kovykta Gas Condensate Field

A new method for predicting lithofacies, gas, fluid and brine zones, and zones with abnormally high reservoir pressure, as well as the petrophysical properties of rocks using artificial intelligence methods, based on a family of new seismic attributes of the RTH (reverse time holography) method and...

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Bibliographic Details
Published in:Doklady earth sciences Vol. 514; no. 1; pp. 105 - 113
Main Authors: Bugaev, A. S., Erokhin, G. N., Ryabykh, S. A., Smirnov, A. S.
Format: Journal Article
Language:English
Published: Moscow Pleiades Publishing 2024
Springer Nature B.V
Subjects:
Artificial intelligence
Brines
Condensates
Drilling
Earth and Environmental Science
Earth Sciences
Geology
Geophysics
Holography
Lithofacies
Predictions
Rock properties
Seismic data
Seismological data
Well drilling
prediction
seismic exploration
seismic attributes
brine
artificial intelligence
RTH
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Summary:A new method for predicting lithofacies, gas, fluid and brine zones, and zones with abnormally high reservoir pressure, as well as the petrophysical properties of rocks using artificial intelligence methods, based on a family of new seismic attributes of the RTH (reverse time holography) method and well drilling data is proposed. The main difference between RTH attributes and conventional ones obtained by migration transformation is their voxel nature and hyperattribution. This turned out to be a key advantage of the new approach to solving problems of geological prediction by artificial intelligence methods. The results of applying a new method for processing and interpreting modern 3D seismic data, as well as geological prediction based on it for the area of intense brine occurrence at the Kovykta gas condensate field, are presented.
ISSN:1028-334X
1531-8354
DOI:10.1134/S1028334X23602389