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
Online Access:	Get full text
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