--> Abstract: Estimation of Sand/Shale Ratio in Interbedded Formations Using Neural Network Processing of Multiple Seismic Attributes, by S. A. Katz, G. V. Chilingar, V. Benenson, L. G. Kiryukhin, and T. Smolenchuk; #90928 (1999).
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KATZ, SIMON A.1, GEORGE V. CHILINGAR1, VLADIMIR BENENSON2, LEONID G. KIRYUKHIN3, and TATIANA SMOLENCHUK3
1 USC
2 Academy of Natural Sciences, Russia
3 NSC

Abstract: Estimation of Sand/Shale Ratio in Interbedded Formations Using Neural Network Processing of Multiple Previous HitSeismicNext Hit Previous HitAttributesNext Hit

Summary

The problem of integral characterization of sandstone reservoir rocks in terrigenous geologic sections is of complex nature especially when individual sand layers are I to 10 m in thickness. Thin-bedded sand-shale oil-gas-bearing formations are encountered in many parts of the world including: Gulf of Mexico, Western Siberia, Western Kazakhstan, Eastern China, and Sakhalin Island of Russia.

New method for integral evaluation of interbedded formations was developed and tested on synthetic Previous HitseismicNext Hit data. It is based on the processing of multiple Previous HitseismicNext Hit Previous HitattributesNext Hit by biradial-basis neural networks (BRB NN) which may be trained on recorded and synthetic Previous HitseismicNext Hit data. This approach is especially efficient when the studied formation is a combination of thin layers having alternating acoustic impedances and with thicknesses of individual layers beyond the resolution of Previous HitseismicTop interpretation.

AAPG Search and Discovery Article #90928©1999 AAPG Annual Convention, San Antonio, Texas