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Author:

Zhang Rongxi (Zhang Rongxi.)

Indexed by:

CPCI-S EI Scopus

Abstract:

Sequence stratigraphy is a great contribution to the analysis and characterization of oil reservoirs. But how to divide sequence stratigraphic units quantitatively is the urgent problem to solve. Well logging signal representing lithology and physical properties embrace much information related to sedimentary cycles, and wavelet analysis of signal has good time-frequency local adjustable performance to be able to identified different frequency cycles. So we can draw the conclusion that the sediment cycles in different periods can be identified by using wavelet and analysis of well log curves. In terms of the properties of the wavelet bases and the characteristics of logging signals, dmey 12 is chosen for the cycle classification of logging curve. The research shows that the wavelet analysis is a helpful complementary technique for the location of stratigraphic sequences.

Keyword:

dmey stratigraphic sequence well logging Wavelet transform

Author Community:

  • [ 1 ] [Zhang Rongxi]Beijing Univ Technol, Coll Comp Sci, Beijing, Peoples R China

Reprint Author's Address:

  • [Zhang Rongxi]Beijing Univ Technol, Coll Comp Sci, Beijing, Peoples R China

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Source :

2015 IEEE INTERNATIONAL CONFERENCE ON COMPUTATIONAL INTELLIGENCE AND COMMUNICATION TECHNOLOGY CICT 2015

Year: 2015

Page: 18-21

Language: English

Cited Count:

WoS CC Cited Count: 2

SCOPUS Cited Count: 1

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 0

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