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Detection of hidden reservoirs under strong shielding based on bi‐dimensional empirical mode decomposition and the Teager–Kaiser operator
Author(s) -
Jiang Xudong,
Cao Junxing,
Zu Shaohuan,
Xu Hanqing,
Wang Jun
Publication year - 2021
Publication title -
geophysical prospecting
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.735
H-Index - 79
eISSN - 1365-2478
pISSN - 0016-8025
DOI - 10.1111/1365-2478.13073
Subject(s) - classification of discontinuities , hilbert–huang transform , geology , operator (biology) , amplitude , signal (programming language) , energy (signal processing) , shielded cable , electromagnetic shielding , matrix (chemical analysis) , mode (computer interface) , acoustics , seismology , algorithm , computer science , physics , mathematics , mathematical analysis , statistics , optics , telecommunications , materials science , repressor , chemistry , composite material , operating system , biochemistry , quantum mechanics , transcription factor , programming language , gene
In this paper, we propose a method for revealing hidden reservoirs that are shielded by strong amplitudes. The bi‐dimensional empirical mode decomposition algorithm is used to decompose pre‐stack seismic data into several localized components, which generated from different discontinuities in the subsurface elastic properties. The two‐dimensional Teager–Kaiser energy operator process is applied to the first component, which includes a strong signal, to further locate the strong event. According to the located results, an energy weight matrix is established. By weighted summation of all the components, the strong event is suppressed, and the hidden reservoir becomes more prominent. Tests on a synthetic data and field data from Daniudi confirm that this method can separate strong signals from weaker responses and efficiently reveal shielded reservoirs.