TY - JOUR
T1 - The Fine Characterization Method of Multiscale Sedimentary Cycles in Phase Space
AU - Tian, Yajun
AU - Gao, Jinghuai
AU - Chen, Maoshan
AU - Tao, Chunfeng
AU - Meng, Chuangji
N1 - Publisher Copyright:
© 1980-2012 IEEE.
PY - 2025
Y1 - 2025
N2 - Sedimentary cycles are the fundamental building blocks of sedimentary sequences, resulting from the superposition of periodic sedimentary events at different scales. Seismic reflection data contain multiscale sedimentary cycle information in the subsurface. Accurate extraction multiscale sedimentary cycle information from seismic data is key to realizing multiscale sequence stratigraphy analysis. This article proposes a workflow for multiscale sedimentary cycle characterization by combining variational mode decomposition (VMD) and synchrosqueezing optimal basic wavelet transform (SOBWT) methods. The workflow first derives the relationship between different-scale sedimentary cycles and their reflectivity amplitude spectrum and proposes a method for determining the number of intrinsic mode functions (IMFs) and center frequencies parameters of VMD. Subsequently, VMD is employed to decompose the different-scale seismic reflection from seismic data. Further, SOBWT and ridge extraction methods are introduced to extract instantaneous dominant frequency attributes from IMF profiles to characterize different-scale sedimentary cycles and to divide sedimentary cycle units. Applications on synthetic and field data demonstrate that the proposed workflow can effectively separate seismic reflection characteristics of different-scale sedimentary cycles from seismic data. The instantaneous dominant frequency attributes proposed based on SOBWT and ridge extraction methods can effectively characterize the thin bed thickness variation of different-scale sedimentary cycle and can assist in sedimentary cycle unit identification. This provides an important tool for subsequent sequence stratigraphy research.
AB - Sedimentary cycles are the fundamental building blocks of sedimentary sequences, resulting from the superposition of periodic sedimentary events at different scales. Seismic reflection data contain multiscale sedimentary cycle information in the subsurface. Accurate extraction multiscale sedimentary cycle information from seismic data is key to realizing multiscale sequence stratigraphy analysis. This article proposes a workflow for multiscale sedimentary cycle characterization by combining variational mode decomposition (VMD) and synchrosqueezing optimal basic wavelet transform (SOBWT) methods. The workflow first derives the relationship between different-scale sedimentary cycles and their reflectivity amplitude spectrum and proposes a method for determining the number of intrinsic mode functions (IMFs) and center frequencies parameters of VMD. Subsequently, VMD is employed to decompose the different-scale seismic reflection from seismic data. Further, SOBWT and ridge extraction methods are introduced to extract instantaneous dominant frequency attributes from IMF profiles to characterize different-scale sedimentary cycles and to divide sedimentary cycle units. Applications on synthetic and field data demonstrate that the proposed workflow can effectively separate seismic reflection characteristics of different-scale sedimentary cycles from seismic data. The instantaneous dominant frequency attributes proposed based on SOBWT and ridge extraction methods can effectively characterize the thin bed thickness variation of different-scale sedimentary cycle and can assist in sedimentary cycle unit identification. This provides an important tool for subsequent sequence stratigraphy research.
KW - Multiscale sedimentary cycle characterization
KW - sequence stratigraphy
KW - synchrosqueezing optimal basic wavelet transform (SOBWT)
KW - variational mode decomposition (VMD)
UR - https://www.scopus.com/pages/publications/86000386246
U2 - 10.1109/TGRS.2024.3512660
DO - 10.1109/TGRS.2024.3512660
M3 - 文章
AN - SCOPUS:86000386246
SN - 0196-2892
VL - 63
JO - IEEE Transactions on Geoscience and Remote Sensing
JF - IEEE Transactions on Geoscience and Remote Sensing
M1 - 5900713
ER -