Depositional sequence characterization based on seismic variational mode decomposition

Li, Fangyu; Zhang, Bo; Zhai, Rui; Zhou, Hao-Miao; Marfurt, Kurt J.

doi:10.1190/int-2016-0069.1

Cited by 42 publications

(3 citation statements)

References 29 publications

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“…For the transgressive cycle, the thickness of sandstone increases with depth, whereas the grain size of the sediment changes from fine to coarse. For the regressive cycle, the thickness of sandstone decreases with depth, whereas the grain size of sediment changes from coarse to fine (Li et al., 2017; Melani et al., 2020; Rossi et al., 2020). With the decrease or increase of thin‐bed thicknesses, the dominant frequency of the time–frequency spectrum will increase or decrease gradually, which is the theoretical basis for the sedimentary cycle characterization using the time–frequency analysis methods.…”

Section: Theorymentioning

confidence: 99%

Upscaling method based on sedimentary cycle prior and its application to well‐to‐seismic tie

Tian

Stovas

Gao

2023

Geophysical Prospecting

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A well‐to‐seismic tie is a typical upscaling problem. The traditional well‐to‐seismic tie methods often use the velocity log directly to tie well logs to seismic data without considering the upscaling problem led by the velocity dispersion due to thin beds. We propose an upscaling method based on the Backus average method to upscale the well‐log velocity to seismic velocity and apply it to a well‐to‐seismic tie problem. For Backus average method, choosing an appropriate average window is a crucial issue. We introduce a synchrosqueezing optimal basic wavelet transform to calculate an average window. The synchrosqueezing optimal basic wavelet transform is a time–frequency representation method, which can extract the sedimentary cycle information from seismic data. Considering the relationship between the sedimentary cycle and the thin‐bed thickness, we propose a workflow to estimate the instantaneous thin‐bed thickness based on synchrosqueezing optimal basic wavelet transform and determine the window length of the Backus average at each depth point. Then, the Backus average is used to estimate the effective velocity, which is further used to calculate the initial time–depth function and transfer the reflection coefficients from the depth domain to the time domain. Choosing an appropriate seismic wavelet is another fundamental problem for the well‐to‐seismic tie process. This paper introduces an alternating iterative deep neural network‐based method to estimate the seismic wavelet. Thus realistic synthetic seismograms can be computed by convolving the estimated seismic wavelet and the reflection coefficient, which can be stretched or squeezed to match the near‐well seismic trace. We show that the proposed workflow effectively reduces the errors in a well‐to‐seismic tie procedure caused by velocity dispersion of thin beds.

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Section: Theorymentioning

confidence: 99%

Upscaling method based on sedimentary cycle prior and its application to well‐to‐seismic tie

Tian

Stovas

Gao

2023

Geophysical Prospecting

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“…Colominas et al proposed a new improved CEEMD; the new method was used for artificial signals and real biomedical signals [19]. The improvements of the CEEMD method have been achieved through the application of correlation theory [20][21][22][23][24]. The main steps of the CEEMD are as follows:…”

Section: The Proposed Methodsmentioning

confidence: 99%

Noncontact Measurement and Detection of Instantaneous Seismic Attributes Based on Complementary Ensemble Empirical Mode Decomposition

Huang

Malekian

et al. 2017

Energies

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Hilbert-Huang transform (HHT) is a popular method to analyze nonlinear and non-stationary data. It has been widely used in geophysical prospecting. This paper analyzes the mode mixing problems of empirical mode decomposition (EMD) and introduces the noncontact measurement and detection of instantaneous seismic attributes using complementary ensemble empirical mode decomposition (CEEMD). Numerical simulation testing indicates that the CEEMD can effectively solve the mode mixing problems of EMD and can provide stronger anti-noise ability. The decomposed results of the synthetic seismic record show that CEEMD has a better ability to decompose seismic signals. Then, CEEMD is applied to extract instantaneous seismic attributes of 3D seismic data in a real-world coal mine in Inner Mongolia, China. The detection results demonstrate that instantaneous seismic attributes extracted by CEEMD are helpful to effectively identify the undulations of the top interfaces of limestone.

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“…Therefore, it is sometimes difficult to directly use full-band and non-stationary seismic data to identify the subsurface geological anomalies. Decomposing seismic data into certain modes with different dominant frequencies and bandwidth can facilitate extracting intrinsic spectral features (e.g., Li et al 2017;Liu et al 2019).…”

Section: Introductionmentioning

confidence: 99%

Inverse spectral decomposition using an lp-norm constraint for the detection of close geological anomalies

et al. 2020

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An important application of spectral decomposition (SD) is to identify subsurface geological anomalies such as channels and karst caves, which may be buried in full-band seismic data. However, the classical SD methods including the wavelet transform (WT) are often limited by relatively low time–frequency resolution, which is responsible for false high horizon-associated space resolution probably indicating more geological structures, especially when close geological anomalies exist. To address this issue, we impose a constraint of minimizing an lp (0 < p < 1) norm of time–frequency spectral coefficients on the misfit derived by using the inverse WT and apply the generalized iterated shrinkage algorithm to invert for the optimal coefficients. Compared with the WT and inverse SD (ISD) using a typical l1-norm constraint, the modified ISD (MISD) using an lp-norm constraint can yield a more compact spectrum contributing to detect the distributions of close geological features. We design a 3D synthetic dataset involving frequency-close thin geological anomalies and the other 3D non-stationary dataset involving time-close anomalies to demonstrate the effectiveness of MISD. The application of 4D spectrum on a 3D real dataset with an area of approximately 230 km2 illustrates its potential for detecting deep channels and the karst slope fracture zone.

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Depositional sequence characterization based on seismic variational mode decomposition

Cited by 42 publications

References 29 publications

Upscaling method based on sedimentary cycle prior and its application to well‐to‐seismic tie

Upscaling method based on sedimentary cycle prior and its application to well‐to‐seismic tie

Noncontact Measurement and Detection of Instantaneous Seismic Attributes Based on Complementary Ensemble Empirical Mode Decomposition

Inverse spectral decomposition using an lp-norm constraint for the detection of close geological anomalies

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