Natural logarithm transformed EEMD instantaneous attributes of reflection data

Chen, Chih Sung; Jeng, Yih

doi:10.1016/j.jappgeo.2013.05.006

Cited by 14 publications

(16 citation statements)

References 26 publications

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“…Firstly, a geological significant event could be a combination of several IMFs (usually two or three in our case); therefore, the significant events (signals) that we tried to recover in the spatial-amplitude domain are not necessary mono-component and mono-frequency. In other words, mono-component instantaneous attributes presentation may not be the best strategy for showing geological events (Chen and Jeng, 2013). Secondly, negative frequencies are the consequence of mathematical operation, e.g.…”

Section: Discussionmentioning

confidence: 99%

“…In this study, we do not deal with the instantaneous attributes, and certainly do not apply any transform. Lastly, all the IMFs are zero mean, and thus have no negative instantaneous frequencies if we perform the transform (Chen and Jeng, 2013;Huang et al, 2009). Although negative instantaneous frequencies may still occur in the attribute domain for some other reasons ), the chance is very slim because our algorithm is not Fourier-based.…”

Section: Discussionmentioning

confidence: 99%

“…Although negative instantaneous frequencies may still occur in the attribute domain for some other reasons ), the chance is very slim because our algorithm is not Fourier-based. If the negative instantaneous frequency is still an issue, it can be corrected by using the local averaging with the end effect removal technique (Chen and Jeng, 2013).…”

Section: Discussionmentioning

confidence: 99%

“…If any monotonicity is found in the lower frequency components, it should be respected rather than replaced by artificial wiggles resulting from standard cubic polynomial spline. To have a more stable interpolation particularly at the ends of the signals, we moreover adopt the slope extrapolation technique (Chen and Jeng, 2013) to alleviate the end effect problem. We determine the end points by extrapolating the slope estimated by the two preceding (the right end) or following points (the left end).…”

Section: Interpolation Methodsmentioning

confidence: 99%

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Two-dimensional nonlinear geophysical data filtering using the multidimensional EEMD method

Chen

Jeng

2014

Journal of Applied Geophysics

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A variety of two-dimensional (2D) empirical mode decomposition (EMD) methods have been proposed in the last decade. Furthermore, the multidimensional EMD algorithm and its parallel class, multivariate EMD (MEMD), are available in recent years. From those achievements, it is possible to design an efficient 2D nonlinear filter for geophysical data processing. We introduce a robust 2D nonlinear filter which can be applied to enhance the signal of 2D geophysical data or to highlight the feature component on an image. We did this by replacing the conventionally used smooth interpolation in the ensemble empirical mode decomposition (EEMD) algorithm with a piecewise interpolation method. The one-dimensional (1D) EEMD procedures were consecutively performed in all directions, and then the comparable minimal scale combination technique was applied to the decomposed components. The theoretical derivation, model simulation, and real data applications are demonstrated in this paper. The proposed filtering method is effective in improving the image resolution by suppressing the random noise added in the simulation example and strong low frequency track corrugation noise bands with background noise in the field example. Furthermore, the algorithm can be easily extended to higher dimensions by repeating the same procedure in the succeeding dimension. To evaluate the proposed method, one data set is processed separately by using the enhanced analytic signal method and the multivariate EMD (MEMD) algorithm, and the results from these two methods are compared with that of the proposed method. A general equation for generating three-dimensional (3D) EEMD components based on the comparable minimal scale combination principle is derived for further applications.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Interpolation Methodsmentioning

confidence: 99%

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Two-dimensional nonlinear geophysical data filtering using the multidimensional EEMD method

Chen

Jeng

2014

Journal of Applied Geophysics

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“…Torres proposed the complete ensemble empirical mode decomposition (CEEMD) in order to overcome these situations [18]. Furthermore, some scholars have proposed that the EEMD and the CEEMD could both be used in GPR signal analysis [19][20][21][22]. However, these methods also have limitations, for example, the lack of mathematical theory and the degrees of freedom will reduce the algorithm's robustness, which leave room for theoretical development and the improvement of the robustness of the decomposition [23].…”

Section: Introductionmentioning

confidence: 99%

Data Interpretation Technology of GPR Survey Based on Variational Mode Decomposition

Lei

2019

Applied Sciences

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Data interpretation is the crucial scientific component that influences the inspection accuracy of ground penetrating radar (GPR). Developing algorithms for interpreting GPR data is a research focus of increasing interest. The problem of algorithms for interpreting GPR data is unresolved. To this end, this study proposes a sophisticated algorithm for interpreting GPR data with the aim of improving the inspection resolution. The algorithm is formulated by integrating variational mode decomposition (VMD) and Hilbert–Huang transform techniques. With this method, the intrinsic mode function of the GPR data is first produced using the VMD of the data, followed by obtaining the instantaneous frequency by using the Hilbert–Huang transform to analyze the intrinsic mode functions. The instantaneous frequency data can be decomposed into three frequency attributes, including frequency division section, time-frequency section, and space frequency section, which constitute a platform to gain insight into the nature of the GPR data, such that the inspected media components can be examined. The effectiveness of the proposed method on a synthetic signal from a GPR forward model was studied, with the multi-resolution performance being tested. Inspecting the media of a highroad by analyzing the GPR data, with the abnormal characteristics being designated, validated the applicability of the proposed method.

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Instantaneous attributes analysis of seismic signals using improved HHT

Wang

Peng

2015

J. Earth Sci.

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As the key technique of improved Hilbert-Huang transform (HHT), ensemble empirical mode decomposition (EEMD) has a good performance of eliminating mode mixing phenomenon, which has a strong impact on the observation of seismic information. However, the intrinsic mode functions (IMF) obtained from EEMD contain noises, so that it is required to find a more robust frequency estimation method to calculate the instantaneous frequency (IF) of IMF. For this reason, the improved HHT algorithm based on the damped instantaneous frequency (DIF) is proposed to overcome the shortage of EEMD. Compared with other IF estimation methods, the DIF has strong antinoise ability and high estimation accuracy. The test results of synthetic and real seismic data show that the proposed algorithm is feasible and effective for extracting seismic instantaneous attributes. KEY WORDS: mode mixing, ensemble empirical mode decomposition (EEMD), damped instantaneous frequency (DIF), frequency estimation, seismic instantaneous attributes.

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Natural logarithm transformed EEMD instantaneous attributes of reflection data

Cited by 14 publications

References 26 publications

Two-dimensional nonlinear geophysical data filtering using the multidimensional EEMD method

Two-dimensional nonlinear geophysical data filtering using the multidimensional EEMD method

Data Interpretation Technology of GPR Survey Based on Variational Mode Decomposition

Instantaneous attributes analysis of seismic signals using improved HHT

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