A new Ensemble Empirical Mode Decomposition (EEMD) is presented. This new approach consists of sifting an ensemble of white noise-added signal (data) and treats the mean as the final true result. Finite, not infinitesimal, amplitude white noise is necessary to force the ensemble to exhaust all possible solutions in the sifting process, thus making the different scale signals to collate in the proper intrinsic mode functions (IMF) dictated by the dyadic filter banks. As EEMD is a time–space analysis method, the added white noise is averaged out with sufficient number of trials; the only persistent part that survives the averaging process is the component of the signal (original data), which is then treated as the true and more physical meaningful answer. The effect of the added white noise is to provide a uniform reference frame in the time–frequency space; therefore, the added noise collates the portion of the signal of comparable scale in one IMF. With this ensemble mean, one can separate scales naturall...

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Ensemble empirical mode decomposition: a noise-assisted data analysis method

Interpretation theory in applied geophysics: Grant, F S ... Interpretation theory in applied geophysics Unknown Binding – January 1, 1965 5.0 out of 5 stars 1 rating. See all formats and editions Hide other formats and editions. The Amazon Book Review Book recommendations, author interviews, editors' picks, and more. Read it now. Enter your mobile number or email address below and we'll send you a ...

Interpretation Theory in Applied Geophysics Grant (McGraw-Hill, 140s.)

Wind speed forecasting based on the hybrid ensemble empirical mode decomposition and GA-BP neural network method

Landform characterization using geophysics—Recent advances, applications, and emerging tools

This paper presents an overview of the strengths and limitations of existing and emerging geophysical tools for landform studies. The objectives are to discuss recent technical developments and to provide a review of relevant recent literature, with a focus on propagating field methods with terrestrial applications. For various methods in this category, including ground-penetrating radar (GPR), electrical resistivity (ER), seismics, and electromagnetic (EM) induction, the technical backgrounds are introduced, followed by section on novel developments relevant to landform characterization. For several decades, GPR has been popular for characterization of the shallow subsurface and in particular sedimentary systems. Novel developments in GPR include the use of multi-offset systems to improve signal-to-noise ratios and data collection efficiency, amongst others, and the increased use of 3D data. Multi-electrode ER systems have become popular in recent years as they allow for relatively fast and detailed mapping. Novel developments include time-lapse monitoring of dynamic processes as well as the use of capacitively-coupled systems for fast, non-invasive surveys. EM induction methods are especially popular for fast mapping of spatial variation, but can also be used to obtain information on the vertical variation in subsurface electrical conductivity. In recent years several examples of the use of plane wave EM for characterization of landforms have been published. Seismic methods for landform characterization include seismic reflection and refraction techniques and the use of surface waves. A recent development is the use of passive sensing approaches. The use of multiple geophysical methods, which can benefit from the sensitivity to different subsurface parameters, is becoming more common. Strategies for coupled and joint inversion of complementary datasets will, once more widely available, benefit the geophysical study of landforms.Three cases studies are presented on the use of electrical and GPR methods for characterization of landforms in the range of meters to 100. s of meters in dimension. In a study of polygonal patterned ground in the Saginaw Lowlands, Michigan, USA, electrical resistivity tomography was used to characterize differences in subsurface texture and water content associated with polygon-swale topography. Also, a sand-filled thermokarst feature was identified using electrical resistivity data. The second example is on the use of constant spread traversing (CST) for characterization of large-scale glaciotectonic deformation in the Ludington Ridge, Michigan. Multiple CST surveys parallel to an ~. 60. m high cliff, where broad (~. 100. m) synclines and narrow clay-rich anticlines are visible, illustrated that at least one of the narrow structures extended inland. A third case study discusses internal structures of an eolian dune on a coastal spit in New Zealand. Both 35 and 200. MHz GPR data, which clearly identified a paleosol and internal sedimentary structures of the dune, were used to improve understanding of the development of the dune, which may shed light on paleo-wind directions.

Geologic noise and background electromagnetic EM waves often degrade the quality of very low frequency electromagneticVLF-EMdata.Toretrievesignalswithsignificant geologic information, we used a new nonlinear decomposition technique called the empirical mode decomposition EMD method with the Hilbert transform. We conducted a 2Dresistivitymodelstudythatincludedinversionofthesyntheticdatatotesttheaccuracyandcapabilitiesofthismethod. Next, we applied this method to real data obtained from a fieldexperimentandageologicexample.ThefilteringprocedureforrealdatastartswithapplyingtheEMDmethodtodecompose the VLF data into a series of intrinsic mode functions that admit a well-behaved Hilbert transform. With the Hilbert transform, the intrinsic mode functions yielded a spectrogram that presents an energy-wavenumber-distance distribution of the VLF data. We then examined the decomposeddataandtheirspectrogramtodeterminethenoisecomponents, which we eliminated to obtain more reliable VLF data. The EMD-filtered data and their associated spectrograms indicated the successful application of this method. Because VLF data are recorded as a complex function of the real variable distance, the in-phase and quadrature parts are complementarycomponentsofeachotherandcouldbeaHilbert transform pair if the data are analytical and noise free. Therefore,bycomparingtheoriginaldatasetwiththeoneobtained from the Hilbert transform, we could evaluate data quality and could even replace the original with its Hilbert transform counterpart with acceptable accuracy. By application of both this technique and conventional methods to real data in this study, we have shown the superiority of this new method and have obtained a more reliable earth model by invertingtheEMD-filtereddata.

Noise reduction and data recovery for a VLF-EM survey using a nonlinear decomposition method

Integrated signal enhancements in magnetic investigation in archaeology

Application of the VLF-EM method with EEMD to the study of a mud volcano in southern Taiwan

This study utilized the very low frequency-electromagnetic (VLF-EM) technique, a passive electromagnetic prospecting method working in the very low frequency range (15–30 KHz) to investigate the geo-environmental problems of shallow, low conductivity sedimentary layers in Taiwan. Field examples successfully demonstrate the advantages of using this method in locating non-mineralized shallow fault zones. The zero-crossings of in-phase and quadrature measurements in 2-D contour maps clearly locate the position of subsurface anomalous source bodies. Further analysis of the measured VLF single profile peaks reveals that this method is useful in determining subsurface structures and conductivity. The advantages of nondestructive, noninvasive, and low consumption of power make this method extremely friendly to the environment. The authors anticipate this method will have more profound impacts on the interactions between prospecting technology and the earth.

Ming Juin Lin

Papers

Noise reduction and data recovery for a VLF-EM survey using a nonlinear decomposition method

Integrated signal enhancements in magnetic investigation in archaeology

Application of the VLF-EM method with EEMD to the study of a mud volcano in southern Taiwan

A very low frequency-electromagnetic study of the geo-environmental hazardous areas in Taiwan

Ultrashallow seismic experiment on a trenched section of the Chelunpu fault zone, Taiwan