L1 pseudo-Vz estimation and deghosting of single-component marine towed-streamer data

Geophysics ◽  
2013 ◽  
Vol 78 (2) ◽  
pp. WA21-WA6 ◽  
Author(s):  
Ralf Ferber ◽  
Philippe Caprioli ◽  
Lee West
Keyword(s):  
Particle Motion ◽  
Pressure Wave ◽  
Vertical Component ◽  
Low Frequency ◽  
Single Component ◽  
Pressure Data ◽  
Data Set ◽  
Low Frequencies ◽  
Motion Data ◽  
Streamer Data

We present a novel technique estimating the vertical component of particle motion from marine single-component pressure data. The particle motion data, bar an angle-dependent obliquity factor, is computed by convolution of the output from L1 deconvolution of the pressure ghost wavelet with the corresponding ghost wavelet of the particle motion. The estimated particle motion data is then used in a conventional 2D technique for receiver ghost attenuation by combination with the original pressure-wave data. The proposed new technique operates in the τ-[Formula: see text] domain of individual shot-streamer records and in overlapping windows along the intercept-time axis. In each window, the L1 deconvolution is achieved by an iteratively reweighted-norm least squares algorithm. We applied our technique to deep-tow streamer data of a 3D over/sparse-under marine survey, in which six streamers were towed at a shallow depth, with two additional streamers towed deeper. Over/sparse-under technology allows using seismic measurements from a shallow streamer to be complemented by a low-frequency limited measurement from a deep streamer to achieve an estimate of the up-going pressure wave recording. The low frequencies of the deep streamer are used to boost the low frequencies of the shallow streamer, which have been heavily attenuated by the shallow tow ghost response. Our technique achieves, on this particular data, set improvements in bandwidth of the single-component pressure data, while not fully reaching the quality of the optimally deghosted data from the over/sparse-under survey.

Wavefield-separation methods for dual-sensor towed-streamer data

Geophysics ◽  
2013 ◽  
Vol 78 (2) ◽  
pp. WA55-WA70 ◽  
Author(s):  
Anthony Day ◽  
Tilman Klüver ◽  
Walter Söllner ◽  
Hocine Tabti ◽  
David Carlson
Keyword(s):  
Particle Motion ◽  
Signal To Noise Ratio ◽  
Vertical Component ◽  
Pressure Data ◽  
Motion Data ◽  
Wavefield Separation ◽  
Small Depth ◽  
Scattered Energy ◽  
Dual Sensor ◽  
Streamer Data

A dual-sensor towed streamer records the pressure and vertical component of particle motion associated with the incident wavefield that may be used to separate the wavefield into its up- and downgoing parts. This procedure requires information about the water properties (wave-propagation velocity and density) and is robust in the presence of errors in the estimation of these quantities of the magnitude likely to be encountered. In practice, the particle motion data recorded by current towed marine streamers encounter very strong mechanical noise such that, for the lowest frequencies, the wavefield separation must be approximated by deconvolving the ghost function from the pressure data. This procedure requires information about the streamer depth and is robust to small depth errors over the frequency range for which it is required for dual-sensor streamer processing, but it is much more sensitive if applied over the bandwidth necessary to deghost pressure data acquired at a conventional streamer depth. The signal-to-noise ratio can be further enhanced by recombining the up- and downgoing pressure fields at the sea surface, which has the effect of applying a ghostlike filter to noise that is recorded by only one of the two sensors. In practical marine acquisition scenarios, spatial sampling is often insufficient to yield an accurate result, especially in the crossline direction. If each streamer is processed independently assuming that the wavefield propagation is purely inline, significant errors can be introduced. For arrivals with high emergent angles, errors may also be introduced even if the wavefield propagation actually is purely inline due to incorrect treatment of spatially aliased energy. However, these effects are almost entirely confined to very shallow events. They can be mitigated by using independently derived information about the crossline propagation angle and, for data comprising predominantly forward scattered energy, appropriate application of linear moveout.

A teleseism-specific detection algorithm for single short-period traces

1983 ◽  
Vol 73 (4) ◽  
pp. 1173-1186
Author(s):  
John R. Evans ◽  
Stephen S. Allen
Keyword(s):  
Frequency Band ◽  
High Frequency ◽  
Vertical Component ◽  
Low Frequency ◽  
Field Studies ◽  
Detection Algorithm ◽  
P Waves ◽  
Data Set ◽  
Short Period ◽  
Worldwide Network

abstract An algorithm for microprocessor-controlled seismographic recorders is described which reliably detects major phases from earthquakes more than 3° from the sensor but rejects noise events and most earthquakes closer than 3°. Unusually large earthquakes within 3° also are detected. The algorithm is applicable to field studies using triggered seismographs to record teleseismic P waves, to worldwide network automation, and to scanning records for teleseisms. It uses two band-pass filtered data streams evolved from a single short-period vertical-component seismometer to differentiate (low-frequency) teleseisms from other signals; the low-frequency band (0.5 to 2.0 Hz) declares “triggers” while the high-frequency band (3.0 to 8.0 Hz) inhibits any of these triggers generated by broadband signals such as local earthquakes. Locally generated noise is usually high frequency and does not excite the low-frequency band. A 16-bit fixed-word-length implementation of this algorithm detected 82 per cent of good P phases (readable to ±0.25 sec) occurring more than 20° from the seismograph, and 50 per cent of earthquakes between 3° and 20°, in a test data set comprising 23 hr of data in 93 segments. The same implementation of the algorithm rejected most noise and 91 per cent of earthquakes within 3° of the seismograph.

Acoustic impedance estimation from combined harmonic reconstruction and interval velocity

Geophysics ◽  
2019 ◽  
Vol 84 (3) ◽  
pp. R385-R400
Author(s):  
Luca Bianchin ◽  
Emanuele Forte ◽  
Michele Pipan
Keyword(s):  
Velocity Field ◽  
Seismic Data ◽  
Acoustic Impedance ◽  
Low Frequency ◽  
Reconstruction Method ◽  
Well Log ◽  
Data Set ◽  
Low Frequencies ◽  
Interval Velocity ◽  
Frequency Components

Low-frequency components of reflection seismic data are of paramount importance for acoustic impedance (AI) inversion, but they typically suffer from a poor signal-to-noise ratio. The estimation of the low frequencies of AI can benefit from the combination of a harmonic reconstruction method (based on autoregressive [AR] models) and a seismic-derived interval velocity field. We have developed the construction of a convex cost function that accounts for the velocity field, together with geologic a priori information on AI and its uncertainty, during the AR reconstruction of the low frequencies. The minimization of this function allows one to reconstruct sensible estimates of low-frequency components of the subsurface reflectivity, which lead to an estimation of AI model via a recursive formulation. In particular, the method is suited for an initial and computationally inexpensive assessment of the absolute value of AI even when no well-log data are available. We first tested the method on layered synthetic models, then we analyzed its applicability and limitations on a real marine seismic data set that included tomographic velocity information. Despite a strong trace-to-trace variability in the results, which could partially be mitigated by multitrace inversion, the method demonstrates its capability to highlight lateral variations of AI that cannot be detected when the low frequencies only come from well-log information.

scholarly journals Localization of Alternating Magnetic Dipole in the Near-Field Zone with Single-Component Magnetometers

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Gao Xiang ◽  
Du Bo-cheng ◽  
Wang Qi-long
Keyword(s):  
Magnetic Field ◽  
Magnetic Dipole ◽  
Near Field ◽  
Vertical Component ◽  
Low Frequency ◽  
Single Component ◽  
Dipole Source ◽  
Magnetic Field Measurement ◽  
Field Zone ◽  
Theoretical Simulation

Tri-axis magnetometers are widely used to measure magnetic field in engineering of the magnetic localization technology. However, the magnetic field measurement precision is influenced by the nonorthogonal error of tri-axis magnetometers. A locating model of the alternating magnetic dipole in the near-field zone with single-component magnetometers was proposed in this paper. Using the vertical component of the low-frequency magnetic field acquired by at least six single-component magnetometers, the localization of an alternating magnetic dipole could be attributed to the solution for a class of nonlinear unconstrained optimization problem. In order to calculate the locating information of alternating magnetic dipole, a hybrid algorithm combining the Gauss–Newton algorithm and genetic algorithm was applied. The theoretical simulation and field experiment for the localization of alternating magnetic dipole source were carried out, respectively. The positioning result is stable and reliable, indicating that the locating model has better performance and could meet the requirements of actual positioning.

scholarly journals Waveform inversion based on wavefield decomposition

Geophysics ◽  
2016 ◽  
Vol 81 (6) ◽  
pp. R457-R470 ◽  
Author(s):  
Fang Wang ◽  
Daniela Donno ◽  
Hervé Chauris ◽  
Henri Calandra ◽  
François Audebert
Keyword(s):  
Waveform Inversion ◽  
Low Frequency ◽  
Velocity Model ◽  
Model Parameters ◽  
Data Set ◽  
Low Frequencies ◽  
Full Waveform ◽  
Highly Nonlinear ◽  
Gradient Based ◽  
Wavefield Decomposition

Full-waveform inversion (FWI) is a technique for determining the optimal model parameters by minimizing the seismic data misfit between observed and modeled data. The objective function may be highly nonlinear if the model is complex and low-frequency data are missing. If a data set mainly contains reflections, this problem particularly prevents the gradient-based methods from recovering the long wavelengths of the velocity model. Several authors observed that nonlinearity could be reduced by progressively introducing higher wavenumbers to the model. We have developed a new inversion workflow to solve this problem by breaking down the FWI gradient formula into four terms after wavefield decomposition and then selecting proper terms to invert for the short- and long-wavelength components of the velocity model alternately. Numerical tests applied on a 2D synthetic model indicate that this method is efficient at recovering the long wavelengths of the velocity model using mainly offset-limited reflection events. The source does not need to contain low frequencies. The initial velocity model may have large errors that would otherwise prevent convergence for conventional FWI.

Multiparameter waveform inversion of a large wide-azimuth low-frequency land data set in Oman

Geophysics ◽  
2014 ◽  
Vol 79 (3) ◽  
pp. WA69-WA77 ◽  
Author(s):  
Alexandre Stopin ◽  
René-Édouard Plessix ◽  
Said Al Abri
Keyword(s):  
Waveform Inversion ◽  
Low Frequency ◽  
Large Data ◽  
Earth Model ◽  
Data Sets ◽  
Anisotropic Parameter ◽  
Data Set ◽  
Low Frequencies ◽  
Reflected Waves ◽  
Simultaneous Inversion

Several 3D seismic acoustic full-waveform inversions (FWIs) of offshore data sets have been reported over the last five years. A successful updating of the long-to-intermediate wavelengths of the earth model by FWI requires good-quality wide-angle, long-offset, low-frequency data. Recent improvements in acquisition make such data sets available on land, too. We evaluated a 3D application on a data set recorded in North Oman. The data contain low frequencies down to 1.5 Hz, long-offsets, and wide azimuths. The application of acoustic FWI on land remains complicated because of the elastic effects, notably the strong ground-roll and many acquisition and human-activity-related noises. The presence of fast carbonate layers in this region induces velocity inversions, difficult to recover from diving or postcritical waves. We accounted for anisotropic effects as we include FWI in a classical structural imaging workflow. With a dedicated processing of the data and a simultaneous inversion of the NMO velocity and the anelliptic-anisotropic parameter, we succeeded to interpret the kinematics of transmitted and reflected waves, although in the waveform inversion we included only the diving and postcritical waves. This approach has some limitations because of the acoustic assumption. We could not obtain a high-resolution image, especially at the shale-carbonate interfaces. There is also a trade-off between the NMO velocity and the anelliptic anisotropic parameter. However, the image improvements after acoustic FWI and the ability to handle the large data volume make this technique attractive in an imaging workflow.

scholarly journals Acceleration Feature Extraction of Human Body Based on Wearable Devices

Energies ◽  
2021 ◽  
Vol 14 (4) ◽  
pp. 924
Author(s):  
Zhenzhen Huang ◽  
Qiang Niu ◽  
Ilsun You ◽  
Giovanni Pau
Keyword(s):  
Genetic Algorithm ◽  
Feature Extraction ◽  
Kalman Filter ◽  
Human Body ◽  
Wearable Devices ◽  
Human Motion ◽  
Data Set ◽  
Feature Extraction Method ◽  
Motion Data ◽  
Kalman Filter Algorithm

Wearable devices used for human body monitoring has broad applications in smart home, sports, security and other fields. Wearable devices provide an extremely convenient way to collect a large amount of human motion data. In this paper, the human body acceleration feature extraction method based on wearable devices is studied. Firstly, Butterworth filter is used to filter the data. Then, in order to ensure the extracted feature value more accurately, it is necessary to remove the abnormal data in the source. This paper combines Kalman filter algorithm with a genetic algorithm and use the genetic algorithm to code the parameters of the Kalman filter algorithm. We use Standard Deviation (SD), Interval of Peaks (IoP) and Difference between Adjacent Peaks and Troughs (DAPT) to analyze seven kinds of acceleration. At last, SisFall data set, which is a globally available data set for study and experiments, is used for experiments to verify the effectiveness of our method. Based on simulation results, we can conclude that our method can distinguish different activity clearly.

scholarly journals Earless toads sense low frequencies but miss the high notes

2017 ◽  
Vol 284 (1864) ◽  
pp. 20171670 ◽  
Author(s):  
Molly C. Womack ◽  
Jakob Christensen-Dalsgaard ◽  
Luis A. Coloma ◽  
Juan C. Chaparro ◽  
Kim L. Hoke
Keyword(s):  
High Frequency ◽  
Species Differences ◽  
Low Frequency ◽  
Auditory Brainstem ◽  
Low Frequencies ◽  
Hearing Sensitivity ◽  
Sensory Pathways ◽  
Airborne Sound ◽  
Vibrational Sensitivity ◽  
Species Specific

Sensory losses or reductions are frequently attributed to relaxed selection. However, anuran species have lost tympanic middle ears many times, despite anurans' use of acoustic communication and the benefit of middle ears for hearing airborne sound. Here we determine whether pre-existing alternative sensory pathways enable anurans lacking tympanic middle ears (termed earless anurans) to hear airborne sound as well as eared species or to better sense vibrations in the environment. We used auditory brainstem recordings to compare hearing and vibrational sensitivity among 10 species (six eared, four earless) within the Neotropical true toad family (Bufonidae). We found that species lacking middle ears are less sensitive to high-frequency sounds, however, low-frequency hearing and vibrational sensitivity are equivalent between eared and earless species. Furthermore, extratympanic hearing sensitivity varies among earless species, highlighting potential species differences in extratympanic hearing mechanisms. We argue that ancestral bufonids may have sufficient extratympanic hearing and vibrational sensitivity such that earless lineages tolerated the loss of high frequency hearing sensitivity by adopting species-specific behavioural strategies to detect conspecifics, predators and prey.

A waveform inversion technique for measuring elastic wave attenuation in cylindrical bars

Geophysics ◽  
1992 ◽  
Vol 57 (6) ◽  
pp. 854-859 ◽  
Author(s):  
Xiao Ming Tang
Keyword(s):  
Elastic Wave ◽  
Wave Attenuation ◽  
Waveform Inversion ◽  
Finite Size ◽  
Low Frequency ◽  
Frequency Range ◽  
Multiple Reflections ◽  
Low Frequencies ◽  
The Time Domain ◽  
Attenuation Values

A new technique for measuring elastic wave attenuation in the frequency range of 10–150 kHz consists of measuring low‐frequency waveforms using two cylindrical bars of the same material but of different lengths. The attenuation is obtained through two steps. In the first, the waveform measured within the shorter bar is propagated to the length of the longer bar, and the distortion of the waveform due to the dispersion effect of the cylindrical waveguide is compensated. The second step is the inversion for the attenuation or Q of the bar material by minimizing the difference between the waveform propagated from the shorter bar and the waveform measured within the longer bar. The waveform inversion is performed in the time domain, and the waveforms can be appropriately truncated to avoid multiple reflections due to the finite size of the (shorter) sample, allowing attenuation to be measured at long wavelengths or low frequencies. The frequency range in which this technique operates fills the gap between the resonant bar measurement (∼10 kHz) and ultrasonic measurement (∼100–1000 kHz). By using the technique, attenuation values in a PVC (a highly attenuative) material and in Sierra White granite were measured in the frequency range of 40–140 kHz. The obtained attenuation values for the two materials are found to be reliable and consistent.

Methods to isolate retrograde and prograde Rayleigh-wave signals

2019 ◽  
Vol 219 (2) ◽  
pp. 975-994 ◽  
Author(s):  
Gabriel Gribler ◽  
T Dylan Mikesell
Keyword(s):  
Rayleigh Wave ◽  
Time Domain ◽  
Fundamental Mode ◽  
Poisson Ratio ◽  
Low Frequency ◽  
Wave Dispersion ◽  
Low Frequencies ◽  
Retrograde Motion ◽  
Mode Identification ◽  
Time Frequency

SUMMARY Estimating shear wave velocity with depth from Rayleigh-wave dispersion data is limited by the accuracy of fundamental and higher mode identification and characterization. In many cases, the fundamental mode signal propagates exclusively in retrograde motion, while higher modes propagate in prograde motion. It has previously been shown that differences in particle motion can be identified with multicomponent recordings and used to separate prograde from retrograde signals. Here we explore the domain of existence of prograde motion of the fundamental mode, arising from a combination of two conditions: (1) a shallow, high-impedance contrast and (2) a high Poisson ratio material. We present solutions to isolate fundamental and higher mode signals using multicomponent recordings. Previously, a time-domain polarity mute was used with limited success due to the overlap in the time domain of fundamental and higher mode signals at low frequencies. We present several new approaches to overcome this low-frequency obstacle, all of which utilize the different particle motions of retrograde and prograde signals. First, the Hilbert transform is used to phase shift one component by 90° prior to summation or subtraction of the other component. This enhances either retrograde or prograde motion and can increase the mode amplitude. Secondly, we present a new time–frequency domain polarity mute to separate retrograde and prograde signals. We demonstrate these methods with synthetic and field data to highlight the improvements to dispersion images and the resulting dispersion curve extraction.

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