Search Results (10)

Linear noise, a significant type of interference in exploration seismic data, adversely affects the signal-to-noise ratio (SNR) and imaging resolution. As seismic exploration advances, the constraints of the acquisition environment hinder the ability to acquire seismic data in a regular and dense manner, complicating the suppression of linear noise. To address this challenge, we have developed an anti-aliasing and anti-leakage frequency–wavenumber (f-k) filtering method. This approach effectively mitigates issues of spatial aliasing and spectral leakage caused by irregular coarse data acquisition by integrating linear moveout correction and anti-leakage Fourier transform into traditional f-k filtering. The efficacy of our method was demonstrated through examples of linear noise suppression on both irregular coarse synthetic data and field seismic data. Full article

This study investigates the structure of shear-wave velocities (Vs) in the shallow layers of the Oran region, north-west of Algeria, using non-invasive techniques based on ambient vibration arrays. The region has experienced several moderate earthquakes, including the historical Oran earthquake of 1790. Ambient vibration measurements were carried out at 15 sites throughout the study area. Two methods were used: spatial autocorrelation (SPAC) and frequency–wavenumber analysis (f-k), which allowed us to better constrain Rayleigh wave dispersion curves. The inversion of the dispersion curves derived from the f-k analysis allowed for estimating the shear-wave velocity profiles and the V_s30 value at the sites under study. The other important result of the present study is an empirical equation that has been proposed to predict V_s30 in the Oran region. The determination of near-surface shear-wave velocity profiles is an important step in the assessment of seismic hazard. This study has demonstrated the effectiveness of using ambient vibration array techniques to estimate the soil Vs structure. Full article

Ground-penetrating radar (GPR) is a classic geophysical exploration method that utilizes the emission and reception of electromagnetic waves to non-destructively detect target objects in the target medium. It has been widely applied in various fields such as pipeline detection, cavity detection, and rebar detection. However, GPR systems are susceptible to environmental clutter interference, which poses challenges for data interpretation and subsequent processing. In this paper, the separability of clutter and target signal in the frequency-wavenumber (F-K) domain is validated through modeling, leading to the proposal of a comprehensive clutter removal method based on the F-K domain for complex scenarios. The direct coupling wave is initially eliminated by applying a peak matching mean subtraction filter, which avoids the artifacts. Subsequently, the F-K domain transformation is performed and surface clutter undulations are effectively removed using a method based on singular value decomposition and k-means clustering. Finally, an angle filter with Gaussian tapering at the edges is designed based on physical models to efficiently eliminate linear interference without undesired ringing interference. The commonly used clutter removal algorithms, including mean subtraction (MS), singular value decomposition (SVD), robust principal component analysis (RPCA), and traditional F-K filtering methods, are compared with the proposed algorithm on both the numerical simulated data and actual GPR data. The results from visual and quantitative analysis confirm that our proposed method is more effective than current commonly used clutter suppression algorithms. We have successfully enhanced the Signal-to-Clutter Ratio (SCR) of the GPR data, resulting in an Improvement Factor (IF) of 30.63 dB, 23.59 dB, and 30.60 dB for simulated data, experimental data, and TU1208 public data, respectively. The detection capability of buried targets is enhanced, thereby establishing a solid foundation for subsequent data interpretation and target identification. Full article

Metal structural plates are extensively used in various engineering structures due to their high strength, high-temperature resistance, toughness, and plasticity. However, they are susceptible to damage from external loads and impacts over time. The current Lamb wave detection methods suffer from dispersion and multimodal effects, leading to ineffective identification of damage information. In this paper, we investigate Lamb wave propagation in steel structure plates with flat-bottomed holes using a sinusoidal modulation five-peak wave signal. Finite element numerical models are developed, and an experimental platform is constructed using steel and aluminum boards. Experimental data is collected using a Scanning Laser Doppler Vibrometer (SLDV, PSV-500, Polytec Inc., Baden-Württemberg, German). The results demonstrate that, under the same frequency, the damage reflection energy for different modes is distinct. By fusing the data from the two modes, more accurate damage imaging results are obtained in the frequency-wavenumber (f-k) domain compared to single-mode imaging. Furthermore, experiments are conducted to locate damage in a steel board with a through hole and an aluminum plate with double flat-bottomed holes, confirming the feasibility of the proposed algorithm in isotropic plates. Full article

Tele-ultrasound imaging is useful in various situations. Plane wave imaging provides a method for ultrafast ultrasound with very high frame rates, which sacrifices image quality and leads to the problem of a large amount of data and low signal transmission speed in telemedicine imaging. In this paper, a novel compressive frequency-wavenumber domain beamforming method is introduced, which integrates Stolt’s f-k method and compressed sensing theory on the lateral wavenumber. The data load is reduced by the sparsity of the echo signal parallel to the transducer, which requires a smaller measurement matrix during compressed sensing to reduce memory usage and accelerate the transmission rate. The signal is compressed in the Fourier domain to obtain greater stability and better image quality after reconstruction than if it was compressed in the temporal domain. Simulated data and experimental acquisitions were used to compare compressive Fourier domain beamforming with conventional delay-and-sum (DAS) beamforming. The results showed that compressive beamforming within the wavenumber domain provides the image with higher quality from less data. Full article

In order to better assess the seismic hazard in the northern region of Algeria, the shear-wave velocity structure in the Middle-Chelif Basin is estimated using ambient vibration single-station and array measurements. The Middle-Chelif Basin is located in the central part of the Chelif Basin, the largest of the Neogene sedimentary basins in northern Algeria. This basin hosts the El-Asnam fault, one of the most important active faults in the Mediterranean area. In this seismically active region, most towns and villages are built on large unconsolidated sedimentary covers. Application of the horizontal-to-vertical spectral ratio (HVSR) technique at 164 sites, and frequency–wavenumber (F–K) analysis at 7 other sites, allowed for the estimation of the ground resonance frequencies, shear-wave velocity profiles, and sedimentary cover thicknesses. The electrical resistivity tomography method was used at some sites to further constrain the thickness of the superficial sedimentary layers. The soil resonance frequencies range from 0.75 Hz to 12 Hz and the maximum frequency peak amplitude is 6.2. The structure of the estimated shear-wave velocities is presented in some places as 2D profiles to help interpret the existing faults. The ambient vibration data allowed us to estimate the maximum depth in the Middle-Chelif Basin, which is 760 m near the city of El-Abadia. Full article

The use of unmanned aerial vehicle (UAV)-mounted radar for obtaining snowpack parameters has seen considerable advances over recent years. However, a robust method of snow density estimation still needs further development. The objective of this work is to develop a method to reliably and remotely estimate snow water equivalent (SWE) using UAV-mounted radar and to perform initial field experiments. In this paper, we present an improved scheme for measuring SWE using ultra-wide-band (UWB) (0.7 to 4.5 GHz) pseudo-noise radar on a moving UAV, which is based on airborne snow depth and density measurements from the same platform. The scheme involves autofocusing procedures with the frequency–wavenumber (F–K) migration algorithm combined with the Dix equation for layered media in addition to altitude correction of the flying platform. Initial results from field experiments show high repeatability (R > 0.92) for depth measurements up to $5.5$ m, and good agreement with Monte Carlo simulations for the statistical spread of snow density estimates with standard deviation of $0.108$ g/cm³. This paper also outlines needed system improvements to increase the accuracy of a snow density estimator based on an F–K migration technique. Full article

The reactivation of very large landslides may cause severe damage to society. Its prevention and management requires detailed information on the geometry and structure of these landslides, but the use of standard techniques (boreholes) may be prohibitive from an economic point of view. To overcome these difficulties, geophysical techniques are of special interest because they allow for studying very large areas at a reasonable cost. In this paper, we present a case study wherein the analysis of ambient noise allowed us to produce a model of a large landslide near Granada (southern Spain). The geometry and location of the failure zone, as well as the assessment of the state of involved materials, were estimated by combining two available boreholes and different geophysical techniques (downhole tests and the spectral analysis of ambient noise, horizontal to vertical spectral ratios (HVSR) and the frequency-wavenumber (f-k) methods). The results have allowed us to differentiate between values within the landslide mass with respect to those of stable materials, and to perform for the first time a comprehensive geological model of this unstable mass. Differences were also observed within the landslide mass (earth flow vs. slide zones), which are attributed to differences in the degree of alteration and the disturbance of the internal structure of materials constituting the landslide mass. These results show that techniques based on the measurement of ambient noise are of special interest for studying very large, highly remolded landslide masses. Full article

Fractured imaging is an important target for oil and gas exploration, as these images are heterogeneous and have contain low-impedance contrast, which indicate the complexity in a geological structure. These small-scale discontinuities, such as fractures and faults, present themselves in seismic data in the form of diffracted waves. Generally, seismic data contain both reflected and diffracted events because of the physical phenomena in the subsurface and due to the recording system. Seismic diffractions are produced once the acoustic impedance contrast appears, including faults, fractures, channels, rough edges of structures, and karst sections. In this study, a double square root (DSR) equation is used for modeling of the diffraction hyperbola with different velocities and depths of point diffraction to elaborate the diffraction hyperbolic pattern. Further, we study the diffraction separation methods and the effects of the velocity analysis methods (semblance vs. hybrid travel time) for velocity model building for imaging. As a proof of concept, we apply our research work on a steep dipping fault model, which demonstrates the possibility of separating seismic diffractions using dip frequency filtering (DFF) in the frequency–wavenumber (F-K) domain. The imaging is performed using two different velocity models, namely the semblance and hybrid travel time (HTT) analysis methods. The HTT method provides the optimum results for imaging of complex structures and imaging below shadow zones. Full article

This paper proposes an innovative method for identifying the locations of multiple simultaneous acoustic emission (AE) events in plate-like structures from the view of image processing. By using a linear lead zirconium titanate (PZT) sensor array to record the AE wave signals, a reverse-time frequency-wavenumber (f-k) migration is employed to produce images displaying the locations of AE sources by back-propagating the AE waves. Lamb wave theory is included in the f-k migration to consider the dispersive property of the AE waves. Since the exact occurrence time of the AE events is usually unknown when recording the AE wave signals, a heuristic artificial bee colony (ABC) algorithm combined with an optimal criterion using minimum Shannon entropy is used to find the image with the identified AE source locations and occurrence time that mostly approximate the actual ones. Experimental studies on an aluminum plate with AE events simulated by PZT actuators are performed to validate the applicability and effectiveness of the proposed optimal image-based AE source identification method. Full article