Search Results (6)

The Ground Penetrating Radar (GPR) method can image dielectric discontinuities in subsurface structures, which cause the reflection of electromagnetic (EM) waves. These discontinuities are imaged as reflectors in GPR sections, often distorted by diffracted energy. To focus the diffracted energy within the GPR sections, migration is commonly used. The migration velocity of GPR data is a low-wavenumber attribute crucial for effective migration. Obtaining a migration velocity model, typically close to a Root Mean Square (RMS) model, from zero-offset (ZO) data requires analysis of the available diffractions, whose density and (x, t) coverage are random. Thus, the accuracy and efficiency of such a velocity model, whether for migration or interval velocity model estimation, are not guaranteed. An alternative is the multipath summation method, which involves the weighted stacking of constant velocity migrated sections. Each stacked section contributes to the final stack, weighted by a scalar value dependent on the constant velocity value used and its relation to its estimated mean velocity of the section. This method effectively focuses the GPR diffractions in the presence of low heterogeneity. However, when the EM velocity varies dramatically, 2D weights are needed. In this study, with the aid of an Artificial Intelligence (AI) algorithm that detects diffractions and uses their kinematic information, we generate a diffraction velocity model. This model is then used to assign 2D weights for the weighted multipath summation, aiming to focus the scattered energy within the GPR section. We describe this methodology and demonstrate its application in enhancing the lateral continuity of reflections. We compare it with the 1D multipath summation using simulated data and present its application on marble assessment GPR data for imaging cracks and discontinuities in the subsurface structure. Full article

The current reverse-time migration, which is based on wave equations for imaging wavefields, employs an imaging formula derived from Claerbout’s imaging principle. This imaging formula is only valid for plane waves with small incident angles on the perfectly flat reflecting surface. However, the complexity of seismic wave propagation may lead to situations that do not meet this requirement. Therefore, this paper divides the subsurface into local scattering and reflecting bodies. It proposes linear forward representations for scattering and reflection data based on perturbations in the physical parameters and wave impedance, respectively. To further describe the effect on the reflecting body boundary, the local reflection coefficient is defined and the linear forward representation for the reflection data based on it is obtained. After that, the proposed linear forward representations are used as the forward equations for the linear inverse of the seismic data, and the seismic data waveform imaging method is developed based on linear inversion theory. At the same time, the specific waveform imaging calculation formulas for scalar wave scattering data and scalar wave reflection data are provided and validated via numerical experiments. Compared with the current reverse-time migration, waveform migration not only has the correct phase and higher resolution in theory but also does not increase the computational complexity. To some extent, it improves the deficiencies of the current structural imaging and provides a basis for subsurface lithological imaging. Full article

To meet the demand for the aerosol detection of single-angle and multi-band polarization instrument containing short-wave infrared bands, an inversion algorithm that makes full use of multi-band intensity and polarization information is proposed based on optimal estimation theory. This method uses the polarization information in the short-wave infrared band to perform surface and atmosphere decoupling without a prior information on the surface. This obtains the initial value of the aerosol, and then it uses the scalar information to obtain the final result. Moreover, the multi-band information of the instrument is used for decoupling the surface and atmospheric information, which avoids the inversion error caused by the untimely update of the surface reflectance database and the error of spatio-temporal matching. The measured data of the Particulate Observing Scanning Polarimeter (POSP) are used to test the proposed algorithm. Firstly, to verify the effectiveness of the algorithm under different surface conditions, four regions with large geographical differences (Beijing, Hefei, Baotou, and Taiwan) are selected for aerosol optical depth (AOD) inversion, and they are compared with the aerosol robotic network (AERONET) products of the nearby stations. The validation against the AERONET products produces high correlation coefficients of 0.982, 0.986, 0.718, and 0.989, respectively, which verifies the effectiveness of the algorithm in different regions. Further, we analyzed the effectiveness of the proposed algorithm under different pollution conditions. Regions with AOD >0.7 and AOD < 0.7 are screened by using the AOD products of the Moderate-Resolution Imaging Spectroradiomete (MODIS), and the AOD of the corresponding region is inverted using POSP data. It was found to be spatially consistent with the MODIS products. The correlation coefficient and root mean square error (RMSE) in the AOD high region were 0.802 and 0.217, respectively, and 0.944 and 0.022 in the AOD low region, respectively, which verified the effectiveness of the proposed algorithm under different pollution conditions. Full article

The development of multi-component seismic acquisition technology creates new possibilities for the high-precision imaging of complex media. Compared to the scalar acoustic wave equation, the elastic wave equation takes the information of P-waves, S-waves, and converted waves into account simultaneously, enabling accurate description of actual seismic propagation. However, inherent attenuation is one of the important factors that restricts multi-component high-precision migration imaging. Its influence is mainly reflected in the following three ways: first, the attenuation of the amplitude energy makes the deep structure display unclear; second, phase distortion introduces errors to the positioning of underground structures; and third, the loss of high frequency components reduces imaging resolution. Therefore, it is crucial to fully consider the absorption and attenuation characteristics of the real Earth during seismic modeling and imaging. This paper aims to develop an accurate attenuation compensation reverse-time migration scheme for complex heterogeneous viscoelastic media. We first utilize a novel viscoelastic wave equation with decoupled fractional Laplacians to depict the Earth’s attenuation behavior. Then, an adaptive stable attenuation compensation operator is developed to realize high-precision attenuation compensation imaging. Several synthetic and field data analyses verify the effectiveness of the proposed method. Full article

Multi-component seismic data contain a great deal of vector field information that reflects the situation of the underground medium. However, the processing methods used for multi-component seismic data are still being developed, and effectively retaining and using this information is the difficulty and the focus of the task. Currently, the main-stream processing techniques of multi-component seismic data treat the individual components independently as a scalar field; in this way, they do not excavate the vector features of the wavefield, thus restricting the potential utilities of the effective information. Research into processing methods that are suitable for use with the vector field, which can better retain and use the orientations and the relative amplitude relationship between multi-component seismic data, is urgently needed and represent an important direction for the current development of multi-component seismic data processing techniques. In this paper, we introduce and summarize several existing vector pre-processing techniques, including polarization filtering, de-noising using vector order statistics, group sparse representation, and vector separation of compressional waves and shear waves, to help scholars develop more effective vector field processing methods and to promote the development of vector processing techniques for multi-component seismic data. Full article

Marine X-band radar based systems are well tested to provide information about sea state and bathymetry. It is also well known that complex geometries and non-uniform bathymetries provide a much bigger challenge than offshore scenarios. In order to tackle this issue a retrieval method is proposed, based on spatial partitioning of the data and the application of the Normalized Scalar Product (NSP), which is an innovative procedure for the joint estimation of bathymetry and surface currents. The strategy is then applied to radar data acquired around a harbour entrance, and results show that the reconstructed bathymetry compares well with ground truth data obtained by an echo-sounder campaign, thus proving the reliability of the whole procedure. The spectrum thus retrieved is then analysed to show the evidence of reflected waves from the harbour jetties, as confirmed by chain of hydrodynamic models of the sea wave field. The possibility of using a land based radar to reveal sea wave reflection is entirely new and may open up new operational applications of the system. Full article