Chinese Journal of Geophysics最新文献

For seismic random noise suppression, this work designs a steerable filter by taking advantage of elongated Hermite-Gauss functions. According to the different directional responses between valid signal and random noise, we can reconstruct signal by the local characteristics of selected data. With the added directional selectivity, the filtering process can match different direction axes, which makes sure that noise is suppressed without reducing the signal fidelity. The property of directional steerability makes computation more efficient and requires less storage space. Simulation results show that we can get better signal amplitude and denoising effects than traditional wavelet transform and Curvelet transform algorithm by using this method. At –5 db SNR, this method can ensure that the average amplitude reaches 92.99% and SNR enhances 221.774%, which can significantly suppress noise as well as keep the useful signal in processing of real seismic signals.

We study the P-wave structure around the 660 km discontinuity (660) beneath the eastern North China Craton (NCC), using a deep earthquake occurred at the border of northeast China and Russia and recorded by the China Digital Seismograph Network (CDSN). Best-fitting models are obtained with relative travel-time fittings and waveform comparisons. We find that the 660 km discontinuity is depressed by 15∼20 km, atop which there is a high-velocity layer about 115∼120 km thick with a velocity increase of 1.5%∼2.0%, which should be the stagnant slab of the Pacific plate; and below the 660, there is a local low-velocity anomaly with a velocity drop of 0.6%∼0.9%, which is possibly related to the slab dehydration from its bottom to the top of lower mantle or the dehydration of slab fragments that have collapsed into the deep lower mantle, or probably associated with the hot material upwelling induced by the slab deep subduction and the collapsing of slab fragments.

In this paper we propose Russell fluid factor direct estimation method based on stochastic seismic inversion. It is a Monte Carlo based strategy for non-linear inversion, which can effectively integrate the high-frequency information of well-logging data and have a higher resolution. And the method is formulated in a Bayesian framework. Firstly, we can calculate the Russell fluid factor using well-logging data and get the a priori information of fluid factor through sequential Gaussian simulation (SGS). Then we construct the likelihood function. Finally, we apply Metropolis algorithm in order to obtain an exhaustive description of the posteriori probability density. In this paper, we use the sequential Gaussian simulation (SGS) in a new implementation way, which can improve the computation speed. According to the numerical calculations, we can conclude that the final results match the model and real well-logging data well and have a higher resolution. In addition, Russell fluid factor we inverted is a sensitive indicator for reservoir fluid identification.

In order to improve the accuracy and computational efficiency of change detection of multi-temporal remote sensing images, a change detection algorithm based on contourlet transform and independent component analysis (ICA) is proposed. Firstly, multi-scale decomposition of image data is performed by using contourlet transform with multi-scale, directionality and anisotropy. Then independent component analysis is carried out for the decomposed data. And the independent data components are separated by the improved fixed point ICA algorithm based on Newton iteration. Next the separated data components are transformed into image components. Finally, change detection is achieved by threshold segmentation and filtering for change image components. The experimental results show that, compared with the existing three change detection algorithms such as the algorithm based on PCA, the algorithm based on ICA and the algorithm based on wavelet transform and ICA, the proposed algorithm in this paper more effectively separates change information and reduces computational complexity. The obtained change image has higher accuracy and strong robustness with respect to the background.

In this paper, a theoretical model of EM-MWD is set up based on the numerical mode matching method (NMM) and source equivalent principle. The model may consider radial and axial inhomogeneities, facilitate analysis of the influence of casing, mud, high conductivity layer, high resistivity layer on signal transmission. The correctness of this theoretical model is proved by calculation and field test. The effect of formation resistivity, working frequency, casing, drilling mud, pillar, high conductivity layer and high resistivity layer on the signal transmission is analyzed.

Suppressing the scattering induced by the laterally heterogeneous media is important for imaging the crustal structure and its anisotropy from Receiver Functions (RFs) based on the laterally stratified model. Although the scattering can be suppressed, to some degree, with stacking technique or low-pass filtering, these may lead to undesired waveform distortion, information loss or resolution reduction. To avoid these problems, we make use of the curvelet transform technique, which is developing rapidly in recent years, to reduce the scattering field in the RFs. Unlike exploration seismology, our major challenge comes from the spatially nonuniform sampling of RFs, caused by the spatially incomplete and uneven distribution of stations and events. To overcome these difficulties, we combine the compressed sensing theory with the curvelet-based denoising method to realize the denoising and wavefield reconstruction, simultaneously. To verify our idea, we have tested the denoising and wavefield reconstruction with synthetic RFs and then apply our method to the observed data at one of the IRIS GSN stations and the western Sichuan array, respectively. The results show that: 1) our method is efficient in suppressing the scattering induced by the lateral heterogeneity of the crust, which leads to great improvement of the signal-to-noise ratio and spatial traceability of the RFs. This is valuable for the waveform imaging of the crustal structure and anisotropic parameters from the RFs; 2) the missing data caused by the event distribution can be correctly reconstructed; 3) our method can be applied to either single station or seismic array observations, but it is more efficient in single station observation than the seismic array study.

The electron density profile inversion from vertical incidence ionograms is essential for research in ionospheric structures and movements, wave propagation and space weather applications, hence has gathered very wide attention. The echo trace of incompletely developed F₁ layer is common in vertical incidence ionograms, and it is usually expressed as smooth transition from F₁ layer to F₂ layer, not a cusp appeared at the critical frequency of F₁ layer. However, the existing ionospheric models and inversion algorithms are generally intended for the completely developed F₁ layer with the assumptions of a parabolic profile and an infinite slope at the peak of F₁ layer, which are not suitable for the profile of incompletely developed F₁ layer which achieves the maximum electron density of F₁ layer and enters F₂ layer at the peak of F₁ layer and has a finite slope. Consequently, an F₁ layer electron density profile model based on the shifted Chebyshev polynomial for incompletely developed case of F₁ layer is introduced with a parameter named as the model setting critical frequency. Taking into account the profile smoothness, an electron density profile inversion algorithm with constrained optimization F₁ and F₂ layer parameters based on the model mentioned above is proposed. The validity of the model and the inversion algorithm is analyzed through the simulation, and the effectivity of the proposed algorithm is further verified by the comparison between the synthesized vertical sounding & oblique sounding traces and the measured data.

Time-Frequency Response Spectrum (TFRS) is a three-dimensional spectrum, which includes three main characteristics of ground motion: amplitude, frequency characteristic and duration. Based on it, Normalized Time-Frequency Response Spectrum (NTFRS) was proposed and the NTFRS of three typical seismic waves were calculated. The comparison of three NTFRS shows that spectra amplitudes distributed along period axis and duration axis are different from each other; the large difference may cause different effect on the structures. One 12-storey reinforced concrete frame structure was analyzed by using elastic-plastic time-history analysis method. The comparison of the seismic response, structural damage curve and NTFRS of input ground motion shows that the maximum seismic response of structure might not be the cause of its collapse. It implies that the traditional response spectrum theory has limitation because in the theory the maximum elastic response of structures is used to make seismic design. It could be concluded that the Normalized Time-Frequency Response Spectrum is better for analyzing the characteristics of ground motions and the structural failure mechanism in the earthquakes.

Due to the particular seafloor environment and the special outer mechanical structure of the ocean bottom seismometer (OBS), there are some problems that have not been solved in the lithospheric structure inversion using the OBS teleseismic receiver functions. Based on the analysis of these problems, we combined the Fourier transform and wavelet analysis to suppress the non-stationary noise to obtain a better signal-to-noise ratio and clearer seismic phases recorded by the OBSs at the southwestern subbasin in the South China Sea (SCS). The equipment is a broadband OBS of I-4C type produced by the Institute of Geology and Geophysics, Chinese Academy of Sciences. We then inverted the lithospheric structure by successfully applying the receiver functions to the teleseismic data recorded at the southwestern subbasin in the SCS. The results show that it is feasible to use the receiver functions for the inversion of the lithosphere structure based on the passive observation data collected via the OBS, in which the key is to suppress the non-stationary noise. The Moho depth at the southwestern subbasin in the SCS is 10∼12 km, with a crust thickness of 6∼8 km. The shallow crust is a low velocity layer with sediment thickness 1∼2 km, which consists of sediment and volcanic clastic breccia produced by the magma eruption after the spreading cessation. In the spreading axis center, a low S-wave velocity zone exists at the depths of 6 km to 12 km above the Moho. We interpreted this zone as the result of partial melting of the lower crust or the presence of a magma chamber. In the same area at the depths of 17 km to 30 km, the vertical S-wave velocity gradient is negative. We interpreted it as the result of the hot magma supply moving upward in the mantle.