Magnetotelluric data inversion with seismic data constraint

Introduction The research on the structure and physical property of ancient hidden hill, igneous rocks and basement is relatively difficult by using seismic data only. If we combine seismic data, magneto-telluric (MT) data and geophysical data together, better results can be obtained for the above problem. A number of geophysicists at home and abroad, such as CHEN and WANG (1990), Siri-punvarapor and Egbert (2000) have tried many methods to solve the problem by the inversion of seismic da…     

数据自相关多次波偏移成像

在常规偏移方法中一般都需要压制地震数据中的多次波,仅利用一次波信息成像,把自由表面反射的多次波视为噪声,但是在多次波中也包含着地下结构信息,应该将其充分利用到成像中来.事实上,已经有不少成像方法试图利用多次波信息,但是大部分方法都需要对多次波进行预测.本文提出了基于傅里叶有限差分偏移算子的数据自相关偏移方法.在这种偏移方法中,对含有一次波和多次波的地震数据,分别进行下行和上行延拓,然后直接利用常规的互相关成像条件成像.由于波场延拓采用了傅里叶有限差分算子,其计算效率高,能够很好地对复杂介质中的地震数据进行延拓.在数值试验中,使用了一个含散射点的三层模型和Marmousi模型.合成数据测试结果表明,这种方法可以对更大范围的地下构造成像,比常规的只利用一次波的傅里叶有限差分法照明度更好,并且在浅层可以提供更高的分辨率.我们提出的数据自相关策略易于实现且避免了繁杂的多次波预测,这对于复杂地下构造成像可能有着重大意义.     

基于大数据技术的地震数据处理新思路

现代地震观测积累了大量、种类繁多的地震前兆数据和震后数据,但数据中隐含的地震规律及趋势无法用经典的算例、数学公式、物理公式进行定量解释、分析和预测,需要探索新方法、新技术。案例表明,大数据分析具有预测事物发展趋势、改变传统观念和发现新事物的功能,有助于从错误信息中挖掘有价值信息。本文由此提出基于大数据技术处理地震数据的新思路,对地震监测预报新思路进行探索;通过在大数据平台上基于地震目录的余震预测研究,给出大数据技术在地震数据处理方面的一个应用实例,验证该思路的可行性。     

An automatic method for data processing of seismic data in tunneling

We present a new method for the prediction of the discontinuities and lithological variations ahead of the tunnel face. The automatic procedure is applied to data collected by seismic reflection surveys, with the sources and sensors located along the tunnel. The method allows: i) to estimate an average value of the wave velocity; ii) to detect the discontinuities for each source point; and iii) to analyze and plot the number of superposing estimates for each node of the domain. The final result can be interpreted as the probability to detect a discontinuity at a certain distance from the tunnel face. The method automatically estimates the peaks in the seismograms that can be related to a reflection. On the base of this process, the method only requires the source–receiver geometry and the data acquisition parameters. The procedure has been tested on synthetic and real data coming from a seismic survey on a tunnel under construction. The results indicate that the method runs very fast and it is reliable in the identification of lithological changes and discontinuities, up to more than 100 m ahead of the tunnel face.     

Nonlinear data processing method for the signal enhancement of GPR data

An alternative data processing procedure is proposed in this paper for the purpose of enhancing the signal/noise (S/N) ratio of ground penetrating radar (GPR) data. The processing methodology is achieved by performing the logarithmic transform in conjunction with the ensemble empirical mode decomposition (EEMD), a new nonlinear data analysis method in signal processing. The synthetic model study and field example indicate that the logarithmic transform is effective in alleviating the attenuation problem. Additionally, the spectrogram obtained from Hilbert-Huang transform (HHT) shows that the decomposition sensitivity of the EEMD method is greatly improved with the aid of the logarithmic transform. This new method allows us to extract the signal components from noisy GPR data efficiently. The success of this study suggests a possible nonlinear analysis application in future GPR investigation, particularly in the filter design and gain correction.     

Processing of magnetotelluric data

The processing of magnetotelluric data involves concepts from electromagnetic theory, time series analysis and linear systems theory for reducing natural electric and magnetic field variations recorded at the earth's surface to forms suitable for studying the electrical properties of the earth's interior.The electromagnetic field relations lead to either a scalar transfer impedance which couples an electric component to an orthogonal magnetic component at the surface of a plane-layered earth, or a tensor transfer impedance which couples each electric component to both magnetic components in the vicinity of a lateral inhomogeneity.A number of time series spectral analysis methods can be used for estimating the complex spectral coefficients of the various field quantities. These in turn are used for estimating the nature of the transfer function or tensor impedance. For two dimensional situations, the tensor impedance can be rotated to determine the principal directions of the electrical structure.In general for real data, estimates of the apparent resistivity are more stable when calculated from the tensor elements rather than from simple orthogonal field ratios (Cagniard estimates), even when the fields are measured in the principal coordinates.     

A platform for Kirchhoff data mapping in scalar models of data acquisition

Kirchhoff data mapping (KDM) is a procedure for transforming data from a given input source/receiver configuration and background earth model to data corresponding to a different output source/receiver configuration and background model. The generalization of NMO/DMO, datuming and offset continuation are three examples of KDM applications. This paper describes a 'platform' for KDM for scalar wavefields. The word, platform, indicates that no calculations are carried out in this paper that would adapt the derived formula to any one of a list of KDMs that are presented in the text. Platform formulae are presented in 3D and in 2.5D. For the latter, the validity of the platform equation is verified — within the constraints of high-frequency asymptotics — by applying it to a Kirchhoff approximate representation of the upward scattered data from a single reflector and for an arbitrary source/receiver configuration. The KDM formalism is shown to map this Kirchhoff model data in the input source/receiver configuration to Kirchhoff data in the output source/receiver configuration, with one exception. The method does not map the reflection coefficient. Thus, we verify that, asymptotically, the ray theoretical geometrical spreading effects due to propagation and reflection (including reflector curvature) are mapped by this formalism, consistent with the input and output modelling parameters, while the input reflection coefficient is preserved. In this sense, this is a 'true-amplitude' formalism. As with earlier Kirchhoff inversion, a slight modification of the kernel of KDM provides alternative integral operators for estimating the specular reflection angle, both in the input configuration and in the output configuration, thereby providing a basis for amplitude-versus-angle analysis of the data.     

Super-resolution data assimilation

Ocean Dynamics - Increasing model resolution can improve the performance of a data assimilation system because it reduces model error, the system can more optimally use high-resolution...     

利用地基观测对卫星观测电离层结构参数的定量验证研究

本文采用散点图、趋势线、相关系数及观测偏差等统计方法,利用COSMIC卫星和SPIDR提供的垂测仪观测的F₂层峰值电子密度数据,开展了综合统计及按季节、地方时和纬度的分类统计.统计结果显示:地基垂测仪与卫星观测到的相应的F₂层峰值电子密度数据具有很高的相关性,两者之间的相关系数高达0.95,相对偏差的平均值为-3.38%,标准差为19.54%.基于上述研究结果,提出了利用地面垂测仪观测数据验证卫星观测的电离层结构参数的方法,并给出了定性的判别依据和定量的判别标准,可在我国电磁监测试验卫星发射后,为F₂层峰值电子密度观测数据的真实性和有效性提供检验方法和保障.      

Tests of data assimilation and data initialization for the purposes of short-range weather forecast

Summary The initialization and assimilation of input data were studied and tested by the adiabatic version of a simple numerical model for short-range weather forecast.The initialization was based on the utilization of a digital filter technique. The method succeeded in removing high-frequency oscillations from prognostic pressure fields. However, excessive smoothing deteriorated the accuracy of the prediction at the lowest levels of the atmosphere.The data assimilation was performed using the nudging method. Three versions of the nudging method in a splitting scheme were tested. The inclusion of the assimilation at the end of the integration step proved to be the best. The assimilation damped the oscillations of prognostic surface pressure fields and slightly improved the pressure prediction at the lowest levels of the atmosphere.     

Spectral analysis of climate data

The complexity of climate variability on all time scales requires the use of several refined tools to unravel its primary dynamics from observations. Indeed, ideas from the theory of dynamical systems have provided new ways of interpreting the information contained in climatic time series.We review the properties of several modern time series analysis methods. Those methods belong to four main classes: Fourier techniques (Blackman-Tukey and Multi-Taper), Maximum Entropy technique, Singular-spectrum techniques and wavelet analysis. Their respective advantages and limitations are illustrated by numerical experiments on synthetic time series. As climate data can be irregularly spaced in time, we also compare three interpolating methods on those time series. Those tests are aimed at showing the pitfalls of the blind use of mathematical or statistical techniques on climate data.We apply those methods to real climatic data from temperature variations over the last century, and the Vostok ice core deuterium record over the last glacial cycle. Then we show how interpretations on the dynamics of climate can be derived on those time scales.     

Resolution of airborne VLF data

The interpretation of airborne VLF data represents an important aspect of geophysical mapping of the upper few hundred meters of the Earth's crust, especially in areas with crystalline rocks. We have examined the ability of the single frequency VLF method to provide quantitative subsurface resistivity information using two generic models and standard airborne parameters with a flight altitude of 70 m and a frequency of 16 kHz. The models are long thin conductor (10 m thick, 10 Ω m resistivity and 1 km long) and a wider buried conductive dike (100 Ω m resistivity and 500 m wide). Using standard regularized inversion it turned out that for both models the conductivity of the conductors are underestimated and the vertical resolution is rather poor. The lateral positions of the minimum of the resistivity distributions coincide well with the true positions of the shallow conductors. For deeper conductors the position of the minimum resistivity moves from the edges of the conductor into the conductor. The depth to the minimum of the resistivity anomalies correlates well with the true depth to the top of the conductors although the latter is always smaller than the former.Interpretation of field airborne data collected at 70 m flight height resolved both small scale and large scale near surface conductors (conductance ∼1 S). Deeper conductors show up in the VLF data as very long wavelength anomalies that are particularly powerful in delineating the lateral boundaries of the conductors. Many of the VLF anomalies in the Stockholm area are dominated by these deep conductor responses with some near surface conductors superimposed. The deep conductors often follow topographic lows coinciding with metasediments. We interpret the frequent absence of near surface responses at 70 m flight height as a result of weak coupling between the primary VLF wave and the small scale (in all three dimensions) near-surface conductors.Radio magnetotelluric (RMT) ground measurements were carried out along a short profile coinciding with part of an airborne profile. Using data at 9 frequencies (14–250 kHz) small scale conductors in the upper few tens of meters, not identified from the airborne data, could be well resolved. Large scale deeper conductors could be identified by both methods at nearly the same positions.     

Inversion of GPS meteorology data

The GPS meteorology (GPS/MET) experiment, led by the Universities Corporation for Atmospheric Research (UCAR), consists of a GPS receiver aboard a low earth orbit (LEO) satellite which was launched on 3 April 1995. During a radio occultation the LEO satellite rises or sets relative to one of the 24 GPS satellites at the Earths horizon. Thereby the atmospheric layers are successively sounded by radio waves which propagate from the GPS satellite to the LEO satellite. From the observed phase path increases, which are due to refraction of the radio waves by the ionosphere and the neutral atmosphere, the atmospheric parameter refractivity, density, pressure and temperature are calculated with high accuracy and resolution (0.5–1.5 km). In the present study, practical aspects of the GPS/MET data analysis are discussed. The retrieval is based on the Abelian integral inversion of the atmospheric bending angle profile into the refractivity index profile. The problem of the upper boundary condition of the Abelian integral is described by examples. The statistical optimization approach which is applied to the data above 40 km and the use of topside bending angle profiles from model atmospheres stabilize the inversion. The retrieved temperature profiles are compared with corresponding profiles which have already been calculated by scientists of UCAR and Jet Propulsion Laboratory (JPL), using Abelian integral inversion too. The comparison shows that in some cases large differences occur (5 K and more). This is probably due to different treatment of the upper boundary condition, data runaways and noise. Several temperature profiles with wavelike structures at tropospheric and stratospheric heights are shown. While the periodic structures at upper stratospheric heights could be caused by residual errors of the ionospheric correction method, the periodic temperature fluctuations at heights below 30 km are most likely caused by atmospheric waves (vertically propagating large-scale gravity waves and equatorial waves).Present address: Communications Research Laboratory, Upper Atmosphere Section, 4-2-1 Nukui- Kita, Koganei- shi, Tokyo 184, Japan     

Scale-recursive assimilation of precipitation data

This paper presents a new statistical method for assimilating precipitation data from different sensors operating over a range of scales. The technique is based on a scale-recursive estimation algorithm which is computationally efficient and able to account for the nested spatial structure of precipitation fields. The version of the algorithm described here relies on a static multiplicative cascade model which relates rainrates at different scales. Bayesian estimation techniques are used to condition rainrate estimates on measurements. The conditioning process is carried out recursively in two sweeps: first from fine to coarse scales and then from coarse to fine scales. The complete estimation algorithm is similar to a fixed interval smoother although it processes data over scale rather than time. We use this algorithm to assimilate radar and satellite microwave data collected during the tropical ocean–global atmosphere coupled ocean–atmosphere response experiment (TOGA-COARE). The resulting rainrate estimates reproduce withheld radar measurements to within the level of accuracy predicted by the assimilation algorithm.     

新一代中国数字地震台网(NCDSN)数据的应用

中美地震科技合作至今已20多年了,通过中美地震科技合作建成的中国数字地震台网(CDSN)在我国已运行了16个年头,它为我国数字地震观测技术的发展提供了借鉴,也促进了我国数字地震学的研究和地震预报工作开展。 第2代数字地震观测系统不仅具有远程数据快速传输的能力,而且具有动态范围更大,记录频带更宽的特点。从STS-1地震计中滤波出来的UH信号,能观测地球的自由振荡信