共查询到20条相似文献，搜索用时 15 毫秒
1.
在浅水情况下,由于观测数据中缺少近偏移距信息,水层多次波的压制面临挑战.利用多道预测算子压制水层多次波是浅水环境下压制多次波的重要方法之一,这种方法先从输入数据中估计出多道预测算子,再将预测算子和输入数据做褶积预测出水层相关多次波.然而,估计的多道预测算子很容易受噪声污染,从而影响多次波模型的精度.所以,我们提出了改进的多道预测算子压制浅水多次波方法.该方法先从数据中估计出多道预测算子,并利用估计的算子构建出精确的水层模型;然后,通过计算算子的走时信息、估计振幅信息、合成新算子三个步骤来修正原始的多道预测算子.修正的算子不仅不受噪声影响,还含有精确的走时信息、可靠的振幅信息;最后,该方法用修正的算子来预测多次波,并结合自适应相减,将预测的多次波从输入数据中去除.通过合成数据和实际资料的验证表明,相比于原始的多道预测算子压制多次波方法,改进的方法能够取得更好的压制效果. 相似文献
2.
地震滑坡的滑距与重力滑坡的滑距有着显著的不同,科学预测地震发生时黄土地区滑坡的滑动距离是合理评估黄土地区滑坡风险和减轻滑坡灾害的有效方式之一。基于海原特大地震诱发黄土滑坡的400组野外调查数据,通过引入BP神经网络算法,论证了BP神经网络模型用于预测黄土地震滑坡滑距的适宜性和可行性;建立了地震诱发黄土滑坡滑距的BP神经网络预测模型,并通过67组数据进行了验证。BP神经网络算法和传统多元线性回归、多元非线性回归结果的对比显示,BP神经网络的预测更接近真实情况,具有较为理想的预测效果,可以用于黄土地震滑坡滑距的预测,并为圈定较为可靠的致灾范围提供依据。 相似文献
3.
N. R. Dalezios P. A. Tyraskis 《Stochastic Environmental Research and Risk Assessment (SERRA)》1990,4(1):43-53
The accuracy of an optimum interpolation technique in filling missing values in multichannel (or multisite) hydrologic series containing time-coincident data gaps is examined. The applied methodology is based on the maximum entropy method (MEM) of spectral estimation or multivariate autoregressive modeling and heavily depends upon the properties of multichannel prediction error filter (PEF). Six precipitation time series spatially located within a hydrologic basin are used and time-coincident artificial gaps are created in all six series. The performance of the technique is assessed by comparing the filled-in series to the observed and by employing spectral analysis. The results reveal the usefulness of the method in multichannel hydrologic analysis. 相似文献
4.
The accuracy of an optimum interpolation technique in filling missing values in multichannel (or multisite) hydrologic series containing time-coincident data gaps is examined. The applied methodology is based on the maximum entropy method (MEM) of spectral estimation or multivariate autoregressive modeling and heavily depends upon the properties of multichannel prediction error filter (PEF). Six precipitation time series spatially located within a hydrologic basin are used and time-coincident artificial gaps are created in all six series. The performance of the technique is assessed by comparing the filled-in series to the observed and by employing spectral analysis. The results reveal the usefulness of the method in multichannel hydrologic analysis. 相似文献
5.
J. A. Vargas-Guzmán T.-C. Jim Yeh 《Stochastic Environmental Research and Risk Assessment (SERRA)》1999,13(6):416-435
A sequential linear estimator is developed in this study to progressively incorporate new or different spatial data sets
into the estimation. It begins with a classical linear estimator (i.e., kriging or cokriging) to estimate means conditioned
to a given observed data set. When an additional data set becomes available, the sequential estimator improves the previous
estimate by using linearly weighted sums of differences between the new data set and previous estimates at sample locations.
Like the classical linear estimator, the weights used in the sequential linear estimator are derived from a system of equations
that contains covariances and cross-covariances between sample locations and the location where the estimate is to be made.
However, the covariances and cross-covariances are conditioned upon the previous data sets.
The sequential estimator is shown to produce the best, unbiased linear estimate, and to provide the same estimates and variances
as classic simple kriging or cokriging with the simultaneous use of the entire data set. However, by using data sets sequentially,
this new algorithm alleviates numerical difficulties associated with the classical kriging or cokriging techniques when a
large amount of data are used. It also provides a new way to incorporate additional information into a previous estimation. 相似文献
6.
Despite its importance, accurate representation of the spatial distribution of water table depth remains one of the greatest deficiencies in many hydrological investigations. Historically, both inverse distance weighting (IDW) and ordinary kriging (OK) have been used to interpolate depths. These methods, however, have major limitations: namely they require large numbers of measurements to represent the spatial variability of water table depth and they do not represent the variation between measurement points. We address this issue by assessing the benefits of using stepwise multiple linear regression (MLR) with three different ancillary data sets to predict the water table depth at 100-m intervals. The ancillary data sets used are Electromagnetic (EM34 and EM38), gamma radiometric: potassium (K), uranium (eU), thorium (eTh), total count (TC), and morphometric data. Results show that MLR offers significant precision and accuracy benefits over OK and IDW. Inclusion of the morphometric data set yielded the greatest (16%) improvement in prediction accuracy compared with IDW, followed by the electromagnetic data set (5%). Use of the gamma radiometric data set showed no improvement. The greatest improvement, however, resulted when all data sets were combined (37% increase in prediction accuracy over IDW). Significantly, however, the use of MLR also allows for prediction in variations in water table depth between measurement points, which is crucial for land management. 相似文献
7.
作为近地表横波速度结构成像的主要手段之一,面波多道分析法的正问题研究对现场观测系统设计及后续反演计算具有重要意义.目前面波频散曲线的正演主要分为两类:一是对水平层状介质中面波的本征值问题进行求解,该类方法计算效率高但较难考虑地下介质在横向上的不均匀性;二是基于波动方程的全波场模拟,该类方法在理论上可考虑任意复杂的地质模型但计算成本相对较高.本文基于振幅归一化加权的聚束分析,提出了一种适用于横向非均匀介质模型的多道瑞雷波频散曲线正演方法.首先,基于聚束分析的计算公式推导得到了经振幅归一化加权后输出功率谱中相速度与局部相速度之间的关系,然后通过黄金分割极值搜索算法计算得到了多道瑞雷波数据的理论频散曲线.数值分析结果表明,该算法能够快速地实现横向非均匀介质中多道瑞雷波频散曲线的正演计算,所求取的频散曲线与采用二维弹性波时间域有限差分模拟分析得到的结果误差较小,这在一定程度上说明了该计算方法的可靠性,从而可为面波多道分析法中的观测系统快速优化设计以及横向非均匀介质中频散曲线的反演解释提供理论支撑. 相似文献
8.
神经网络模型在地震预报中的某些应用 总被引：2，自引：2，他引：2
本文介绍了人工神经网络模型以地震活动性指标为基础应用于地震预报的一些最新研究结果，选用多层前向神经网络模型及ＢＰ算法，其输入取不同的地震活动性指标的集合，输出为某一指定地区在未来时段内可能发生的最大地震的震级，以华北及首都圈地区为例，用多组不同类型的地震活动性指标进行学习与检验，结果表明，利用人工神经网络模型对未来时段震级预报的符合率较高，内检预报符合率可达１００％，外推预报符合率达到６０％以上。 相似文献
9.
A new spectral factorization method is presented for the estimation of a causal as well as a causally invertible ARMA operator from the correlation sequence of seismic traces. The method has been implemented for multichannel deconvolution of seismic traces with the aim of exploiting the trace-to-trace correlation that exists within seismograms. A layered earth model with a small reflectivity sequence has been considered, and the seismic traces have been considered as the output of a linear system driven by white noise reflection coefficient sequences. The present method is the concatenation of three algorithms, namely Kung's method for state variable ( F , G , H ) realization using a singular value decomposition (SVD) algorithm, Faurre's technique for computation of the strong spectral factor and Leverrier's algorithm for ARMA representation of the spectral factor. The inverted ARMA operator is used as a recursive filter for deconvolution of seismic traces. In the example shown, two traces with a covariance sequence of 160 ms length have been considered for multichannel deconvolution of stacked seismic traces. The results presented, when compared with those obtained from a conventional deconvolution algorithm, have shown encouraging prospects. 相似文献
10.
Prediction of effective porosity from seismic attributes using locally linear model tree algorithm 
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下载免费PDF全文 Ahmad Ashtari Talkhestani 《Geophysical Prospecting》2015,63(3):680-693
In this study, a locally linear model tree algorithm was used to optimize a neuro‐fuzzy model for prediction of effective porosity from seismic attributes in one of Iranian oil fields located southwest of Iran. Valid identification of effective porosity distribution in fractured carbonate reservoirs is extremely essential for reservoir characterization. These high‐accuracy predictions facilitate efficient exploration and management of oil and gas resources. The multi‐attribute stepwise linear regression method was used to select five out of 26 seismic attributes one by one. These attributes introduced into the neuro‐fuzzy model to predict effective porosity. The neuro‐fuzzy model with seven locally linear models resulted in the lowest validation error. Moreover, a blind test was carried out at the location of two wells that were used neither in training nor validation. The results obtained from the validation and blind test of the model confirmed the ability of the proposed algorithm in predicting the effective porosity. In the end, the performance of this neuro‐fuzzy model was compared with two regular neural networks of a multi‐layer perceptron and a radial basis function, and the results show that a locally linear neuro‐fuzzy model trained by a locally linear model tree algorithm resulted in more accurate porosity prediction than standard neural networks, particularly in the case where irregularities increase in the data set. The production data have been also used to verify the reliability of the porosity model. The porosity sections through the two wells demonstrate that the porosity model conforms to the production rate of wells. Comparison of the locally linear neuro‐fuzzy model performance on different wells indicates that there is a distinct discrepancy in the performance of this model compared with the other techniques. This discrepancy in the performance is a function of the correlation between the model inputs and output. In the case where the strength of the relationship between seismic attributes and effective porosity decreases, the neuro‐fuzzy model results in more accurate prediction than regular neural networks, whereas the neuro‐fuzzy model has a close performance to neural networks if there is a strong relationship between seismic attributes and effective porosity. The effective porosity map, presented as the output of the method, shows a high‐porosity area in the centre of zone 2 of the Ilam reservoir. Furthermore, there is an extensive high‐porosity area in zone 4 of Sarvak that extends from the centre to the east of the reservoir. 相似文献
11.
HENRY J. MEYERHOFF 《Geophysical Prospecting》1966,14(4):441-454
The common depth point method of shooting in oil exploration provides a series of seismic traces which yield information about the substrata layers at one location. After normal moveout and static corrections have been applied, the traces are combined by horizontal stacking, or linear multichannel filtering, into a single record in which the primary reflections have been enhanced relative to the multiple reflections and random noise. The criterion used in optimum horizontal stacking is to maximize the signal to noise power ratio, where signal refers to the primary reflection sequence and noise includes the multiple reflections. It is shown when this criterion is equivalent to minimizing the mean square difference between the desired signal (primary reflection sequence) and the weighted horizontally stacked traces. If the seismic traces are combined by multichannel linear filtering, the primary reflection sequence will have undergone some phase and frequency distortion on the resulting record. The signal to noise power ratio then becomes less meaningful a criterion for designing the optimum linear multichannel filter, and the mean square criterion is adopted. In general, however, since more a priori information about the seismic traces is required to design the optimum linear multichannel filter than required for the optimum set of weights of the horizontal stacking process, the former will be an improvement over the latter. It becomes evident that optimum horizontal stacking is a restricted form of linear multichannel filtering. 相似文献
12.
HENRY J. MEYERHOFF 《Geophysical Prospecting》1966,14(Z2):441-453
The common depth point method of shooting in oil exploration provides a series of seismic traces which yield information about the substrata layers at one location. After normal moveout and static corrections have been applied, the traces are combined by horizontal stacking, or linear multichannel filtering, into a single record in which the primary reflections have been enhanced relative to the multiple reflections and random noise. The criterion used in optimum horizontal stacking is to maximize the signal to noise power ratio, where signal refers to the primary reflection sequence and noise includes the multiple reflections. It is shown when this criterion is equivalent to minimizing the mean square difference between the desired signal (primary reflection sequence) and the weighted horizontally stacked traces. If the seismic traces are combined by multichannel linear filtering, the primary reflection sequence will have undergone some phase and frequency distortion on the resulting record. The signal to noise power ratio then becomes less meaningful a criterion for designing the optimum linear multichannel filter, and the mean square criterion is adopted. In general, however, since more a priori information about the seismic traces is required to design the optimum linear multichannel filter than required for the optimum set of weights of the horizontal stacking process, the former will be an improvement over the latter. It becomes evident that optimum horizontal stacking is a restricted form of linear multichannel filtering. 相似文献
13.
The Selection of Field Acquisition Parameters for Dispersion Images from Multichannel Surface Wave Data 总被引：3，自引：0，他引：3
The accuracy and resolution of surface wave dispersion results depend on the parameters used for acquiring data in the field. The optimized field parameters for acquiring multichannel analysis of surface wave (MASW) dispersion images can be determined if preliminary information on the phase velocity range and interface depth is available. In a case study on a fill slope in Hong Kong, the optimal acquisition parameters were first determined from a preliminary seismic survey prior to a MASW survey. Field tests using different sets of receiver distances and array lengths showed that the most consistent and useful dispersion images were obtained from the optimal acquisition parameters predicted. The inverted S-wave velocities from the dispersion curve obtained at the optimal offset distance range also agreed with those obtained by using direct refraction survey. 相似文献
14.
15.
Multichannel filtering to obtain wavefield separation has been used in seismic processing for decades and has become an essential component in VSP and cross-well reflection imaging. The need for good multichannel wavefield separation filters is acute in borehole seismic imaging techniques such as VSP and cross-well reflection imaging, where strong interfering arrivals such as tube waves, shear conversions, multiples, direct arrivals and guided waves can overlap temporally with desired arrivals. We investigate the effects of preprocessing (alignment and equalization) on the quality of cross-well reflection imaging wavefield separation and we show that the choice of the multichannel filter and filter parameters is critical to the wavefield separation of cross-well data (median filters, f–k pie-slice filters, eigenvector filters). We show that spatial aliasing creates situations where the application of purely spatial filters (median filters) will create notches in the frequency spectrum of the desired reflection arrival. Eigenvector filters allow us to work past the limits of aliasing, but these kinds of filter are strongly dependent on the ratio of undesired to desired signal amplitude. On the basis of these observations, we developed a new type of multichannel filter that combined the best characteristics of spatial filters and eigenvector filters. We call this filter a ‘constrained eigenvector filter’. We use two real data sets of cross-well seismic experiments with small and large well spacing to evaluate the effects of these factors on the quality of cross-well wavefield separation. We apply median filters, f–k pie-slice filters and constrained eigenvector filters in multiple domains available for these data sets (common-source, common-receiver, common-offset and common-midpoint gathers). We show that the results of applying the constrained eigenvector filter to the entire cross-well data set are superior to both the spatial and standard eigenvector filter results. 相似文献
16.
介绍了人工智能领域最新的基于结构风险最小化原理的数据挖掘算法——支持向量机算法。根据支持向量机线性分类和可以具有不同核函数的非线性分类两种算法,建立了地震序列分类模型。通过试算和分析比较得到了地震序列最佳分类模型,最佳模型的分类结果与实际地震序列分类基本一致。综合分析认为支持向量机算法无论在学习或者预测精度方面都具有很大的优越性,其获得的地震序列分类知识库可以较为准确地实现地震序列类型的分类,因此基于支持向量机理论建立的地震序列分类模型应该是可行的。 相似文献
17.
Seismic data processing is a challenging task, especially when dealing with vector-valued datasets. These data are characterized by correlated components, where different levels of uncorrelated random noise corrupt each one of the components. Mitigating such noise while preserving the signal of interest is a primary goal in the seismic-processing workflow. The frequency-space deconvolution is a well-known linear prediction technique, which is commonly used for random noise suppression. This paper represents vector-field seismic data through quaternion arrays and shows how to mitigate random noise by proposing the extension of the frequency-space deconvolution to its hypercomplex version, the quaternion frequency-space deconvolution. It also shows how a widely linear prediction model exploits the correlation between data components of improper signals. The widely linear scheme, named widely-linear quaternion frequency-space deconvolution, produces longer prediction filters, which have enhanced signal preservation capabilities shown through synthetic and field vector-valued data examples. 相似文献
18.
控制路基沉降是公路工程中的一个关键技术问题,而路基沉降与其影响因素之间存在着线性、非线性关系。当输入自变量较多时,用传统神经网络建模容易出现过拟合现象,导致网络模型预测精度较低。针对此问题,本文用遗传算法对神经网络模型的权值和阈值进行优化,同时讨论遗传参数的设定对输出结果的影响。通过对成南高速的实测数据进行仿真,试验结果表明:优化后的BP神经网络具有较高的预测精度,预测效果明显优于传统神经网络模型的输出结果,该预测方法可作为高速公路路基长期沉降预测的一种有效辅助手段。 相似文献
19.
基于非因果滤波器的多次波匹配相减方法(英文) 总被引：1，自引：0，他引：1
在常规多道匹配滤波方法中的滤波器是物理可实现的因果滤波器,只能实现地震信号序列延迟的滤波。本文提出了最小二乘意义下的非因果多道输入多道输出维纳滤波方法,通过比较多道匹配相减中因果和非因果滤波方法之间的差别,验证了方法的有效性,解决了模型数据滞后于实际数据的情况。而且,通过定义长度随偏移距和层速度变化的滑动时窗,解决了匹配时窗内同相轴数量随偏移距增大而增加的问题。并将上述方法应用到改进的扩展多道匹配相减去除多次波的方法中,利用Pluto1.5理论模拟数据,对非因果滤波器和变长度时窗的匹配相减方法进行测试,取得了很好的去除多次波后的地震数据。 相似文献
20.
Network of seismo-geochemical monitoring observatories for earthquake prediction research in India 总被引：2，自引：0，他引：2
Hirok Chaudhuri Chiranjib Barman A. N. Sekar Iyengar Debasis Ghose Prasanta Sen Bikash Sinha 《Acta Geophysica》2013,61(4):1000-1025
Present paper deals with a brief review of the research carried out to develop multi-parametric gas-geochemical monitoring facilities dedicated to earthquake prediction research in India by installing a network of seismo-geochemical monitoring observatories at different regions of the country. In an attempt to detect earthquake precursors, the concentrations of helium, argon, nitrogen, methane, radon-222 (222Rn), polonium-218 (218Po), and polonium-214 (214Po) emanating from hydrothermal systems are monitored continuously and round the clock at these observatories. In this paper, we make a cross correlation study of a number of geochemical anomalies recorded at these observatories. With the data received from each of the above observatories we attempt to make a time series analysis to relate magnitude and epicentral distance locations through statistical methods, empirical formulations that relate the area of influence to earthquake scale. Application of the linear and nonlinear statistical techniques in the recorded geochemical data sets reveal a clear signature of long-range correlation in the data sets. 相似文献