共查询到20条相似文献，搜索用时 31 毫秒
1.
Multiple prediction and subtraction techniques based on wavefield extrapolation are effective for suppressing multiple related to water layers.In the conventional wavefield extrapolation method, the multiples of the seismic data are predicted from the known total wave field by the Green function convoluted with each point of the bottom.However, only the energy near the stationary phase point has an effect on the summation result when the convolutional gathers are added.The research proposed a stationary phase point extraction method based on high-resolution radon transform.In the radon domain, the energy near the stationary phase point is directly added along the convolutional gathers curve, which is a valid solution to the problem of the unstable phase of the events of multiple.The Curvelet matching subtraction technique is used to remove the multiple, which improved the accuracy of the multiple predicted by the wavefield extrapolation and the artifacts appearing around the events of multiple are well eliminated.The validity and feasibility of the proposed method are verified by the theoretical and practical data example. 相似文献
2.
基于GPU并行加速的叠前逆时偏移方法 总被引：1，自引：1，他引：0
为了提高复杂地下介质的成像精度和偏移算法的计算效率,提出可高效对地下复杂构造进行准确成像的GPU加速叠前逆时偏移方法.该方法采用双程声波方程进行波场延拓,突破倾角限制,借助于高阶有限差分方法实现叠前逆时偏移成像;利用GPU(Graphic Processing Unit)并行加速技术对波场延拓和成像进行计算,相比于传统算法,其计算效率有较大提高,可以解决叠前逆时偏移算法计算量过大问题;在获取波场信息过程中,也采用随机边界条件,实施以计算换存储策略,解决逆时偏移计算中的海量存储问题.模型测试结果表明,该方法能够高效和高精度地对地下复杂地质体成像. 相似文献
3.
The surface-related multiple elimination (SRME) method is based on feedback formulation and has become one of the most preferred multiple suppression methods used. However, some differences are apparent between the predicted multiples and those in the source seismic records, which may result in conventional adaptive multiple subtraction methods being barely able to effectively suppress multiples in actual production. This paper introduces a combined adaptive multiple attenuation method based on the optimized event tracing technique and extended Wiener filtering. The method firstly uses multiple records predicted by SRME to generate a multiple velocity spectrum, then separates the original record to an approximate primary record and an approximate multiple record by applying the optimized event tracing method and short-time window FK filtering method. After applying the extended Wiener filtering method, residual multiples in the approximate primary record can then be eliminated and the damaged primary can be restored from the approximate multiple record. This method combines the advantages of multiple elimination based on the optimized event tracing method and the extended Wiener filtering technique. It is an ideal method for suppressing typical hyperbolic and other types of multiples, with the advantage of minimizing damage of the primary. Synthetic and field data tests show that this method produces better multiple elimination results than the traditional multi-channel Wiener filter method and is more suitable for multiple elimination in complicated geological areas. 相似文献
4.
LI Qiang MAO Xianzhong DENG Guotong ZHAO Ruixiang ZHANG Chuanzheng ZHU Xiaohua 《中国海洋大学学报(英文版)》2019,(4)
Internal tides generated by a rough sea floor are an important source of mixing in the abyssal ocean. Two linear models are employed to evaluate the conversion rate from barotropic tides to internal tides and the energy distribution in each mode. Considering the periodicity of internal tides, the topography is represented by periodically distributed knife edges and sinusoidal ridges within one wavelength of mode-1 internal tides. The knife edges generate greater internal tides than the sinusoidal ridges due to their sharp shape, which approximates an extremely supercritical condition. Energy flux concentrates in modes whose numbers are multiples of the knife edge or ridge number. Then, a fully nonlinear model that integrates viscosity and diffusion is implemented, and its results are compared with those of the linear model. Internal wave rays generated in the nonlinear model show a distribution similar to the linear models' prediction. High dissipation rates coincide with the rays, suggesting that nonlinear wave-wave interaction is a dominant mechanism for internal tide dissipation in the abyssal ocean. 相似文献
5.
在对"等待时间法"进行残差结构分析的基础上提出基于加权最小二乘拟合的模型改进方法,并将其应用于尼泊尔地震的强余震预测。结果表明,由模型误差转换至时间误差具有ln10·Δt倍的缩放效果,选择主震后3d内的余震样本进行强余震预测结果较为可信。实际震例表明,加权最小二乘模型可以有效降低模型预测误差,缩小预测值置信区间,从而提高预测的实用性。 相似文献
6.
Based on surfaced-related multiple elimination (SRME),this research has derived the methods on multiples elimination in the inverse data space.Inverse data processing means moving seismic data from forward data space (FDS) to inverse data space (IDS).The surface-related multiples and primaries can then be separated in the IDS,since surface-related multiples will form a focus region in the IDS.Muting the multiples energy can achieve the purpose of multiples elimination and avoid the damage to primaries energy during the process of adaptive subtraction.Randomized singular value decomposition (RSVD) is used to enhance calculation speed and improve the accuracy in the conversion of FDS to IDS.The synthetic shot record of the salt dome model shows that the relationship between primaries and multiples is simple and clear,and RSVD can easily eliminate multiples and save primaries energy.Compared with conventional multiples elimination methods and ordinary methods of multiples elimination in the inverse data space,this technique has an advantage of high calculation speed and reliable outcomes. 相似文献
7.
位置预测技术可以提前预知用户下一时刻的位置,在基于位置的服务（Location-based Service,LBS）领域中发挥着极其重要的作用。现有的位置预测技术大多仅使用用户的地理轨迹,仅使用地理轨迹挖掘出来的用户移动模式易受地理特性的限制缺乏深层次的语义信息。本文基于某商场群体用户的室内轨迹数据和语义信息预测用户下一个时刻语义位置。语义位置预测包括停留区域识别、停留区域语义匹配、语义位置建模。在停留区域识别阶段,为减少室内停留时间不固定对停留区域识别的影响,本研究提出了一种新型的时空凝聚层次聚类算法（Spatial-Temporal Agglomerative Nesting, ST-AGNES),该算法具有思想简单、超参数少、自动生成聚类个数等优点。在语义匹配阶段,引入了吸引度规则,充分利用停留区域所有轨迹点与室内高密度的商铺名称信息做匹配。最后,采用长短型记忆神经网络模型（Long Short-Term Memory,LSTM）挖掘群体用户的语义位置模式并预测用户未来的语义位置,实验预测正确率达到61.3%。 相似文献
8.
Remigration is an imaging method that maps migrated image fields of different migration velocity fields to each other.It is mainly used for migration velocity analysis, wave mode transformation, and data regu-larization.Theoretically, this kind of mapping can be realized by differential operator, or by integral operator. Compared between the two, the integral operator achieves higher computational efficiency and has more adapta-bility to the irregularity of the input data.Given the fact, the authors worked out the depth domain remigration method based on the Kirchhoff integral theory with the basic theory and workflow of the Kirchhoff remigration. The calculation results on the gradient model and Marmousi model verify the effectiveness of this method.In ad-dition, numerical experiments show that integral method is faster than the differential method. 相似文献
9.
Internal waves play a crucial role in ocean mixing, and density perturbation and energy flux are essential quantities to investigate the generation and propagation of internal waves. This paper presents a methodology for calculating density perturbation and energy flux of internal waves only using a velocity field that is based on linearized equations for internal waves. The method was tested by numerical simulations of internal waves generated by tidal flowing over a Gaussian topography in a stratified fluid. The density perturbations and energy fluxes determined using our method that only used velocity data agreed with density perturbations and energy fluxes determined by the equation of state based on temperature data. The mean relative error (MRE) and root mean square error (RMSE) between the two methods were lower than 5% and 10% respectively. In addition, an experiment was performed to exam our method using the velocity field measured by Particle Image Velocimetry (PIV), and the setup of the experiment is consistent with the numerical model. The results of the experiments calculated by the methods using PIV data were also generally equal to those of the numerical model. 相似文献
10.
Kirchhoff beam migration is a beam migration method, which focuses on rapid imaging of geological structures. Although this imaging method ignores the amplitude information in the calculation process, it can calculate multi-arrival traveltime. This migration method takes into account both imaging accuracy and computational efficiency. Kirchhoff beam migration employs coarse grid techniques in several key steps such as traveltime calculation, weight function calculation, and imaging calculation. The selection of the coarse mesh size has an important influence on the computational efficiency and imaging accuracy of the migration imaging method. This paper will analyze this influence and illustrate the analysis results by the Marmousi data sets. 相似文献
11.
地震时间剖面可以对地质目标进行精细刻画,但由于变质岩、侵入岩地区存在地质体不规则、地质界线间波阻抗差异不明显、断裂构造倾角高陡等特征,导致地震原始资料具有波场复杂、干扰波发育、资料信噪比低等特点。为获得客观反应实际地质情况的沂沭断裂带深反射地震剖面,通过对研究区原始地震资料细致分析,针对各种干扰波的不同特性特征,分别采取针对性压制措施,进行组合去噪,在压制干扰的同时最大限度保护了有效信号。本次地震资料处理以高保真和高信噪比为目标,通过边处理边解释不断优化处理流程和处理参数。在处理过程中对静校正、叠前去噪、速度场建立以及波场空间归位等关键工作进行了重点研究,最终获得了高品质地震叠加和偏移时间剖面。反射剖面首次揭示了沂沭断裂带及其两侧岩石圈精细结构,为研究沂沭断裂带深部结构及对资源、环境的影响提供了可靠的地震学依据。 相似文献
12.
针对单一预测模型的不足,提出EEMD分解与粒子群灰色支持向量机（particle swarm optimization grey support vector machine,PSOGSVM）相结合的基坑位移预测模型。以基坑时间序列的混沌性为基础,利用EEMD分解时间序列,采用相空间重构技术构造样本,应用PSOGSVM模型进行基坑预测,并与GM(1,1)、SVM、遗传小波神经网络进行对比。结果表明,该算法预测精度好,具有良好的稳定性,可有效地应用于基坑位移预测。 相似文献
13.
犯罪时空预测作为预测警务的核心支撑技术,自2000年左右至今得到了快速的发展。本文介绍了犯罪时空预测的实践背景和理论基础,将犯罪时空预测解构为利用历史案件的时空位置、时空环境和个体行为等要素,结合相应的算法模型预测未来案件时空分布的过程。然后,从输入要素的视角对当前的犯罪时空预测方法进行了总结和归纳,将其划分为基于案件时空位置信息的犯罪时空预测、基于时空环境要素的犯罪时空预测,以及融合行为轨迹和时空环境要素的犯罪时空预测3种类型,详细总结了不同类型犯罪时空预测的方法原理,并从适应场景和预测效果等方面对不同的方法模型进行了比较。最后,结合当前的大数据技术发展趋势,对未来的犯罪时空预测进行了展望。本文认为犯罪时空预测未来需要从数据角度重点解决输入数据的体系融合、粒度细化和新型数据融合等问题,从模型优化角度应着重提高多源异构数据融合能力,平衡模型的可解释性与预测效果。 相似文献
14.
针对GPS可降水量时间序列具有非线性、非平稳性的特征，研究一种基于小波分解（WD）、遗传算法（GA）和最小二乘支持向量机（LSSVM）的GPS可降水量短临预报方法。先采用小波分解将GPS可降水量时间序列分解成便于预报的低频分量和高频分量；然后利用遗传算法优化LSSVM参数，进而对各分量建立预报模型；再将各分量预报结果进行叠加重构得到最终预报结果。选取两组数据进行实验，并将预报结果分别与LSSVM和遗传小波神经网络（GA-WNN）预报结果进行对比。结果表明，该组合模型具有良好的泛化能力，可有效解决神经网络易陷于局部极小的问题，提高了全局预报精度。 相似文献
15.
线性Radon变换噪音压制法及其在古龙断陷中的应用 总被引：1，自引：1，他引：0
针对松辽盆地北部古龙断陷地震资料信噪比低、线性干扰强特点,提出应用线性Radon变换进行叠前线性噪音压制的预处理方法,Radon变换可在炮集和CMP道集上进行运算,算法简单,易于编程实现,其积分路径的特点适合线性噪音压制.模拟数据和实际地震资料应用结果表明,线性Radon变换法能够实现保幅的线性噪音压制,是叠前提高地震资料信噪比的实用方法,在地震资料预处理中具有应用前景. 相似文献
16.
Prestack elastic reverse time migration ( RTM) requires multicomponent seismic data .But for multi-component elastic Kirchhoff migration , there is a limitation that ray theory no longer applies if thegeology be-comes complicated .In this paper, the authors have created a new 2D migration context for isotropic , elastic RTM, which included decomposition of the elastic source and receiver wavefields into P and S wave vectors by decoupled elastodynamic extrapolation , which retained the same stress and particle velocity components as the input data .Then we appliedsource-normalized crosscorrelation imaging condition in elastic reverse time migra-tion to compensate the energy of deep strata .We found that the resulting images were nearly identical to the ve-locity model , and the resolution has been improved .Our method is a wavefielddecomposition based on vector , and we can alsoavoid the problem of polarity reversal of converted shear wave imaging .It proved the applicabili-ty of the method proposed in our paper . 相似文献
17.
跨海大桥系统受外界影响扰动,其变形伴有混沌现象发生。对桥梁变形监测数据实现了混沌识别,运用C-C法计算时间序列的延迟时间,用G-P方法求得最佳嵌入维数,通过求取的时间延迟和最佳嵌入维数对桥梁变形监测数据进行相空间重构,为混沌时间序列预测模型的建立奠定基础;基于RBF神经网络建立混沌时间序列预测模型,对实测数据进行桥梁变形水平位移预测,并与基于最大Lyapunov指数混沌时间序列预测结果以及实测数据进行对比分析。结果表明,基于RBF神经网络建立的混沌时间序列预测模型的预测结果比基于最大Lyapunov指数混沌时间序列预测模型的预测结果要好,且短期预测效果好。 相似文献
18.
Using a bottom simulating reflector(BSR) on a seismic profile to identify marine gas hydrate is a traditional seismic exploration method. However, owing to the abundance differences between the gas hydrate and free gas in different regions, the BSR may be unremarkable on the seismic profile and invisible in certain cases. With the improvement of exploration precision, difficulty arises in meeting the requirements of distinguishing the abundance differences in the gas hydrate based on BSR. Hence, we studied other sensitive attributes to ascertain the existence of gas hydrate and its abundance variations, eventually improving the success rate of drilling and productivity. In this paper, we analyzed the contradiction between the seismic profile data and drilling sampling data from the Blake Ridge. We extracted different attributes and performed multi-parameter constraint analysis based on the prestack elastic wave impedance inversion. Then, we compared the analysis results with the drilling sampling data. Eventually, we determined five sensitive attributes that can better indicate the existence of gas hydrate and its abundance variations. This method overcomes the limitations of recognizing the gas hydrate methods based on BSR or single inversion attribute. Moreover, the conclusions can notably improve the identification accuracy of marine gas hydrate and provide excellent reference significance for the recognition of marine gas hydrate. Notably, the different geological features of reservoirs feature different sensitivities to the prestacking attributes when using the prestack elastic inversion in different areas. 相似文献
19.
采用有限元方法模拟隧道地震波场,采用波场快照与时间记录相结合的方法,研究空洞对隧道地震波场传播的影响,并对含空洞模型的时间记录进行处理,得到数值模型的速度云图和反射层位图。经数据处理表明,采用TSPwin设定默认值处理得到的速度云图与模型设定的空洞位置比较一致,在提取反射层位图上,空洞反射层呈现条带状特征,需要结合速度云图来确定空洞位置,且P波预报的准确性相对较高。对TSP系统的抗噪性进行研究,表明其具有良好的抗噪性能。最后通过对工程实例的处理,验证了数值模拟所得的结论。 相似文献
20.
船舶行为特征挖掘与预测是水上智能交通系统的重要研究内容,也是交通运输工程领域的关键科学问题。为系统研究基于船舶自动识别系统（Automatic Identification System, AIS）数据的船舶行为特征挖掘与预测的研究现状与发展趋势,本文首先针对Web of Science(WOS)和中国知网（China National Knowledge Infrastructure, CNKI）收录的文献,用知识图谱分析软件VOSviewer对文献关键词进行处理,从文献计量学的角度生成高频关键词的聚类图谱和趋势演化。然后对基于AIS数据的水上交通要素挖掘、船舶行为聚类和船舶行为预测3个主题的研究内容、方法、存在问题进行了系统分析和展望,研究结果表明：① 在基于AIS的水上交通要素挖掘方面,主要集中在对AIS数据中表征船舶行为空间特征和交通流的时间特征单独挖掘分析,缺乏对AIS数据的时间、空间以及环境因素特征的关联挖掘,对于如何进行交通要素的关联融合挖掘研究还有待深入探索;② 在船舶行为聚类方面,研究主要是运用无监督聚类方法研究船舶航迹点和航迹段聚类,得到船舶航行行为模式的时空分布和船舶操纵意图辨识模型,然而融合多维特征的船舶轨迹的相似性计算方法、聚类参数的自适应选取以及船舶行为的语义特征建模有待进一步研究;③ 在船舶行为预测方面,主要集中在基于动力学方程、传统智能算法和深度循环神经网络的船舶行为预测研究,考虑船舶行为的随机性、多样性和耦合性的特点,运用混合神经网络模型以及神经网络与向量机、注意力机制相结合的模型实现多维的船舶航行行为特征的实时预测将是新的研究方向。最后提出了基于语义模型的船舶行为特征挖掘、基于深度卷积神经网络的船舶行为的预测和基于知识图谱的船舶行为特征挖掘和预测结果可视化等有待进一步研究的方向。 相似文献