基于小波变换的机器人腕力传感器滤波算法

在对机器人腕力传感器信号特点分析基础上,提出了应用小波变换对腕力传感器信号进行滤波的方法,讨论了小波滤波算法,研究了机器人腕力传感器信号滤波方案,并针对抛光机器人作业实验数据进行滤波。仿真实验表明方法有效。

小波变换理论应用进展

本文介绍了小波变换理论 ,讨论了基本小波函数的选取准则和小波变换算法 ,分析了小波变换与人工智能等其它方法的结合方式和特点 .通过介绍小波变换在信号瞬态分析、图像边沿检测、图像去噪、模式识别、数据压缩、分形信号分析等方面的应用实例 ,讨论了小波变换在处理非平稳信号和复杂图像时的优势 .最后 ,对小波变换理论的发展及其应用前景作了描述 .

基于多特征模糊聚类的图像融合方法

首先利用模糊C-均值聚类算法在多特征形成的特征空间上对图像进行区域分割,并在此基础上对区域进行多尺度小波分解;然后利用柯西函数构造区域的模糊相似度,应用模糊相似度及区域信息量构造加权因子,从而得到融合图像的小波系数;最后利用小波逆变换得到融合图像·采用均方根误差、峰值信噪比、熵、交叉熵和互信息5种准则评价融合算法的性能·实验结果表明,文中方法具有良好的融合特性·

基于小波与小波包的变速器故障特征提取

本文结合自适应小波变换滤波去噪方法与小波阈值去噪方法,提出了一种可用于变速器故障振动信号去噪的双层滤波去噪算法。该算法的滤波过程分为两层,第一层滤波采用自适应小波变换滤波算法;第二层滤波采用经典的小波阈值去噪算法对信号进行二次去噪。最后,将去噪后的故障信号采用小波包进行了分解,并提取了小波包频带能量作为故障特征向量。

基于神经网络和小波变换的车型识别方法研究

车型自动识别分类在不停车收费系统中起着关键的作用，决定了不停车收费系统的可靠性和智能化程度，对提高公路交通系统的管理水平和车辆通行速度具有重要的意义。 本文对现有车型自动识别分类方法进行了分析比较，在此基础上，对采用雷达微波进行车型识别进行了探索和研究，雷达微波车型识别技术与车载电子标签有机结合起来，起到车型二次识别的作用，有效防止各种舞弊行为，控制收费损失。 本文通过MATLAB产生仿真的雷达微波信号，信号中包含了车型的特征信息。再采用小波变换的方法消除噪声，由于车型大小与信号经过小波变换后得到的各层能量分布有关，所以提取其能量分布作为分类识别的特征矢量。设计了BP神经网络的分类器，车型的能量分布特征由车型分类器进行分类，最终得到车辆的类型。 本文在对所设计的神经网络分类器进行训练的时候，对样本采用了改进的模糊C均值算法进行聚类分析，有效地避免了样本集不理想情况下对各类中心隶属度过小的情况，用隶属度作为网络输出训练,使网络容错性更强，更加符合实际分类情况，三个网络分别训练，最后综合判断，提高了分类质量。 本文首先介绍了已有车型自动识别的方法，分析讨论了存在的弊端，然后提出采用雷达微波进行识别的方法，详细介绍了对回波信号进行处理所用到的算法，分析比较各种算法，选择合适的算法用于信号的处理，最后介绍了车型识别硬件仿真平台及软件实现。

裂缝性油气藏储层预测方法研究

In this paper, based on the E & P situation in the oilfield and the theory of geophysical exploration, a series researches are conducted on fracture reservoir prediction technology in general，and it especially focus on some difficult points. The technological series which integrated amplitude preserved data processing、interpretation and its comprehensive application research as a whole were developed and this new method can be applied to the other similar oilfield exploration and development. The contents and results in this paper are listed as follows: 1. An overview was given on the status and development of fracture reservoir estimation technique, compare and analyze those geophysical prediction methods. This will be very helpful to the similar reservoir researches. 2. Analyze and conclude the characters of geologies and well logging response of burial hills fracture reservoir, those conclusions are used to steer the geophysical research and get satisfying results. 3. Forward modeling anisotropy seismic response of fracture reservoir. Quantitatively describe the azimuthal amplitude variation. Amplitude ellipse at each incidence angle is used to identify the fracture orientation. 4. Numerical simulation of structure stress based on finite difference method is carried out. Quantitatively describe and analyze the direction and intensity of fracture. 5. Conventional attributes extraction of amplitude preserved seismic data、attributes with different azimuthal angle and different offset are used to determine the relationship between the results and fracture distribution. 6. With spectrum decomposition method based on wavelet transform， the author disclose the reservoir distribution in space. It is a powerful tool to display its anisotropy. 7. Integrated seismic wave impendence、elastic impendence、spectrum decomposition、attribute extraction、fracture analysis result as a whole to identify and evaluate the fracture reservoir. An optimum workflow is constructed. It is used to practical oil&gas production and good results are obtained. This can indicate the wide foreground of this technique series.

多尺度分解与相位反褶积提高海上地震资料分辨率和信噪比

Offshore seismic exploration is full of high investment and risk. And there are many problems, such as multiple. The technology of high resolution and high S/N ratio on marine seismic data processing is becoming an important project. In this paper, the technology of multi-scale decomposition on both prestack and poststack seismic data based on wavelet and Hilbert-Huang transform and the theory of phase deconvolution is proposed by analysis of marine seismic exploration, investigation and study of literatures, and integration of current mainstream and emerging technology. Related algorithms are studied. The Pyramid algorithm of decomposition and reconstruction had been given by the Mallat algorithm of discrete wavelet transform In this paper, it is introduced into seismic data processing, the validity is shown by test with field data. The main idea of Hilbert-Huang transform is the empirical mode decomposition with which any complicated data set can be decomposed into a finite and often small number of intrinsic mode functions that admit well-behaved Hilbert transform. After the decomposition, a analytical signal is constructed by Hilbert transform, from which the instantaneous frequency and amplitude can be obtained. And then, Hilbert spectrum. This decomposition method is adaptive and highly efficient. Since the decomposition is based on the local characteristics of the time scale of data, it is applicable to nonlinear and non-stationary processes. The phenomenons of fitting overshoot and undershoot and end swings are analyzed in Hilbert-Huang transform. And these phenomenons are eliminated by effective method which is studied in the paper. The technology of multi-scale decomposition on both prestack and poststack seismic data can realize the amplitude preserved processing, enhance the seismic data resolution greatly, and overcome the problem that different frequency components can not restore amplitude properly uniformly in the conventional method. The method of phase deconvolution, which has overcome the minimum phase limitation in traditional deconvolution, approached the base fact well that the seismic wavelet is phase mixed in practical application. And a more reliable result will be given by this method. In the applied research, the high resolution relative amplitude preserved processing result has been obtained by careful analysis and research with the application of the methods mentioned above in seismic data processing in four different target areas of China Sea. Finally, a set of processing flow and method system was formed in the paper, which has been carried on in the application in the actual production process and has made the good progress and the huge economic benefit.

残留盆地分布综合地球物理研究——以大港地区为例

Macro-distribution of residual basins is a basic question in residual basin research，the main object of macro-distribution study is to build strata framework, compute thickness of residual strata and analyze characteristics of residual basins. With the guidance of the theory of integrated geology and geophysical research, the paper assembled series of methods and established the technical chart based on gravity and magnetic data, with restriction of geology, seismic and drilling data. Based on potential field data processing and analysis, forward and inverse computation, region potential field analysis and potential field separation, etc. it computed depth of gravity/magnetic basement and got strata framework. It had got effective results in the research of macro-distribution of residual basin research in the Dagang area. It did the wavelet transform of gravity/magnetic data with multi-kind of wavelet basis using a trou algorithm. From comparison of processing result and their spectral of wavelet analysis, up continuation and filter method, the wavelet approximation is better to fit the regional potential field, and it is an effective method to separate gravity/magnetic effect caused by deep geology bodies. The experiment of matching pursuit shows that te transform domain methods have great advantage in potential data analysis. From the integrated geophysical study of rock property study, gravity/magnetic basement inversion and fault system analysis of the Dagang area, it gets the strata framework and the thickness of pre-Cenozoic residual strata. Comprehensive study with gravity and magnetotelluric profile inversion and interpretation, three prospect plays of macro-distribution of residual basins are fingered out. It has great residual strata thickness in the northern part of Chengning Uplift and there is thrust fault in the deep zone and good up-Paleozoic hydrocarbon source rocks in this area. With integrated analysis, this area will be the most prospective hydrocarbon location of pre-Cenozoic residual basins.

地球化学场的多重分形分析与分解

Geochemical and Geophysical anomaly play an important role in mineral exploration，their spatial structure character include singularity and self－similar。The singularity of an anomaly reflects the enrichment characters of the geochemical element ,The anomaly separation by multifractal model is useful in mineral anomaly assessment。In recent years, The continuous multifractal mode of the geochemical fields was studied ,it can be separated into the simple continuous multifractal mode and the high concentration multifractal mode, and the C－A、C－D、 S－A、MSDV、W－A method to decompose the anomaly were presented。Those are succeeded in interpretation of Geochemical and Geophysical anomaly。 This study makes a summarization to these method， we present a multifractal method based on wavelet transform to analyze the multifractal fields 。The singularity and spectrum are calculated through tracing the wavelet maximum modulus in different measure，and then the fields can be decomposed by the characters of the singularity。 It is demonstrated to be useful in interpretation of Au anomaly in Gekou－Shicheng region Rushang Shandong Province 。 Based on the multifractal theory , Using the concentration—area（C—A）method ,We study two geochemical fields in Chifeng area , Inner Mongolia。The results show that the geochemical fields have three different multifractal modes。Based on these ,we discuss the enrichment mode of the geochemical elements and their distributions in space and get the anomaly lower limit ,then the geochemical backgrounds、regional anomalies and local anomalies are distinguished

奇异性分析方法及其在储层预测中的应用研究

In research field of oil geophysical prospecting, reservoir prediction is refers to forecasting physical properties of petroleum reservoir by using data of seismic and well logging, it is a research which can guide oil field development. Singularities of seismic and logging data are caused by the heterogeneity of reservoir physical property. It's one of important methods that using singularity characteristics of seismic and logging data to study the reservoir physical property in recently. Among them, realization of reservoir quantitative prediction by analyzing singularity of the data and enhancing transition description of data is difficulty in method research. Based on wavelet transform and the fractal theory, the paper studied the singularity judgment criterion for seismic and logging data, not only analyzed quantitative relation between singularity data and reservoir physical property, but also applied it in practical reservoir prediction. The main achievements are: 1. A new method which provides singular points and their strength information estimation at only one single scale is proposed by Herrmann (1999). Based on that, the dissertation proposed modified algorithm which realized singularity polarity detection. 2. The dissertation introduced onset function to generalize the traditional geologic boundaries variations model which used singularity characteristics to represent the abruptness of the lithologic velocity transition. We show that singularity analysis reveals generic singularity information conducted from velocity or acoustic impedance to seismogram based on the convolution seismic-model theory. Theory and applications indicated that singularity information calculated from seismic data was a natural attribute for delineating stratigraphy boundaries due to its excellent ability in detecting detailed geologic features. We demonstrated that singularity analysis was a powerful tool to delineate stratigraphy boundaries and inverse acoustic impedance and velocity. 3. The geologic significances of logging data singularity information were also presented. According to our analysis, the positions of singularities indicate the sequence stratigraphic boundary, and there is subtle relationship between the singularity strength and sedimentary environment, meanwhile the singularity polarity used to recognize stratigraphic base-level cycle. Based on all those above, a new method which provided sedimentary cycle analysis based on the singularity information of logging data in multiple scales was proposed in this dissertation. This method provided a quantitative tool for judging interface of stratum sequence and achieved good results in the actual application.

叠前地震多角度三参数同步反演方法

Pre-stack seismic inversion has become the emphasis and hotspot owing to the exploration & exploitation of oil field and the development of seismic technology. Pre-stack seismic inversion has the strongpoint of making the most of amplitude versus offset compared with the post-stack method. In this dissertation, the three parameters were discussed from multi-angle reflectance of P-wave data based on Zoeppritz’s and Aki & Richard’s equation, include P-wave velocity, S-wave velocity, and density. The three parameters are inversed synchronously from the pre-stack multi-angle P-wave data, based on rockphysics model and aimed at the least remnant difference between model simulation and practical data. In order to improve the stability of inversion and resolution to thin bed, several techniques were employed, such as the wavelet transform with multi-scale function, adding the Bayesian soft constraint and hard constraints (the horizon, structure and so on) to the inversion process. Being the result, the uncertainty of the resolution is reduced, the reliability and precision are improved, the significance of parameters becomes clearer. Meeting to the fundamental requirement of pre-stack inversion, some research in rockphysics are carried out which covered the simulation and inversion of S-wave velocity, the influence of pore fluids to geophysical parameters, and the slecting and analyzing of sensitive parameters. The difference between elastic wave equation modeling and Zoeppritz equation method is also compared. A series of key techniques of pre-stack seismic inversion and description were developed, such as attributes optimization, fluid factors, etc. All the techniques mentioned above are assembled to form a technique sets and process of synchronous pre-stack seismic inversion method of the three parameters based on rock physics and model simulation. The new method and technology were applied in many areas with various reservoirs, obtained both geological and economic significance, which proved to be valid and rational. This study will promote the pre-stack inversion technology and it’s application in hidden reservoirs exploration, face good prospects for development and application.

HHT在电磁信号处理中的应用

In modem signal Processing，non－linear，non－Gaussian and non－stable signals are usually the analyzed and Processed objects，especially non－stable signals. The convention always to analyze and Process non－stable signals are： short time Fourier transform，Wigner－Ville distribution，wavelet Transform and so on. But the above three algorithms are all based on Fourier Transform，so they all have the shortcoming of Fourier Analysis and cannot get rid of the localization of it. Hilbert－Huang Transform is a new non－stable signal processing technology，proposed by N. E. Huang in 1998. It is composed of Empirical Mode Decomposition (referred to as EMD) and Hilbert Spectral Analysis (referred to as HSA). After EMD Processing，any non－stable signal will be decomposed to a series of data sequences with different scales. Each sequence is called an Intrinsic Mode Function (referred to as IMF). And then the energy distribution plots of the original non－stable signal can be found by summing all the Hilbert spectrums of each IMF. In essence，this algorithm makes the non－stable signals become stable and decomposes the fluctuations and tendencies of different scales by degrees and at last describes the frequency components with instantaneous frequency and energy instead of the total frequency and energy in Fourier Spectral Analysis. In this case，the shortcoming of using many fake harmonic waves to describe non－linear and non－stable signals in Fourier Transform can be avoided. This Paper researches in the following parts： Firstly，This paper introduce the history and development of HHT，subsequently the characters and main issues of HHT. This paper briefly introduced the basic realization principles and algorithms of Hilbert－Huang transformation and confirms its validity by simulations. Secondly, This paper discuss on some shortcoming of HHT. By using FFT interpolation, we solve the problem of IMF instability and instantaneous frequency undulate which are caused by the insufficiency of sampling rate. As to the bound effect caused by the limitation of envelop algorithm of HHT, we use the wave characteristic matching method, and have good result. Thirdly, This paper do some deeply research on the application of HHT in electromagnetism signals processing. Based on the analysis of actual data examples, we discussed its application in electromagnetism signals processing and noise suppression. Using empirical mode decomposition method and multi-scale filter characteristics can effectively analyze the noise distribution of electromagnetism signal and suppress interference processing and information interpretability. It has been founded that selecting electromagnetism signal sessions using Hilbert time-frequency energy spectrum is helpful to improve signal quality and enhance the quality of data.

小波域地震资料的处理方法（WSSP）研究

The modeling formula based on seismic wavelet can well simulate zero - phase wavelet and hybrid-phase wavelet, and approximate maximal - phase and minimal - phase wavelet in a certain sense. The modeling wavelet can be used as wavelet function after suitable modification item added to meet some conditions. On the basis of the modified Morlet wavelet, the derivative wavelet function has been derived. As a basic wavelet, it can be sued for high resolution frequency - division processing and instantaneous feature extraction, in acoordance with the signal expanding characters in time and scale domains by each wavelet structured. Finally, an application example proves the effectiveness and reasonability of the method. Based on the analysis of SVD (Singular Value Decomposition) filter, by taking wavelet as basic wavelet and combining SVD filter and wavelet transform, a new de - noising method, which is Based on multi - dimension and multi-space de - noising method, is proposed. The implementation of this method is discussed the detail. Theoretical analysis and modeling show that the method has strong capacity of de - noising and keeping attributes of effective wave. It is a good tool for de - noising when the S/N ratio is poor. To give prominence to high frequency information of reflection event of important layer and to take account of other frequency information under processing seismic data, it is difficult for deconvolution filter to realize this goal. A filter from Fourier Transform has some problems for realizing the goal. In this paper, a new method is put forward, that is a method of processing seismic data in frequency division from wavelet transform and reconstruction. In ordinary seismic processing methods for resolution improvement, deconvolution operator has poor part characteristics, thus influencing the operator frequency. In wavelet transform, wavelet function has very good part characteristics. Frequency - division data processing in wavelet transform also brings quite good high resolution data, but it needs more time than deconvolution method does. On the basis of frequency - division processing method in wavelet domain, a new technique is put forward, which involves 1) designing filter operators equivalent to deconvolution operator in time and frequency domains in wavelet transform, 2) obtaining derivative wavelet function that is suitable to high - resolution seismic data processing, and 3) processing high resolution seismic data by deconvolution method in time domain. In the method of producing some instantaneous characteristic signals by using Hilbert transform, Hilbert transform is very sensitive to high - frequency random noise. As a result, even though there exist weak high - frequency noises in seismic signals, the obtained instantaneous characteristics of seismic signals may be still submerged by the noises. One method for having instantaneous characteristics of seismic signals in wavelet domain is put forward, which obtains directly the instantaneous characteristics of seismic signals by taking the characteristics of both the real part (real signals, namely seismic signals) and the imaginary part (the Hilbert transfom of real signals) of wavelet transform. The method has the functions of frequency division and noise removal. What is more, the weak wave whose frequency is lower than that of high - frequency random noise is retained in the obtained instantaneous characteristics of seismic signals, and the weak wave may be seen in instantaneous characteristic sections (such as instantaneous frequency, instantaneous phase and instantaneous amplitude). Impedance inversion is one of tools in the description of oil reservoir. one of methods in impedance inversion is Generalized Linear Inversion. This method has higher precision of inversion. But, this method is sensitive to noise of seismic data, so that error results are got. The description of oil reservoir in researching important geological layer, in order to give prominence to geological characteristics of the important layer, not only high frequency impedance to research thin sand layer, but other frequency impedance are needed. It is difficult for some impedance inversion method to realize the goal. Wavelet transform is very good in denoising and processing in frequency division. Therefore, in the paper, a method of impedance inversion is put forward based on wavelet transform, that is impedance inversion in frequency division from wavelet transform and reconstruction. in this paper, based on wavelet transform, methods of time - frequency analysis is given. Fanally, methods above are in application on real oil field - Sansan oil field.

岩性油藏储层预测的地震理论与方法研究

At present the main object of the exploration and development (E&D) of oil and gas is not the structural oil-gas pools but the subtle lithological oil-gas reservoir. Since the last 90's, the ratio of this kind of pools in newly-added oil reserves is becoming larger and larger, so is the ratio in the eastern oilfields. The third oil-gas resource evaluation indicates the main exploration object of Jiyang depression is the lithological oil-gas pools in future. However, lack of effective methods that are applied to search for this kind of pool makes E&D difficult and the cost high. In view of the urgent demand of E&D, in this paper we deeply study and analyze the theory and application in which the seismic attributes are used to predict and describe lithological oil-gas reservoirs. The great results are obtained by making full use of abundant physics and reservoir information as well as the remarkable lateral continuity involved in seismic data in combination with well logging, drilling-well and geology. ①Based on a great deal of research and different geological features of Shengli oilfield, the great progresses are made some theories and methods of seismic reservoir prediction and description. Three kinds of extrapolation near well seismic wavelet methods-inverse distance interpolation, phase interpolation and pseudo well reflectivity-are improved; particularly, in sparse well area the method of getting pseudo well reflectivity is given by the application of the wavelet theory. The formulae for seismic attributes and coherent volumes are derived theoretically, and the optimal method of seismic attributes and improved algorithms of picking up coherent data volumes are put forward. The method of making sequence analysis on seismic data is put forward and derived in which the wavelet transform is used to analyze not only qualitatively but also quantitatively seismic characteristics of reservoirs.② According to geologic model and seismic forward simulation, from macro to micro, the method of pre- and post-stack data synthetic analysis and application is put forward using seismic in close combination with geology; particularly, based on making full use of post-stack seismic data, "green food"-pre-stack seismic data is as possible as utilized. ③ In this paper, the formative law and distributing characteristic of lithologic oil-gas pools of the Tertiary in Jiyang depression, the knowledge of geological geophysics and the feasibility of all sorts of seismic methods, and the applied knowledge of seismic data and the geophysical mechanism of oil-gas reservoirs are studied. Therefore a series of perfect seismic technique and software are completed that fit to E&D of different categories of lithologic oil-gas reservoirs. ④ This achievement is different from other new seismic methods that are put forward in the recent years, that is multi-wave multi-component seismic, cross hole seismic, vertical seismic, and time-lapse seismic etc. that need the reacquisition of seismic data to predict and describe the oil-gas reservoir. The method in this paper is based on the conventional 2D/3D seismic data, so the cost falls sharply. ⑤ In recent years this technique that predict and describe lithologic oil-gas reservoirs by seismic information has been applied in E&D of lithologic oil-gas reservoirs on glutenite fans in abrupt slop and turbidite fans in front of abrup slop, slump turbidite fans in front of delta, turbidite fans with channel in low slope and channel sanbody, and a encouraging geologic result has been gained. This achievement indicates that the application of seismic information is one of the most effective ways in solving the present problem of E&D. This technique is significant in the application and popularization, and positive on increasing reserves and raising production as well as stable development in Shengli oilfield. And it will be directive to E&D of some similar reservoirs

基于信息重建技术的地震信号处理方法研究

The dissertation addressed the problems of signals reconstruction and data restoration in seismic data processing, which takes the representation methods of signal as the main clue, and take the seismic information reconstruction (signals separation and trace interpolation) as the core. On the natural bases signal representation, I present the ICA fundamentals, algorithms and its original applications to nature earth quake signals separation and survey seismic signals separation. On determinative bases signal representation, the paper proposed seismic dada reconstruction least square inversion regularization methods, sparseness constraints, pre-conditioned conjugate gradient methods, and their applications to seismic de-convolution, Radon transformation, et. al. The core contents are about de-alias uneven seismic data reconstruction algorithm and its application to seismic interpolation. Although the dissertation discussed two cases of signal representation, they can be integrated into one frame, because they both deal with the signals or information restoration, the former reconstructing original signals from mixed signals, the later reconstructing whole data from sparse or irregular data. The goal of them is same to provide pre-processing methods and post-processing method for seismic pre-stack depth migration. ICA can separate the original signals from mixed signals by them, or abstract the basic structure from analyzed data. I surveyed the fundamental, algorithms and applications of ICA. Compared with KL transformation, I proposed the independent components transformation concept (ICT). On basis of the ne-entropy measurement of independence, I implemented the FastICA and improved it by covariance matrix. By analyzing the characteristics of the seismic signals, I introduced ICA into seismic signal processing firstly in Geophysical community, and implemented the noise separation from seismic signal. Synthetic and real data examples show the usability of ICA to seismic signal processing and initial effects are achieved. The application of ICA to separation quake conversion wave from multiple in sedimentary area is made, which demonstrates good effects, so more reasonable interpretation of underground un-continuity is got. The results show the perspective of application of ICA to Geophysical signal processing. By virtue of the relationship between ICA and Blind Deconvolution , I surveyed the seismic blind deconvolution, and discussed the perspective of applying ICA to seismic blind deconvolution with two possible solutions. The relationship of PC A, ICA and wavelet transform is claimed. It is proved that reconstruction of wavelet prototype functions is Lie group representation. By the way, over-sampled wavelet transform is proposed to enhance the seismic data resolution, which is validated by numerical examples. The key of pre-stack depth migration is the regularization of pre-stack seismic data. As a main procedure, seismic interpolation and missing data reconstruction are necessary. Firstly, I review the seismic imaging methods in order to argue the critical effect of regularization. By review of the seismic interpolation algorithms, I acclaim that de-alias uneven data reconstruction is still a challenge. The fundamental of seismic reconstruction is discussed firstly. Then sparseness constraint on least square inversion and preconditioned conjugate gradient solver are studied and implemented. Choosing constraint item with Cauchy distribution, I programmed PCG algorithm and implement sparse seismic deconvolution, high resolution Radon Transformation by PCG, which is prepared for seismic data reconstruction. About seismic interpolation, dealias even data interpolation and uneven data reconstruction are very good respectively, however they can not be combined each other. In this paper, a novel Fourier transform based method and a algorithm have been proposed, which could reconstruct both uneven and alias seismic data. I formulated band-limited data reconstruction as minimum norm least squares inversion problem where an adaptive DFT-weighted norm regularization term is used. The inverse problem is solved by pre-conditional conjugate gradient method, which makes the solutions stable and convergent quickly. Based on the assumption that seismic data are consisted of finite linear events, from sampling theorem, alias events can be attenuated via LS weight predicted linearly from low frequency. Three application issues are discussed on even gap trace interpolation, uneven gap filling, high frequency trace reconstruction from low frequency data trace constrained by few high frequency traces. Both synthetic and real data numerical examples show the proposed method is valid, efficient and applicable. The research is valuable to seismic data regularization and cross well seismic. To meet 3D shot profile depth migration request for data, schemes must be taken to make the data even and fitting the velocity dataset. The methods of this paper are used to interpolate and extrapolate the shot gathers instead of simply embedding zero traces. So, the aperture of migration is enlarged and the migration effect is improved. The results show the effectiveness and the practicability.