Interpolation of near offset using surface-related multiples

In this research, we present a seismic trace interpolation method which uses seismic data with surface-related multiples. It is different from conventional seismic data interpolation using information transformation or extrapolation of adjacent channels for reconstruction of missing seismic data. In this method there are two steps, first, we construct pseudo-primaries by cross-correlation of surface multiple data to extract the missing near- offset information in multiples, which are not displayed in the acquired seismic record. Second, we correct the pseudo-primaries by applying a Least-squares Matching Filter （LMF） and RMS amplitude correction method in time and space sliding windows. Then the corrected pseudo-primaries can be used to fill the data gaps. The method is easy to implement, without the need to separate multiples and primaries. It extracts the seismic information contained by multiples for filling missing traces. The method is suitable for seismic data with surfacerelated multiples.

First-order multiples imaging aided by water bottom

Surface-related multiples frequently propagate into the subsurface and contain abundant information on small reflection angles.Compared with the conventional migration of primaries,migration of multiples offers complementary illumination and a higher vertical resolution.However,crosstalk artifacts caused by unrelated multiples during reverse time migration(RTM)using multiples severely degrade the reliability and interpretation of the final migration images.Therefore,we proposed RTM using first-order receiver-side water-bottom-related multiples for eliminating crosstalk artifacts and enhancing vertical resolution.We first backward propagate the first-order receiver-side water-bottom-related multiples using a water-layer model,followed by saving the upper boundary wavefield.Then we produce the source wavefield using a seismic wavelet and the receiver wavefield by back-extrapolating the saved boundary.Finally,the cross-correlation imaging condition is applied to generate the final image.This method transforms the receiver-side multiples into primaries,followed by the conventional migration processing procedures.Numerical examples using synthetic datasets demonstrate that our method significantly enhances the imaging quality by eliminating crosstalk artifacts and improving the resolution.

Suppression of internal multiples based on virtual events

In practical seismic exploration, internal multiples generated when the wave impedance of medium is strong, and seismic records are recorded. The method of virtual event repress internal multiples is to move scattered points from underground to the surface, similar to the method of the surface-related multiple elimination (SRME). The method of SRME belongs to the prediction-subtraction approaches to eliminate internal multiples, prediction method is based on building a brand new way of seismic wave propagation (virtual reflection and virtual event), so that it has forward and backward wave propagation, and through convolution with significant wave to predict the internal multiples. Due to required data needing field information of full-wave, the authors use Seislet transform interpolating the missing data to ensure the premise of internal multiples prediction. The test data show that the above method has achieved good results.

Quantifying Solid Solution Strengthening in Nickel-Based Superalloys via High-Throughput Experiment and Machine Learning

Solid solution strengthening(SSS)is one of the main contributions to the desired tensile properties of nickel-based superalloys for turbine blades and disks.The value of SSS can be calculated by using Fleischer’s and Labusch’s theories,while the model parameters are incorporated without fitting to experimental data of complex alloys.In thiswork,four diffusionmultiples consisting of multicomponent alloys and pure Niare prepared and characterized.The composition and microhardness of singleγphase regions in samples are used to quantify the SSS.Then,Fleischer’s and Labusch’s theories are examined based on high-throughput experiments,respectively.The fitted solid solution coefficients are obtained based on Labusch’s theory and experimental data,indicating higher accuracy.Furthermore,six machine learning algorithms are established,providing a more accurate prediction compared with traditional physical models and fitted physical models.The results show that the coupling of highthroughput experiments and machine learning has great potential in the field of performance prediction and alloy design.

用光纤光栅获得理想DWDM光源的设计方法

根据Hill等的理论 ,提出用含光纤Bragg光栅的萨尼亚克环、光纤马赫—曾德尔干涉仪和普通的半导体激光器组成理想DWDM光源的设计方案。整个组件仅用光纤熔接工艺即可完成 ,因此具有制作方法简单、成本低等特点。

ATM网的MMBP信元模型排队分析

设ATM复用器的信元输入为N个两状态的马尔可夫调制贝努利过程的叠合 ,复用器的信元传输率恒定不变 ,缓冲器容量有限 .应用矩阵分析法研究了模型在稳态下队长的概率分布及信元丢失概率 .

Unfolded protein response in myelin disorders

Activation of the unfolded protein response in response to endoplasmic reticulum stress preserves cell viability and function under stressful conditions.Nevertheless,persistent,unresolvable activation of the unfolded protein response can trigger apoptosis to eliminate stressed cells.Recent studies show that the unfolded protein response plays an important role in the pathogenesis of various disorders of myelin,including multiples sclerosis,Charcot-Marie-Tooth disease,Pelizaeus-Merzbacher disease,vanishing white matter disease,spinal cord injury,tuberous sclerosis complex,and hypoxia-induced perinatal white matter injury.In this review we summarize the current literature on the unfolded protein response and the evidence for its role in the pathogenesis of myelin disorders.

A predictive deconvolution method for non-white-noise refl ectivity

Conventional predictive deconvolution assumes that the reflection coefficients of the earth conform to an uncorrelated white noise sequence. The Wiener-Hopf (WH) equation is constructed to solve the filter and eliminate the correlated components of the seismic records, attenuate multiples, and improve seismic resolution. However, in practice, the primary refl ectivity series of fi eld data rarely satisfy the white noise sequence assumption, with the result that the correlated components of the primary reflectivity series are also eliminated by traditional deconvolution. This results in signal distortion. To solve this problem, we have proposed an improved method for deconvolution. First, we estimated the wavelet correlation from seismic records using the spectrum-modeling method. Second, this wavelet autocorrelation was used to construct a new autocorrelation function which contains the correlated components caused by the existence of multiples and avoids the correlated components of the primary reflectivity series. Finally, the new autocorrelation function was brought into the WH equation, and the predictive fi lter operator was calculated for deconvolution. In this paper, we have applied this new method to simulated and field data processing, and we have compared its performance with that of traditional predictive deconvolution. Our results show that the new method can adapt to non-white refl ectivity series without changing the statistical characteristics of the primary reflection coefficient series. Compared with traditional predictive deconvolution, the new method reduces processing noise and improves fidelity, all while maintaining the ability to attenuate multiples and enhance seismic resolution.

Multiple attenuation using λ-f domain high-order and high-resolution Radon transform based on SL0 norm

Radon transform is to use the speed difference between primary wave and multiple wave to focus the difference on different"points"or"lines"in Radon domain,so as to suppress multiple wave.However,the limited migration aperture,discrete sampling,and AVO characteristics of seismic data all will weaken the focusing characteristics of Radon transform.In addition,the traditional Radon transform does not take into account the AVO characteristics of seismic data,and uses L1 Norm,the approximate form of L0 Norm,to improve the focusing characteristics of Radon domain,which requires a lot of computation.In this paper,we combine orthogonal polynomials with the parabolic Radon transform(PRT)and find that the AVO characteristics of seismic data can be fitted with orthogonal polynomial coefficients.This allows the problem to be transformed into the frequency domain by Fourier transform and introduces a new variable,lambda,combining frequency and curvature.Through overall sampling of lambda,the PRT operator only needs to be calculated once for each frequency,yielding higher computational efficiency.The sparse solution of PRT under the constraints of the smoothed L0 Norm(SL0)obtained by the steepest descent method and the gradient projection principle.Synthetic and real examples are given to demonstrate that the proposed method has This method has advantages in improving the Radon focusing characteristics than does the PRT based on L1 norm.

Multiple wave prediction and suppression based on LO-norm sparsity constraint

Multiple wave is one of the important factors affecting the signal-to-noise ratio of marine seismic data.The model-driven-method(MDM)can effectively predict and suppress water-related multiple waves,while the quality of the multiple wave contribution gathers(MCG)can affect the prediction accuracy of multiple waves.Based on the compressed sensing framework,this study used the sparse constraint under LO norm to optimize MCG,which can not only reduce the false in the prediction and improve the image accuracy,but also saves computing time.At the same time,the MDM-type method for multiple wave suppression can be improved.The unified prediction of multiple types of water-related multiple waves weakens the dependence of conventional MDM on the adaptive subtraction process in suppressing water-related multiple waves,improves the stability of the method,and simultaneously,reduces the computational load.Finally,both theoretical model and practical data prove the effectiveness of the present method.

A generic procedure for determining atomic LS spectral terms and their LS eigenfunctions

This paper develops a Fortran code which is capable to construct the simplest LS eigenfunctions for desired symmetry and determine all permitted atomic LS spectral terms under a given orbital occupancy by implementing and extending the Schaefer and Harris method. Examples （in some cases the most complete set to date） of multiple spectroscopic terms of LS coupling of atomic states for both non-equivalent and equivalent electronic configurations are given. It also corrects a few observed errors from the recent literature.

300脚MSA 10Gbit/sTransponder模块

分析了开发 1 0 Gbit/s Transponder模块的必然性 ,介绍了 1 0 Gbit/s Transponder模块的原理、特点和参数指标 .并且用开发出的两只 40 km30 0脚 1 0 Gbit/s Transponder模块成功地进行了 43km的无误码传输试验和测试 .

Effects of Financial Market Variables on Stock Prices:A Review of the Literature

Stock market plays a pivotal role in firms’expansion and turns economic growth.In the literature,because of the importance of stock markets to the real economy,the smooth and risk-free operation of the stock market has attracted significant attention.The finance literature contains a large number of studies that examine the stock price behaviour with some emphasis on the determinants of the relationship between the equity prices and the financial market activities.The present study reviews the previous works of the effect of financial market variables and stock price.Five selected financial market variables,market capitalization,earnings per share,price earnings multiples,dividend yield,and trading volume are reviewed in this study.In the past literature,there are the opinions of the positive significant relationship between market capitalization and stock price.To find the relationship between dividend yield and stock price,there are two broad schools of thoughts.Both of the relevance and irrelevance theory of Gordon and Modigliani have the strong evidence in the current literature that keeps on the dilemma and provides the scopes for future research.Price-earnings multiples are analyzed in the past literature by using different variables.Based on that,it is evidenced that price-earnings multiples have a negative significant effect on stock price.The reviewed studies state the cointegrating relationship between the stock price and the trading volume as the trading volume is a source of risk.

针对MR-OFDM波形的降峰均比机制研究

针对IEEE 802.15.4g标准的多速率多区域正交频分复用(MR-OFDM)波形,提出了一种通过对加扰种子优化选择来降低发送信号峰均比(PAPR)的机制。其充分利用了发送信号的帧格式,在业务负荷信号的产生过程中引入加扰种子的优化选择机制,从而改善了发射信号的PAPR性能。和传统降PAPR算法相比,新算法无需对标准内容进行任何变动,在发送端仅需少量修改现有信号处理流程,而在接收端则无需任何修改,从而实现对大量已部署产品的通信兼容。理论分析和仿真结果表明,优化算法不影响传输速率,且计算复杂度低,不同参数OFDM信号的互补累积分布函数在10^(-4)数值处减少了约2~2.6 dB,取得了较好的降峰均比值性能。另外,相关机制经过适当修改后可以应用于其他同类型的物联网OFDM通信标准中。

Migration of multiples from the South China Sea

The South China Sea where water depth is up to 5000 m is the most promising oil and gas exploration area in China in the future.The seismic data acquired in the South China Sea contain various types of multiples that need to be removed before imaging can be developed.However,compared with the conventional reflection migration,multiples carry more information of the underground structure that helps provide better subsurface imaging.This paper presents a method to modify the conventional reverse time migration so that multiple reflections can migrate to their correct locations in the subsurface.This approach replaces the numerical impulsive source with the recorded data including primaries and multiples on the surface,and replaces the recorded primary reflection data with multiples.In the reverse time migration process,multiples recorded on the surface are extrapolated backward in time to each depth level,while primaries and multiples recorded on the surface are extrapolated forward in time to the same depth levels.By matching the difference between the primary and multiple images using an objective function,this algorithm improves the primary resultant image.Synthetic tests on Sigsbee2 B show that the proposed method can obtain a greater range and better underground illumination.Images of deep water in the South China Sea are obtained using multiples and their matching with primaries.They demonstrate that multiples can make up for the reflection illumination and the migration of multiples is an important research direction in the future.

Acquisition Discount and Valuation Effect of Private M＆As in China

An acquisition discount can reflect not only the liquidity demands for unlisted targets but also the strategic requirements, management efficiencies and capital allocations for the listed bidders.Based on Officer(2007), the authors choose an acquisition approach to generate an acquisition discount for unlisted targets. In China, unlisted firms are sold at a deeper discount than listed firms. The deeper discount mainly depends on the liquidity demand and the characteristics of the bilateral trading components. Larger bidders tend to pay more, whereas smaller targets are sold at lower discounts. The values of unlisted targets in the TMT industry are underestimated. Furthermore, buying out unlisted targets can significantly increase the abnormal return of public bidders during the announcement period.Deeper discounts or stock payments have a positive effect on the stock values of the bidders, whereas this positive increase will be weakened if the bidder is large or has a previous ownership relationship.