Analog RRAM is considered as a promising emerging device technology for the future storage and neuromorphic computing. Different from long-term retention degradation, the usually overlooked relaxation effect shows more significant impact on computing applications, which is manifested in the low energy efficiency of data mapping and in the high accuracy loss of application functions. In this work, we have statistically studied the relaxation effect on analog RRAM arrays. The random conductance fluctuation behaviors due to relaxation effect is captured and quantified with a newly developed fast characterization platform. The intermediate conductance state (ICS) shows more severe relaxation than the high and low conductance states (HCS and LCS). A multi-filament-formation-and-rupture model is established to explain the underlying mechanism of relaxation effect and the reason for differences between different conductance states.

The invention relates to a slope multi-flow-direction overflow analysis method considering surface accumulated water depth change. The method comprises the steps of determining the surface accumulatedwater depth, determining the slope dynamic confluence path, determining the slope multi-flow-direction water quantity distribution weight and determining the slope multi-flow-direction overflow waterquantity. The method aims to solve the problem of small surface fluctuation in plain bumpy areas, large ponding area and fast change, achieves accurate depiction of dynamic change of the surface ponding depth and conversion of the water inflow and outflow relationship between the surface ponding depth and peripheral units, solves the problem of application distortion of a conventional digital elevation model, finely simulates the slope multi-flow-direction flooding process, and effectively improves simulation of the surface runoff production process of the plain low-lying area. The method isoriented to plain bumpy area hydrological simulation, and related results can provide basic support for plain bumpy area hydrological model construction and application.

在Kuster-Toks?z(KT)模型与差分等效介质理论(DEM)结合过程中,通过用孔隙包含物逐渐替换基质的方法获得孔隙介质的岩石弹性模量.现有方法每次替换的孔隙体积是常量,而基质体积不断减小,实际参与替换的包含物体积与孔隙包含物计算体积是不同的.本文通过改进每次替换的孔隙体积计算公式,使得替换体积随迭代次数的增加而逐渐减小,保持替换体积相对基质体积的比率不变,在迭代次数足够大的条件下使得该比率足够小,满足了K-T计算公式的要求,计算结果更接近理论值.测试结果显示:随着孔隙度的增大,岩石等效弹性模量逐渐收敛于孔隙包含物的弹性模量,说明本方法与物理规律一致;与现有的KT迭代方法相比,采用本方法的计算结果与Xu-White模型更接近,本方法提出孔隙包含物的实际体积与计算体积的计算式更符合KT模型孔隙切分过程.

The research on Massive Open Online Course (MOOC) has mushroomed worldwide due to the technical revolution and its unprecedented enrollments. Existing work mainly focuses on performance prediction, content recommendation, and learning behavior summarization. However, finding anomalous learning activities in MOOC data has posed special challenges and requires providing a clear definition of anomalous behavior, analyzing the multifaceted learning sequence data, and interpreting anomalies at different scales. In this paper, we present a novel visual analytics system, MOOCad, for exploring anomalous learning patterns and their clustering in MOOC data. The system integrates an anomaly detection algorithm to cluster learning sequences of MOOC learners into staged-based groups. Moreover, it allows interactive anomaly detection between and within groups on the basis of semantic and interpretable group-wise data summaries. We demonstrate the effectiveness of MOOCad via an in-depth interview with a MOOC lecturer with real-world course data.

The results of anomaly detection are sensitive to the choice of detection algorithms as they are specialized for different properties of data, especially for multidimensional data. Thus, it is vital to select the algorithm appropriately. To systematically select the algorithms, ensemble analysis techniques have been developed to support the assembly and comparison of heterogeneous algorithms. However, challenges remain due to the absence of the ground truth, interpretation, or evaluation of these anomaly detectors. In this paper, we present a visual analytics system named EnsembleLens that evaluates anomaly detection algorithms based on the ensemble analysis process. The system visualizes the ensemble processes and results by a set of novel visual designs and multiple coordinated contextual views to meet the requirements of correlation analysis, assessment and reasoning of anomaly detection algorithms. We also introduce an interactive analysis workflow that dynamically produces contextualized and interpretable data summaries that allow further refinements of exploration results based on user feedback. We demonstrate the effectiveness of EnsembleLens through a quantitative evaluation, three case studies with real-world data and interviews with two domain experts.

It is important to generate both interesting and representative video summary for massive videos. This work proposes a new method to generate dynamic video summary using multiple features and image quality without human's involvement in the whole procedure. Specifically, we first split a video into several video clips. Second, a set of features including visual attention, exposure of light, saturation, hue, rule of thirds, contrast and directionality is computed and the qualities of video clips are also estimated. Then, the importance of each video clip is obtained based on these features and the estimated quality. Finally, based on the importance value, we sort clip values in descending order and select an optimal subset to generate video summary. Experimental results demonstrate that the proposed method enables to generate high-quality video summary.

Prestack seismic inversion is by far the most effective method for fluid discrimination. A novel method was developed that uses variable points-constraint strategy to direct extract Gassmann fluid item (GFI) from prestack data. The initial objective function was build combining likelihood function, priori information and GFI approximate equation. The final objective function was acquired by adding a variable number of constraint points to the initial objective function. Three different points-constraint patterns were discussed, and different constraint effects were illustrated using synthetic data. Instead of initial model, this method used constraint model to improve the accuracy and stability of the extraction results. It did not need to obtain P-wave velocity, S-wave velocity and density first, and therefore can avoid accumulation of error that often happens with indirect approach. Model validation and actual application results showed that the proposed method could produce good results even if the SNR of prestack data is pretty low.

To characterize reservoirs with complex fault blocks or lithology, geophysicists often need to depict the edge of geologic bodies such as small faults. Edge detection is a powerful tool for structural feature identification; however, conventional edge-detection operators that are widely used in image edge detection are not always adequate for seismic data. In fact, most conventional edge-detection methods are effective along a plane. For seismic data, it is more appropriate to detect edge information along the slope of an event. We evaluated a new method for fault detection based on a surface-fitting algorithm. The surface-fitting algorithm was used to find the local slope of a seismic event, and then edge detection is performed along this local fitted plane. For each point in a seismic volume, we defined a small neighborhood in a plane parallel to the local reflector with the help of dip estimation. The data in the neighborhood were then approximated by a bivariate cubic function, called the facet model. Then, the local gradient of the function is calculated and referred to as the facet model attribute. To enhance the robustness of the output attribute and suppress noise, the gradient values were summed over a vertical window and normalized by the energy. To evaluate the performance of our method, we also calculated the dip-guided Sobel attribute and variance attribute. Compared with these three attributes, the result of our method suggested more accurate edge detection, and it showed more detail in fault detection.

Transformerless inverters are widely used in grid-tied photovoltaic (PV) generation systems, due to the benefits of achieving high efficiency and low cost. Various transformerless inverter topologies have been proposed to meet the safety requirement of leakage currents, such as specified in the VDE-4105 standard. In this paper, a family of H6 transformerless inverter topologies with low leakage currents is proposed, and the intrinsic relationship between H5 topology, highly efficient and reliable inverter concept (HERIC) topology, and the proposed H6 topology has been discussed as well. One of the proposed H6 inverter topologies is taken as an example for detail analysis with operation modes and modulation strategy. The power losses and power device costs are compared among the H5, the HERIC, and the proposed H6 topologies. A universal prototype is built for these three topologies mentioned for evaluating their performances in terms of power efficiency and leakage currents characteristics. Experimental results show that the proposed H6 topology and the HERIC achieve similar performance in leakage currents, which is slightly worse than that of the H5 topology, but it features higher efficiency than that of H5 topology.

PreviousNext No AccessSEG Technical Program Expanded Abstracts 2013Lithofacies simulation conditioned to diverse data based on MPGAuthors: Peijie YangShuhui LiuXing MuXikun XvChangjiang WangPeijie YangPeijie YangGeoScience Research Institute of Shengli Oilfield, SINOPECSearch for more papers by this author, Shuhui LiuGeoScience Research Institute of Shengli Oilfield, SINOPECSearch for more papers by this author, Xing MuGeoScience Research Institute of Shengli Oilfield, SINOPECSearch for more papers by this author, Xikun XvGeoScience Research Institute of Shengli Oilfield, SINOPECSearch for more papers by this author, Changjiang WangGeoScience Research Institute of Shengli Oilfield, SINOPECSearch for more papers by this author, and Peijie YangPostdoctoral Workstation of Shengli Oilfield, SINOPECSearch for more papers by this authorhttps://doi.org/10.1190/segam2013-0191.1 SectionsAboutPDF/ePub ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinked InRedditEmail Abstract Traditional two-point geostatistics (TPG) simulation algorithms, limited to the reproduction of two-point statistics, cannot reproduce complex geological structures. The alternative to these traditional techniques is the use of multiple-point geostatistics (MPG) simulation. The basic idea behind MPG is to go beyond the two-point modeling and to model the reservoir using multiple-point relations. A new algorithm to MPG stochastic simulation is proposed based on the existing algorithms. Subpatterns are extracted using a predefined template. These subpatterns are clustered using fuzzy c-means clustering and a certain number of class centers, which are defined by user, are acquired. A data event is extracted using the same template and compared with all of the class centers using a similarity criterion. The class center most similar to the data event is acquired. The central value of the class center is taken as the conditional probability density function (cpdf) and is used to carry out stochastic simulation. During the stochastic simulation, conditionings to diverse data are considered. Practical applications in Dongying delta Jiyang depression are realized based on this algorithm by using training images, well data, and seismic data. The model data and practical application results show that the proposed method can achieve better reproduction of geological characteristics of the study area and is beneficial for further application and popularization. Permalink: https://doi.org/10.1190/segam2013-0191.1FiguresReferencesRelatedDetails SEG Technical Program Expanded Abstracts 2013ISSN (print):1052-3812 ISSN (online):1949-4645Copyright: 2013 Pages: 5258 Publisher:Society of Exploration Geophysicists HistoryPublished Online: 19 Aug 2013 CITATION INFORMATION Peijie Yang, Shuhui Liu, Xing Mu, Xikun Xv, Changjiang Wang, and Peijie Yang, (2013), "Lithofacies simulation conditioned to diverse data based on MPG," SEG Technical Program Expanded Abstracts : 2538-2543. https://doi.org/10.1190/segam2013-0191.1 Plain-Language Summary PDF DownloadLoading ...

In order to enhance the accuracy and reliability of evaluation of hydrocarbon traps, the authors have tried methods of quantitative evaluation of traps based on hydrocarbon pool-forming process simulation. The key points are: firstly, all the analyses are based on 3-dimensional dynamic simulation of hydrocarbon pool-forming process. The rationality of evolution of the trap characteristics can be constrained through dynamic simulation and evaluation of trap evolution based on automatic identification and parameter extraction of single hydrocarbon trap accumulation zone. Secondly, various algorithms are adopted for analysing the possibility of the existence of oil and gas reservoirs, such as artificial neural networks. Simulation test indicate that a proven region with higher levels of exploration and the trap location and resource quantity are close to the actual exploration results. Experiment result shows that the proposed design can not only automatically search for hydrocarbon accumulations, but also more accuracy can be achieved in distinguishing the boundary and types of traps and in getting resource quantity of traps.

Blind signal processing technique is one of the hot topics in the field of modern signal processing, aiming at solving problems such as how to separate or estimate the waveforms of the original source from an array of sensors or transducers without or with little knowledge of original waveforms and the characteristics of transmission channels. This paper presents the application of blind signal processing technology to the extraction of seismic weak signals. Based on the investigation and analysis of the relationship between blind signal processing theory and seismic reflection features of subtle pool, an aliasing model of seismic blind-source signals is established in order to extract weak signals from seismic data of target reservoirs. At same time, two new strategies for weak signal extraction are proposed. Using reflection similarity among seismic traces of surrounding rocks and reflection differences of weak signals from target reservoirs, we developed an iterative algorithm for weak signals extraction. The results of simulation and seismic data processing show that the method can extract seismic weak signals successfully and thus improves the resolution of seismic data.

PreviousNext No AccessInternational Geophysical Conference, Shenzhen, China, November 7–10, 2011Study on petrophysical parameters of compacted sandy‐conglomerateAuthors: Luo HongmeiLiu ShuhuiMu XingEditors: Huimin HaoJie ZhangHuimin HaoSearch for more papers by this author, Jie ZhangSearch for more papers by this author, Luo HongmeiInstitue of Geology and Geophysics, Chinese Academy of Sciences, Beijing, 100029GeoScience Research Institute, ShengLi OilField Company, SINOPEC, DongYing 257015Search for more papers by this author, Liu ShuhuiGeoScience Research Institute, ShengLi OilField Company, SINOPEC, DongYing 257015Search for more papers by this author, and Mu XingGeoScience Research Institute, ShengLi OilField Company, SINOPEC, DongYing 257015Search for more papers by this authorhttps://doi.org/10.1190/1.4705074 SectionsAboutPDF/ePub ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinked InRedditEmail Abstract Compacted sandy‐conglomerates with giant‐thickness develop widely in the northern steep slope of Dongying sag, which are multiepisodically superimposed vertically and distributed as a skirt‐shape horizontally. Fan bodies are characterized by narrow facies distribution, rapidly changed physical properties, low permeability and porosity and complicated geophysical responses. More than 100 core samples are selected and analyzed by ultrasound. Based on the analysis of the test data and experimental results, we conclude that the main factors which influence the seismic velocity of sandy conglomeratic body are lithology, porosity, pore structure and lime content. While different fluids are saturated in the rocks, it has less effect on P‐wave velocity. The elastic modulus of dry core samples is different from that of the rocks saturated with oil and water. The difference of petrophysical parameters between samples saturated with oil and water is almost indiscernible. These test and results lay a foundation for the selection of sensitive seismic attributes of sandy‐conglomerate.Permalink: https://doi.org/10.1190/1.4705074FiguresReferencesRelatedDetails International Geophysical Conference, Shenzhen, China, November 7–10, 2011ISSN (online):2159-6832Copyright: 2011 Pages: publication data© 2011 Copyright © 2011 Society of Petroleum Geophysicists, Society of Exploration GeophysicistsPublisher:Society of Exploration Geophysicists HistoryPublished: 10 Apr 2012 CITATION INFORMATION Huimin Hao, Jie Zhang, Luo Hongmei, Liu Shuhui, and Mu Xing, (2011), "Study on petrophysical parameters of compacted sandy‐conglomerate," SEG Global Meeting Abstracts : 88-88. https://doi.org/10.1190/1.4705074 Plain-Language Summary PDF DownloadLoading ...

Direction of arrival estimation is a technique of array signal processing,which is widely used in the radar and mobile communication systems to find the direction of the signal.Comparing with other methods,this method has high resolution in angular.Introducing this method into seismic data coherence algorithm,with the help of focusing in the frequency domain we can focus the phase on a given frequency.Polynomial fitting the focused amplitude and phase,we can obtain some attributes that reveal lateral amplitude and phase changes.These attributes have certain physical significance,and can be used to distinguish small faults and geologic features.Real data processing shows this method is effective.

Seismic data are often influenced unavoidably by various kinds of factors in the course of data acquisition, which reduces the SNR of the seismic data and increases the difficulty of fault recognition. The purpose of fault enhance is to describe the fault clearly and improve the SNR of the seismic data at the same time. Orientational edge preserving fault enhance technology is proposed, seismic event direction information is estimated by orientation filter at first, and then edge preserving filter technology is combined to enhance fault information. Applying this technology to the seismic data and clearer fault information with good continuity of seismic coherence can be acquired. This technology is helpful for structure interpretation and petroleum transportation system quantitative evaluation, thus possesses very important theory and application value.

PreviousNext No AccessSEG Technical Program Expanded Abstracts 2010Mixed‐phase wavelet extraction based on subspace methodAuthors: Peijie YangXing MuShuhui LiuPeijie YangGeological Scientific Research Institute of Shengli Oilfield, SINOPEC, ChinaSearch for more papers by this author, Xing MuGeological Scientific Research Institute of Shengli Oilfield, SINOPEC, ChinaSearch for more papers by this author, and Shuhui LiuGeological Scientific Research Institute of Shengli Oilfield, SINOPEC, ChinaSearch for more papers by this authorhttps://doi.org/10.1190/1.3513614 SectionsAboutPDF/ePub ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinked InRedditEmail Abstract Usually, statistical methods are needed to extract seismic wavelet while there is no well information available. However, statistical wavelets extraction methods are mostly based on high order statistics, which require reflectivities are non‐gauss white noise and its' computation speed is slow. Subspace decomposition mixed‐phase seismic wavelets extraction ignores the assumption, it's based on the orthogonality between a signal and a noise subspaces, and the reflectivities need not be made any assumption; so this method is totally different from high order statistics wavelets extraction. Tests on synthetic and real data show that subspace mixed‐phase wavelet extraction method can provides better wavelet estimation results and the computational complexity is lower, thus very attractive for real application.Permalink: https://doi.org/10.1190/1.3513614FiguresReferencesRelatedDetails SEG Technical Program Expanded Abstracts 2010ISSN (print):1052-3812 ISSN (online):1949-4645Copyright: 2010 Pages: 4453 publication data© 2010 Copyright © 2010 Society of Exploration GeophysicistsPublisher:Society of Exploration Geophysicists HistoryPublished Online: 21 Oct 2010 CITATION INFORMATION Peijie Yang, Xing Mu, and Shuhui Liu, (2010), "Mixed‐phase wavelet extraction based on subspace method," SEG Technical Program Expanded Abstracts : 3679-3683. https://doi.org/10.1190/1.3513614 Plain-Language Summary PDF DownloadLoading ...

Time-frequency analysis is a key technology of signal analyzing and processing in geophysical exploration. It can be used in seismic cycles dividing and isochronous depositional interface identifying. However,the traditional time-frequency analysis methods have many shortcomings of low resolution and indirect result. High-order statistics time-frequency analysis method was proposed based on analyzing the present methods. The new method can reflect the signal spectral characteristics effectively with high resolution and accurate results. Basic principle of the method has been explained ,and the validity of the method has been verified by forward model. This method has been applied in division of cycles and depositional stages of glutenite in the north slope of the Dongying Depression,which has acquired satisfactory effect.

On the basis of studying the sand distribution rules of Zhengjia-Wangzhuang in JiYang Depression, this paper analyses the dependability of stochastic inversion and summarizes its preferable directing effect on the study of reservoir with thin shale layers according to the effect correlation of Constraint Sparse Spike Inversion, Stochastic impedence inversion and Stochastic Simulation. The Stochastic Simulation based on Constraint Sparse Spike Inversion is one of a suit of methods which are good for researching the glutinite reservoir of abrupt slope strip like this area, and it provides the important meaning with use for reference.

油溶释放气是济阳蚴陷中浅层天然气的重要来源.本文从不同角度阐明了溶解相态是济阳蚴陷天然气初次运移的主要相态,并从油和地下水溶解天然气模型出发,首次定量地确定了济阳蚴陷油溶释放气的起始脱气深度,分析了天然气的赋存状态,建立了济阳蚴陷油溶释放气的脱气模式:不同洼陷起始脱气深度略有差异,一般在1700-2000m之间,平均1900m,埋藏深度小于起始脱气深度,是气藏气存在的主要区域.在起始脱气深度至1200m之间,以气顶气和夹层气藏为主;深度小于1200m,以纯气层气藏为主;在3900m至起始脱气深度之间,天然气在油中处于欠饱和状态,以溶解气的赋存形式为主;深度大于3900m,烃源岩开始进入游离气生成阶段,可形成深层原生气藏.另外,本文尝试性地提出了"饱和程度"的概念和计算方法,并预测了济阳坳陷天然气的有利含气区带.

Based on available well temperatures and vitrinite reflectance (Ro) data, geothermal history of Zhanhua sag, Jiyang Depression was reconstructed with synthesizing lithosphere-scale and basin-scale multi-linear medel offered in this paper. The study result indicates: (l ) the heat flow evolution curve show a general tendency of decreasing slowly interrupted by two picking up periods that shapes' a saddle' from the Paleocene to the Present. The ca1culated heat flow is about 83. 6 mW/m in the early Paleocene corresPOnding to active rift region, however, the present heat flow gets down to 63mW/m as the global average value. (2) the main oil bearing layers exPerienced long term slowly heating process, subsequently, it is sti1l at the 'oil generation window', and has a wide range depth for oil existence. ffe, the geothermal evolution background is favorable to oil genertdri. The conclusion can also be further prooed by the rifting medel of Bohaiwan Basin, and is useful to oil oploration in this area.