碳酸盐岩岩溶储层多井评价方法及地质应用

多井评价是建立在单井精细解释对比分析基础上的预测储层及含油气性平面分布规律的技术方法,而常规测井资料无法区分碳酸盐岩岩溶储层,因而利用多井评价结果确定岩溶发育程度在平面上的分布规律就显得十分重要。为此,在岩心标定成像测井的基础上,对四川盆地高石梯—磨溪地区15口井的成像测井岩溶发育特征进行分析,建立了中二叠统茅口组岩溶发育各分带的标准成像图版,利用交会图及直方图分析各分带的常规测井响应特征,在此基础上形成了电成像测井刻度常规测井识别岩溶发育带的新方法。研究结果表明:①高石梯—磨溪地区茅口组岩溶带自上而下可划分为风化壳残积带、垂直渗流岩溶带、水平潜流岩溶带以及受岩溶作用较弱的基岩;②风化壳残积带在成像测井图像显示为"暗—亮—暗"条带状模式,垂直渗流岩溶带为垂直线状与暗色斑状组合模式,水平潜流岩溶带为水平线状—层状与斑状组合模式,基岩整体显示为亮色块状模式偶见线状或斑状特征;③有效储层主要发育在垂直渗流带和水平潜流带的顶部;④该区茅口组岩溶发育主要受裂缝发育控制,而裂缝发育又与断层关系密切。结论认为,该新方法对碳酸盐岩岩溶储层的多井评价具有普遍适用性,为四川盆地中二叠统风险探井的部署提供了技术支撑。     

金刚烷最新研究

金刚烷是近 30年来发展起来的一种新型精细化工原料。简要介绍了金刚烷的分子结构、性质及其主要用途 ,重点对近年来国内外报道过的金刚烷合成方法进行了评述 ,在此基础上指出了金刚烷化工的未来发展趋势。     

D.c. conduction studies on thermally evaporated neodymium oxide thin films

Aluminium-neodymium oxide-aluminium thin film capacitors have been prepared by thermal evaporation and the d.c. conduction properties of these films have been studied. The thicknesses of the films have been determined by a multiple beam interferometer. The current-voltage power-law dependence showed that the conduction in these films is space-charge limited. The linear dependence of the current density on the square root of the applied field confirmed the exponential trap distribution. The trap density has been found to be of the order of 10²⁶ m^–3. It has also been observed that the Schottky type of conduction is predominant in the high-field region and the height of the Schottky barrier has been determined. It is seen that the conduction mechanism is an activated process with the activation energy decreasing with increasing field.     

Modal Kalman filtering based impedance relaying

An algorithm is presented for computer distance relaying. It is based on modal Kalman filtering (MKF) to estimate fundamental phasors, MKF exploits all the measurement information available from a three-phase line and is founded on enhanced models of the electromagnetic transients noise. To support the modeling of noise for different faults, a study of nontrivial electrical networks with accurate electromagnetic transients modeling is made for 400 kV transmission lines. MKF fits the behavior of the different modal noise for the Clarke phasors, but it is invariant for each type of fault, assuring robustness and minimum error variance. To computer distance, Clarke αB phasors are transformed to +/- symmetrical components, and then a well-known expression is used to computer the positive impedance. Statistical analysis if presented to assess observation time versus estimation accuracy for the different types of line faults     

A study of mixtures of poly(ethylene oxide) with polystyrene or poly(styrene-co-acrylic acid) by inverse gas chromatography and viscosimetry

Summary Systems of poly(ethylene oxide)/polystyrene and of poly(ethylene oxide)/poly(styrene-co-acrylic acid) of different ratios were studied by inverse gas chromatography using benzene and n-decane as molecule probes and by viscosimetry in tetrahydrofuran. The transition temperatures as shown in the retention diagrams and the interaction parameters as determined by inverse gas chromatography and by viscosimetry showed that whereas poly(ethylene oxide) is incompatible with polystyrene, the introduction of amounts of acrylic acid groups into polystyrene chains by free radical copolymerization led to compatible systems of the acidic copolymer with the poly(ethylene oxide).     

Network regression with predictive clustering trees

Network data describe entities represented by nodes, which may be connected with (related to) each other by edges. Many network datasets are characterized by a form of autocorrelation, where the value of a variable at a given node depends on the values of variables at the nodes it is connected with. This phenomenon is a direct violation of the assumption that data are independently and identically distributed. At the same time, it offers an unique opportunity to improve the performance of predictive models on network data, as inferences about one entity can be used to improve inferences about related entities. Regression inference in network data is a challenging task. While many approaches for network classification exist, there are very few approaches for network regression. In this paper, we propose a data mining algorithm, called NCLUS, that explicitly considers autocorrelation when building regression models from network data. The algorithm is based on the concept of predictive clustering trees (PCTs) that can be used for clustering, prediction and multi-target prediction, including multi-target regression and multi-target classification. We evaluate our approach on several real world problems of network regression, coming from the areas of social and spatial networks. Empirical results show that our algorithm performs better than PCTs learned by completely disregarding network information, as well as PCTs that are tailored for spatial data, but do not take autocorrelation into account, and a variety of other existing approaches.     

基于定点化自适应选择卷积神经网络的电力缺陷识别方法

无人机(unmanned aerial vehicle,UAV)电力巡检时的图像数据量急剧增加,为使深度卷积神经网络(deep convolutional neural network,DCN-N)在低功耗的前提下仍能准确识别出电力缺陷,将重点改进传统DCNN算法,以减少机载前端平台中DCNN模型的计算成本,有效提高电力缺陷识别的运行速度,进而延长巡检无人机的续航里程.首先将卷积网络中的浮点运算进行定点化近似,然后通过快速机器学习算法对DCNN模型的输入图像进行自适应选择,最后通过实验对所提方法进行了验证.实验结果证明,DCNN模型经8比特定点优化和自适应选择选择策略后的准确率达88.2％,推理时间缩短了65.9％,能耗减少了71.9％,查准率提高了9.8％.所设计的定点化DCNN模型自适应选择策略不仅能节约电力巡检系统的功耗,而且能提高电力缺陷识别的精度.     

宽频测量装置两种谐波/间谐波算法比较

新能源发电大规模入网,造成电力系统电能质量问题.宽频测量装置可监测谐波/间谐波的含量,但谐波/间谐波的测量在工程实现中目前存在两种方案,有争议.介绍了这两种方案的实现方法和各自的局限性,供后续工程参考.