Spatio‐temporal analysis and modeling of short‐term wind power forecast errors

Forecasts of wind power production are increasingly being used in various management tasks. So far, such forecasts and related uncertainty information have usually been generated individually for a given site of interest (either a wind farm or a group of wind farms), without properly accounting for the spatio‐temporal dependencies observed in the wind generation field. However, it is intuitively expected that, owing to the inertia of meteorological forecasting systems, a forecast error made at a given point in space and time will be related to forecast errors at other points in space in the following period. The existence of such underlying correlation patterns is demonstrated and analyzed in this paper, considering the case‐study of western Denmark. The effects of prevailing wind speed and direction on autocorrelation and cross‐correlation patterns are thoroughly described. For a flat terrain region of small size like western Denmark, significant correlation between the various zones is observed for time delays up to 5 h. Wind direction is shown to play a crucial role, while the effect of wind speed is more complex. Nonlinear models permitting capture of the interdependence structure of wind power forecast errors are proposed, and their ability to mimic this structure is discussed. The best performing model is shown to explain 54% of the variations of the forecast errors observed for the individual forecasts used today. Even though focus is on 1‐h‐ahead forecast errors and on western Denmark only, the methodology proposed may be similarly tested on the cases of further look‐ahead times, larger areas, or more complex topographies. Such generalization may not be straightforward. While the results presented here comprise a first step only, the revealed error propagation principles may be seen as a basis for future related work. Copyright © 2010 John Wiley & Sons, Ltd.     

Multiple architecture system for wind speed prediction

A new approach based on multiple architecture system (MAS) for the prediction of wind speed is proposed. The motivation behind the proposed approach is to combine the complementary predictive powers of multiple models in order to improve the performance of the prediction process. The proposed MAS can be implemented by associating the predictions obtained from the different regression algorithms (MLR, MLP, RBF and SVM) making up the ensemble by three fusion strategies (simple, weighted and non-linear). The efficiency of the proposed approach has been assessed on a real data set recorded from seven locations in Algeria during a period of 10 years. The experimental results point out that the proposed MAS approach is capable of improving the precision of the wind speed prediction compared to the traditional prediction methods.     

大位移井钻井摩阻预测及井眼轨道优选

大位移井钻井的施工难度主要来自钻井的摩阻大,因此在钻大位移井时必须较准确地预测摩阻,根据摩阻预测情况优选井眼轨道.近年来经过多次实践和研究大位移钻井的设计和施工情况,分析了钻井摩阻产生的原因及影响大位移井正常钻进的主要因素,提出了应利用成熟的软件来选择低摩阻的井眼轨道,总结了摩阻预测以及井眼轨道优选的方法,为同类井的施工提供了经验.     

基于路面标记的车辆检测和计数

交通监视系统通过采集实时交通流量数据，为智能化交通运输服务和控制管理提供依据，在智能交通系统中有着极其重要的作用。在基于视频图像的交通监视系统中，由路边建筑、树木等物体引起的静态阴影和由运动物体如车辆引起的运动阴影，是导致车辆检测错误的一大主要因素。提出了一种基于路面标记的自动车辆检测算法，用于检测车辆并排除阴影干扰，进而实现对过往车辆进行正确计数，能更可靠地收集各车道的实时车流信息。     

基坑变形的动态神经网络实时建模预报方法

为了对基坑变形进行更准确的监测和预报，根据基坑变形的特点，提出了应用动态递归神经网络进行实时建模预报，并采用一种改进的在线学习算法，较好地描述了基坑变形的动态特性。通过对某工程基坑的监测，验证了该方法的有效性。     

昆北断阶带基岩储层特征及油气成藏条件

利用岩心、薄片、扫描电镜、测井及储层物性等资料,对昆北断阶带基岩储层特征及油气成藏条件等进行了研究。 结果表明: 基岩储层岩性主要为花岗岩和变质板岩;花岗岩主要以溶蚀缝、构造缝和溶蚀孔为储集空间,板岩主要以构造缝为储集空间;基岩油气成藏的有利条件包括良好的油气源,丰富的构造裂缝、溶蚀缝和溶蚀孔等储集空间,多样的圈闭类型和良好的疏导体系;基岩油气成藏的主控因素为多期次活动的断裂和不整合面及之下的风化壳。     

基于三维场的储层预测方法及应用

三维体可视化解释是通过采用各种不同的透明度参数,在三维空间内对三维地震数据体直接刻画地层的构造、岩性及沉积特征[1]。这种三维立体扫描和追踪技术可使解释人员快速选定目标,结合精细的钻井标定,可帮助解释人员准确、快速的描述各种复杂的地质现象。自组织神经网络地震相分析是一种基于地震道形状的地质特征描述方法,主要通过对不同地震道的波形分析来获得地震相分布,结合测井相标定,可进一步将地震相转换成沉积相的三维空间分布。在对委内瑞拉英特甘博油田复杂岩性油藏的储层空间非均质性以及油水关系研究中,综合应用这两种基于三维场的地震体直接刻画方法,结合测井标定,取得了很好的应用效果。     

灰色拓扑预测方法在评价压裂效果中的应用

应用 灰色拓扑预测方法,由压裂前的油井日产油数据,建立了GM(1,1)模型群,并预测了在压裂有效期内该井不压裂时的产量动态,从而可真实地评价压裂的增产效果。该方法尤其适用于压裂前产量波动比较大的情况。经矿场资料验证,可信度较高,可作为科学评价压裂效果的重要依据。     

小洼地区洼38井区精细构造解释与储层预测

为寻找洼38井区新的出油点和储量增长点,借助Landmark一体化软件,应用相干体分析,可视化,地震属性分析等新技术对其进行研究,通过研究,。进一步搞清了该区的沉积,构造,储层特征及油气分布规律,发现和落实有利圈闭4个,同时指出了上不勘探的方向;在清东陡坡带应注重断鼻的勘探,在潜山披覆构造带上应注重充填沉积体的勘探,在冷东逆掩断裂带上应以断块勘探为主。     

原油闪点预测模型的研究

针对原油这类结构组成复杂、差异性大、可燃的复杂混合体系,选取各地区共计101种原油的恩氏蒸馏温度、20℃密度、20℃粘度作为输入变量,建立原油闪点预测模型。采用主成分分析法对输入变量进行降维,除去恩氏蒸馏系列数据中的信息冗余,分别采用多元线性回归(MLR)、BP神经网络、RBF神经网络三种方法建模,并对模型的预测结果进行对比,RBF神经网络模型的预测准确度与稳定性均为最优,绝对误差期望为2.94℃,相对误差期望为3.45%,BP神经网络模型的准确性优于多元线性回归模型,稳定性不如MLR模型。