鄂尔多斯盆地北部山西组页岩沉积相及其对页岩储层的控制作用

鄂尔多斯盆地北部山西组页岩气储层与煤层共生,页岩有机质含量较高,具有较大的资源勘探潜力。为精细表征控制山西组页岩储层分布的沉积微相,根据测井数据、录井数据、岩芯观察描述、薄片分析、粒度分析、X射线衍射全岩分析以及总有机碳含量(TOC),研究了山西组页岩储层岩相与沉积微相类型,在山西组识别出(灰)黑色碳质页岩、(灰)黑色含碳质页岩、(灰)黑色含碳质(粉)砂质页岩、(深)灰色含碳质页岩、(深)灰色页岩、(深)灰色(粉)砂质页岩和含钙质页岩7种岩相。这些岩相沉积在富植沼泽、贫植沼泽、三角洲平原分流间洼地、曲流河河间洼地、天然堤与决口扇远端微相环境,其中富植沼泽、贫植沼泽与成煤的泥炭沼泽、泥炭坪环境比邻共生,且在山二段时期更发育。富植沼泽和贫植沼泽微相控制了具有较高TOC的(灰)黑色碳质页岩、(灰)黑色含碳质页岩、(灰)黑色含碳质(粉)砂质页岩和(深)灰色含碳质页岩的分布,是控制山西组页岩储层分布的有利微相。     

基于MODIS时序数据的青海湖流域植被时空变化特征及其与气候因子的关系(英文)

Global warming has led to significant vegetation changes in recent years. It is necessary to investigate the effects of climatic variations(temperature and precipitation) on vegetation changes for a better understanding of acclimation to climatic change. In this paper, we focused on the integration and application of multi-methods and spatial analysis techniques in GIS to study the spatio-temporal variation of vegetation dynamics and to explore the vegetation change mechanism. The correlations between EVI and climate factors at different time scales were calculated for each pixel including monthly, seasonal and annual scales respectively in Qinghai Lake Basin from the year of 2001 to 2012. The primary objectives of this study are to reveal when, where and why the vegetation change so as to support better understanding of terrestrial response to global change as well as the useful information and techniques for wise regional ecosystem management practices. The main conclusions are as follows:(1) Overall vegetation EVI in the region increased 6% during recent 12 years. The EVI value in growing seasons(i.e. spring and summer) exhibited very significant improving trend, accounted for 12.8% and 9.3% respectively. The spatial pattern of EVI showed obvious spatial heterogeneity which was consistent with hydrothermal condition. In general, the vegetation coverage improved in most parts of the area since nearly 78% pixel of the whole basin showed increasing trend, while degraded slightly in a small part of the area only.(2) The EVI change was positively correlated with average temperature and precipitation. Generally speaking, in Qinghai Lake Basin, precipitation was the dominant driving factor for vegetation growth; however, at different time scale its weight to vegetation has differences.(3) Based on geo-statistical analysis, the autumn precipitation has a strong correlation with the next spring EVI values in the whole region. This findings explore the autumn precipitation is an important indicator, and then, limits the plant growth of next spring.     

Derivation of reliability index vector formula for series system and its application

In this study, a reliability index vector formula is proposed for series system with two failure modes in term of the concept of reliability index vector and equivalent failure modes. Firstly, the reliability index vector is introduced to determine the correlation coefficient between two failure modes, and then, the reliability index vector of a series system can be obtained. Several numerical cases and an analysis on offshore platform are performed, and the results show that this scheme provided here has better computational accuracy, and its calculation process is simpler for the series systems reliability calculations compared with the other methods. Also this scheme is more convenient for the engineering applications.     

防汛河道汛期蓄水问题的探讨

在根据聊城市徒骇河、马颊河高水位渡汛成熟经验基础上,通过水文分析证明其合理性,并提出了高水位度汛中科学调度的重要性.     

国产不锈钢筛试制成功

我队受地矿部物化探局的委托,与上海新兴丝网商店合作,于82年9月和83年元月先后试制二批不锈钢筛共102套,分发给各省局中心实验室及部分省、区局从事化探工作的地质队推广试用。现将不锈钢筛的技术指标和试用情况报导如下:     

基于机器学习的模式温度预报订正方法研究

机器学习在气象数值模式的后处理中表现优越,但其稳定性和适用性有待深入探究。本文选取了ECWMF模式包括2米温度、风、降水等多气象要素预报产品和安徽省80个国家气象站观测2米温度实况资料,分析了EC模式在安徽省站点温度预报误差,利用决策树、随机森林、LightGBM三种机器学习算法订正EC 模式0-72小时温度站点预报,并将其与传统MOS订正方法和SPCC主观预报产品进行了对比。结果表明：EC模式高温预报误差明显高于低温预报,在安徽皖南山区和大别山区存在较大误差;机器学习算法中最高温度预报随机森林表现最优,最低温度预报LightGBM最优,比EC模式平均绝对误差MAE分别降低了0.55℃、0.2℃,均方根误差RMSE分别降低0.6℃、0.31℃,预报准确率提高了18.16%和5.19%;高山站独立建模并融合周围站的信息能有效降低模型误差;相比SPCC主观预报产品,机器学习预报模型在高温和寒潮过程中互有优劣,但在天气转折初期落后;机器学习可以作为常规预报模式的补充,能显著优化或改善传统预报中温度预测精度,特别是对于数据缺乏的高山站点。     

海南岛西部沙化土地时空变化过程及其与气候因子的关系

本文利用Landsat-TM和MODIS遥感影像, 结合遥感、GIS空间分析及数理统计等技术方法, 研究了1989~2010年海南岛西部沙化土地时空变化过程及其与气候因子的关系。结果表明:1)1989~2010年海南岛西部非沙化面积显著上升, 总体增速为9.2km2/a, 不同程度沙化区域面积均显著下降, 轻度沙化区面积变化在沙化控制中起主导作用, 重度沙化区面积下降最为显著; 2)1990~2010年土地转移分析表明, 20年中研究区域沙化土地面积总体降低174.04km2, 其中67.67 % 的区域为轻度沙化土地, 非沙化区域、轻度沙化区域、中度沙化区域以及重度沙化区域发生转化的面积分别达到1.59 % 、94.67 % 、98.02 % 和99.46 %, 沙化土地转换频繁, 非沙化区域相对稳定; 3)沙化土地主要分布在海岸带区域, 植被覆盖度低, 人类活动频繁, 变化波动剧烈。2000年以来植被覆盖总体上升, 其中西海岸的中部和北部植被覆盖显著上升, 沙化土地得到明显改善; 4)相关性分析表明: 非沙化面积与年降水、年均温均呈显著正相关, 相关系数分别为0.82(pp<0.05), 气温和降水是海南岛西部土地沙化的重要驱动因子, 其中降水对土地沙化的影响相对较大。     

基于双目成像云底高度测量方法

采用基线长为60 m的一对数字摄像机,构成双目成像云底高度测量系统,随着数字摄像技术和立体视觉传感器的发展,尤其是双目成像视觉传感器以结构简单、使用方便、测量精度高等诸多优点而被广泛应用。通过直方图均衡化方法对图像进行增强,利用亚像素角点检测器检测角点提高测量精度,并采用归一化互相关方法进行区域相关检测寻找同名点,将外极线约束引入图像匹配过程中进行同名点粗差去除,提高测量准确度;再根据匹配特征点得到相对视差,利用摄影测量原理计算云底高度;建立三维实验室标校场对相机进行内外方位元素标校,利用星星相对位置与相机姿态角的关系对相机进行现场标校,简化标校系统提高测量精度。利用2011年5月1日—6月30日采集的样本,在北京市观象台与维萨拉生产的CL31激光云高仪进行对比试验,并对产生云底高度测量系统误差的可能原因做出具体分析。     

基于星点状方解石胶结与溶解的识别查明砂岩粒间孔隙类型——以雅布赖盆地新河组砂岩为例

目前含油气砂岩中粒间孔隙是原生孔隙还是次生孔隙的认识仍不一致,而对星点状方解石胶结与溶解的识别能够有效地查明粒间孔隙的类型。文章通过铸体薄片细致地观察雅布赖盆地新河组砂岩中的微观现象,以成岩环境演化和成岩序列分析为主线,重视方解石胶结物的赋存状态与物质来源和溶蚀流体来源的配置关系,精细解剖微观现象,从而弄清楚星点状方解石的成因,进而查明砂岩的粒间孔隙类型和储集空间类型。结果表明,粒间孔隙中的星点状方解石是成岩早期浸染状方解石胶结物的溶蚀残余,溶蚀流体为成岩中期的有机酸流体,溶蚀类型为一致性溶解,形成的粒间孔隙为次生孔隙。鉴于此,雅布赖盆地新河组砂岩的储集空间由次生粒间孔隙和次生粒内孔隙（长石、岩屑、方解石胶结物的溶蚀孔隙）组成。