鄂尔多斯盆地西南部上三叠统延长组长8、长6油层组 的沉积体系与物源方向

野外露头剖面的岩石学与岩相组合,沉积特征与相标志,古流向测定,室内砂岩的骨架矿物、重矿物组合及其平面分布规律的研究结果表明：鄂尔多斯盆地西南部上三叠统延长组长8油层组是以线状或点状物源为特征的一套近源快速堆积的冲积扇与扇三角洲沉积体系,形成于盆地由快速拗陷转入逆冲负荷沉降期间。长8沉积期盆地西南部的古水流与物源主要来自盆地西南方向,其次为西北和东南方向。长6油层组沉积期,盆地内部底床下沉作用减缓,湖盆开始收缩,湖盆西岸除北部有少量扇三角洲沉积外,主要为辫状河三角洲沉积：而盆地东北部与东部的沉积作用大大加强,致使在盆地东部形成一系列大型曲流河三角洲沉积体系,至盆地西南部相变为半深湖-深湖相与浊流相沉积。长6沉积期古水流除来自西南、西北和东南方向外．还有来自北东和正东方向的次要物源,它们在盆地西南部悦乐-玄马-板桥-固城-合水-带汇合,使该地带成为混合物源区。     

An approach of surface coal fire detection from ASTER and Landsat-8 thermal data: Jharia coal field,India

Radiant temperature images from thermal remote sensing sensors are used to delineate surface coal fires, by deriving a cut-off temperature to separate coal-fire from non-fire pixels. Temperature contrast of coal fire and background elements (rocks and vegetation etc.) controls this cut-off temperature. This contrast varies across the coal field, as it is influenced by variability of associated rock types, proportion of vegetation cover and intensity of coal fires etc. We have delineated coal fires from background, based on separation in data clusters in maximum v/s mean radiant temperature (13th band of ASTER and 10th band of Landsat-8) scatter-plot, derived using randomly distributed homogeneous pixel-blocks (9 × 9 pixels for ASTER and 27 × 27 pixels for Landsat-8), covering the entire coal bearing geological formation. It is seen that, for both the datasets, overall temperature variability of background and fires can be addressed using this regional cut-off. However, the summer time ASTER data could not delineate fire pixels for one specific mine (Bhulanbararee) as opposed to the winter time Landsat-8 data. The contrast of radiant temperature of fire and background terrain elements, specific to this mine, is different from the regional contrast of fire and background, during summer. This is due to the higher solar heating of background rocky outcrops, thus, reducing their temperature contrast with fire. The specific cut-off temperature determined for this mine, to extract this fire, differs from the regional cut-off. This is derived by reducing the pixel-block size of the temperature data. It is seen that, summer-time ASTER image is useful for fire detection but required additional processing to determine a local threshold, along with the regional threshold to capture all the fires. However, the winter Landsat-8 data was better for fire detection with a regional threshold.     

基于MicroStation V8的地形图更新与质检系统的开发

在MicroStation VBA环境下,对MicroStation V8进行二次开发,实现了一套基于MicroStation V8平台的多比例尺地形图要素更新与质检系统。该文着重阐述了该系统在处理点、线、面、注记、属性、出图效果及质量检查控制等方面的设计。通过二次开发,快速实现了地形图的更新与维护,并有利于质量的控制,符合入库要求。     

资源一号02C与Landsat8影像融合方法对比分析

针对以往关于资源一号02C和Landsat8卫星影像数据融合的研究不足的问题,该文利用前者在空间分辨率上高于后者、后者具有前者所不具有的光谱信息这一特性,选取主成分变换法、比值变换法、色彩变换法、高通滤波法和超分辨率贝叶斯法5种融合方法,分别对两种数据本身及数据间进行融合,并利用定性与定量的方法对融合结果进行评价,得出:资源一号02C星全色波段与多光谱波段数据融合结果中高通滤波法与超分辨率贝叶斯法效果较好,Landsat8OLI全色波段与多光谱数据融合结果中高通滤波法效果最好,资源一号02C星全色波段与Landsat8OLI多光谱数据融合结果中高通滤波法效果最好。     

频谱激电法在豫西某铅锌银矿区中的应用

采用频谱激电(SIP)法对豫西某铅锌银矿区已发现的激电中梯异常进行了评价。利用 V8多功能电法工作站9道轴向偶极—偶极装置采集数据,经过视谱反演后,根据从已知到未知的原则,总结了本区的物探找矿标识,确定了高充电率、中低阻梯度带、中等时间常数,低频率相关系数的视谱参数组合特征。根据地质矿产资料对具有“高—梯度带(中低阻)—中—低”组合特征的频谱激电异常进行了分类评价,并圈定了找矿靶区。根据圈定的找矿靶区进行了钻探验证,结果表明在定位的Ⅰ类异常靶区中寻找到较大规模的深部隐伏矿体,取得了较好的应用效果。     

Study of high temperature targets identification and temperature retrieval experimental model in SWIR remote sensing based Landsat8

For surface features in short-wave infrared (SWIR, 1.3–3.0 μm) in remote sensing imagery, pixel values depict the total energy including reflection and emission. For surface features at normal temperature in SWIR band, emission energy can be ignored. While for surface features at high temperature in SWIR band, emission energy is equal to or even higher than the reflection energy. So remote sensing imagery of SWIR band can be used to separate emission and reflection energy as well as to realize temperature retrieval of high temperature targets. In this study, the seventh band (SWIR band) of Landsat8 OLI remote sensing imagery is used to perform the theoretical model research for temperature retrieval of high temperature targets. In the meantime, it is also used with the corresponding observation experiment of synchronization satellite to check the theoretical model. The result shows that the radiant flux density for mixed pixels with high temperature targets is higher than adjacent pixels without high temperature targets. Thus, the high temperature pixels can be identified in SWIR band. The retrieval results of temperature and fractional area for high temperature targets are consistent with reality. In the study, the result illustrates that it is effective to identify high temperature targets in remote sensing imagery of SWIR band and the model is appropriate for temperature retrieval use.     

姬塬地区长8油层组层序地层格架内成岩相展布特征

通过岩心观察并充分利用普通薄片、铸体薄片、阴极发光、X-衍射和扫描电镜等资料,对姬塬地区长8油层组储层的成岩作用、成岩矿物、成岩阶段和成岩演化序列特征等进行了研究。根据成岩作用类型及强度、成岩矿物等将储层划分为绿泥石衬边弱溶蚀、不稳定组分溶蚀、压实致密、高岭石充填和碳酸盐胶结5种成岩相。并通过岩心薄片资料刻度测井归纳出不同成岩相在GR、AC等测井曲线及其组合上的响应特征,由此实现各单井储层成岩相的连续划分。对长8油层组层序界面和基准面旋回与成岩相展布的关系进行了研究,结果表明层序界面附近不稳定组分溶蚀相及高岭石充填相较为发育,且各井之间对比性良好,同时层序界面也控制了碳酸盐胶结;中期基准面旋回的最大湖泛面处均发育井间可对比的压实致密相,长82中期基准面下降半旋回砂体一方面易于遭受溶蚀产生次生孔,另一方面由于受沉积驻留和碎屑组分影响导致压实强度较弱,因此物性总体比长81砂体好。     

A Machine Learning-based Cloud Detection Algorithm for the Himawari-8 Spectral Image

Cloud Masking is one of the most essential products for satellite remote sensing and downstream applications. This study develops machine learning-based (ML-based) cloud detection algorithms using spectral observations for the Advanced Himawari Imager (AHI) onboard the Himawari-8 geostationary satellite. Collocated active observations from Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) are used to provide reference labels for model development and validation. We introduce both daytime and nighttime algorithms that differ according to whether solar band observations are included, and the artificial neural network (ANN) and random forest (RF) techniques are adopted for comparison. To eliminate the influences of surface conditions on cloud detection, we introduce three models with different treatments of the surface. Instead of developing independent ML-based algorithms, we add surface variables in a binary way that enhances the ML-based algorithm accuracy by ~5%. Validated against CALIOP observations, we find that our daytime RF-based algorithm outperforms the AHI operational algorithm by improving the accuracy of cloudy pixel detection by ~5%, while at the same time, reducing misjudgment by ~3%. The nighttime model with only infrared observations is also slightly better than the AHI operational product but may tend to overestimate cloudy pixels. Overall, our ML-based algorithms can serve as a reliable method to provide cloud mask results for both daytime and nighttime AHI observations. We furthermore suggest treating the surface with a set of independent variables for future ML-based algorithm development.     

四川盆地白马地区白马8井垂向地球化学特征

文章在详细介绍各项油气化探指标异常形成机制的基础上,通过对白马8井不同地层中化探指标的变化规律、含量特征以及相关元素对比值分析,结果发现白马8井各层位均无油气富集,但发现须家河组第二和第四岩性段是区域上良好的储层,在今后的油气勘查中应该予以重视。     

唐山7.8级地震前的震中迁移与远台前兆的关系

以震中迁移始发点的前兆讨论了唐山7.8级地震震中位置的预测,并以此为例分析了汶川8级地震和芦山7级地震的前兆问题。另外,从震中迁移延长线上的前兆来讨论了唐山大震的发生时间。