浅水三角洲沉积体系与储层岩石学特征

浅水三角洲已经成为当前沉积学研究和油气勘探的重点领域,浅水三角洲常规和非常规砂岩储层中发现了丰富的油气资源。鄂尔多斯盆地中—古生界发育大型浅水三角洲沉积,结合岩芯、测井、分析化验等资料,对盆地西部地区山1—盒8段浅水三角洲的母岩特征、沉积充填、砂体展布与储层岩石学特征进行研究,为研究区常规砂岩储层和致密砂岩油气勘探提供地质依据。分析表明,研究区南部和北部砂岩重矿物组合相似,以锆石和白钛矿为主。综合La/Yb-REE与Dickinson三角图解、稀土元素配分模式和碎屑锆石定年分析认为,北部物源主要来自盆地西北部阿拉善古陆太古界和元古界花岗岩、片麻岩、石英砂岩,向南影响到陇东地区北部;南部物源主要来自盆地南部北秦岭地区太古界、元古界花岗岩、片麻岩和片岩,向北影响陇东地区中南部。山1段发育曲流河三角洲,盒8段发育辫状河三角洲,孤立型与垂向叠置型水下分支河道砂体是主要的砂体类型。盒8段沉积时期,古湖泊可能萎缩;南北物源形成的三角洲在研究区中部环县东南一带交汇混合。砂岩类型主要为岩屑质石英砂岩、石英砂岩和岩屑砂岩,结构成熟度中等—较差。砂岩成岩改造强烈,水—岩反应复杂,压实作用是储层致密化的主因,多期胶结作用使砂岩的孔喉结构变得十分复杂。孔隙类型以微米—纳米级的岩屑溶蚀孔、剩余粒间孔和高岭石晶间孔为主,整体上属于非常规致密砂岩储层。砂体分布与“甜点”预测是研究区致密油气勘探的关键。     

白天和夜间通用的卫星遥感沙尘判识算法构建与验证分析

Himawari-8是日本发射的新一代静止气象卫星,与前一代的MTSAT-2相比,在时间、空间分辨率上都有了很大提升,特别是红外通道数量从4个增至10个,为红外遥感沙尘提供了新的观测数据。本研究利用Himawari-8的红外观测数据,发展了仅用红外通道的沙尘全天候判识算法,可以实现对白天和夜间的连续监测。算法在前人基础上去除了可见光通道,同时引入更多红外通道来进行云检测和沙尘判识。由于一日之中,地表温度发生变化,因此针对白天和夜间设置了两套不同的判别阈值,来保证算法的全天适用性。最后通过两次沙尘事件对沙尘判别结果的分析和检验表明,遥感判识结果与地面气象站和PM_(10)观测较为一致,说明了只用红外通道全天候判识沙尘的可行性。     

基于Himawari-8卫星的云参数和降水关系研究

基于日本Himawari-8卫星的云产品,对中国中东部地区2017年夏季(6—8月)每日08—17时的降水资料进行了分析,重点讨论了云光学厚度(COD)、云顶粒子平均尺度(CPS)、云顶温度(CTT)三个云参数与降水的关系。试验表明,降水概率与云参数相关性较高,存在随着COD增加、CPS增加、CTT减小而增加的明显趋势。但是,单个云参数与降水强度相关性则较低;COD、CPS、CTT与小时降雨率的相关系数分别为0.2315、0.1823、-0.2235,均为弱相关。如果综合考虑联合两个或三个云参数形成小时降雨率分布矩阵,则降水过程能得到更为清晰的体现。2017年8月28日的个例表明,相比纯粹基于红外的算法,三参数方法可以明显提高小时降雨率的估计精度。     

印尼8.7、8.5级远震对云南地区小震的激发和地下流体异常响应初探

2004年12月26日和2005年3月29日,印度尼西亚苏门答腊西北海域相继发生8.7和8.5级地震。通过对这两次地震与云南地震活动关系和地下流体记录异常变化的分析,认为:印尼两次8级地震的发生可能会使云南提前进入新一轮强震活跃期;远震对云南地区小震的激发和导致地下流体记录出现异常变化的因素虽然都与大地震面波的强弱、地质构造环境等有关,但机理不同。     

基于“葵花8号”气象卫星的陇东南地区强对流识别跟踪技术研究

利用常规观测资料、区域自动站资料和“葵花8号”气象卫星资料,对2016年4—9月甘肃省陇东南地区出现的43次强对流天气过程进行分析,确立了强对流云团识别指标、追踪方法及预报指标,并对2018年部分个例进行效果检验。结果表明：（1）利用卫星B13通道（10.4μm）亮温值TBB≤238 K或B08通道（6.2μm）与B13通道亮温差△TBB<0 K双阈值作为强对流云团识别指标,可以准确识别出陇东南地区的强对流天气云团;（2）利用“逆向搜索法”、“面积重叠法”及对云团重心的计算,可以对强对流云团进行准确定位、追踪及移动路径外推预报;（3）建立的强对流天气落区判别指标对该地区短时强降水及冰雹落区具有一定的预报能力。     

鄂尔多斯盆地南部旬邑-宜君地区中生界储层特征

对鄂尔多斯盆地南部旬邑 -宜君地区中生界主要储集层——直罗组、延安组、延长组储层特征从沉积相、砂体纵向展布、岩性和物性等几方面进行了简要论述。通过研究指出本区储层具有低孔、低渗的特点。在纵向上以直罗组储层相对最好 ,延安组次之 ,之后才是三叠系延长组。储集层普遍具有岩性细、成岩后生变化强烈的特点。由于储层低孔、低渗 ,因此 ,油层的压裂改造措施必不可少     

黄土丘陵沟壑区典型村域土地利用变化及对区域乡村转型发展的启示

深入开展乡村地域土地利用变化和聚落发展规律的研究对于探究乡村地域系统优化、推进城乡融合与乡村可持续发展具有重要意义。论文以延安市碾庄流域为例,基于ENVI和GIS等软件技术,结合Landsat卫星影像、马尔科夫链模型和实地调查,从土地利用转移与交换变化、建筑用地空间转移、社会响应等角度探讨了黄土丘陵沟壑区典型村域土地利用变化特征以及对区域乡村发展转型的影响。研究表明：① 在一系列生态工程措施作用下,碾庄流域生态覆被发生明显改观,主要表现为大量的坡耕地及稀疏生态用地转化为林地,其中,林地面积占比由32.34%(2009年)增加至50.88%(2018年);② 在社会经济发展和延安新城“边缘效应”的影响下,碾庄建设用地呈现向流域的东南和西南方向拓展的趋势,10 a间建设用地面积增加了近75%;③ 在人类活动的主导作用下,黄土丘陵沟壑区的乡村正在朝着生态化和集约化的方向转型发展。研究结果有望为深入理解黄土丘陵沟壑区乡村地域系统结构和优化提供新参考。     

Three Decades of Sea-Ice Variability in Jiaozhou Bay Revealed by Landsat Observations

In this study, we used Landsat images and meteorological data to examine the spatiotemporal distribution and variability of sea ice in Jiaozhou Bay(JZB) between 1986 and 2016. The results show that JZB is not always covered by sea ice in winter, but in some extreme cases, sea ice has covered more than one-third of the sea area of the bay. Sea ice in JZB has generally formed between January 1 and February 5, primarily along the coast, and gradually expanding to the central area of the bay. Both meteorological and artificial factors have played important roles in modulating the sea ice distribution. We found sea ice coverage to have been strongly correlated with the accumulated freezing-degree days nine days before the occurrence of sea ice(R2 = 0.767). North-northwest surface winds have dominated the freezing period of sea water in the JZB, and wind speed has exerted a more significant influence on the formation of sea ice when the sea ice coverage has been generally small. Additionally, artificial factors began to affect the expansion of sea ice in JZB since 2007. The construction of the Jiao-Zhou-Bay Bridge(JZBB) is believed to have retarded water flow and reduced the tidal prism, thereby leading to the formation of an ice bridge along the JZBB, which effectively prevents the southward expansion of sea ice.     

Mapping of moraine dammed glacial lakes and assessment of their areal changes in the central and eastern Himalayas using satellite data

The relatively rapid recession of glaciers in the Himalayas and formation of moraine dammed glacial lakes(MDGLs) in the recent past have increased the risk of glacier lake outburst floods(GLOF) in the countries of Nepal and Bhutan and in the mountainous territory of Sikkim in India. As a product of climate change and global warming, such a risk has not only raised the level of threats to the habitation and infrastructure of the region, but has also contributed to the worsening of the balance of the unique ecosystem that exists in this domain that sustains several of the highest mountain peaks of the world. This study attempts to present an up to date mapping of the MDGLs in the central and eastern Himalayan regions using remote sensing data, with an objective to analyse their surface area variations with time from 1990 through 2015, disaggregated over six episodes. The study also includes the evaluation for susceptibility of MDGLs to GLOF with the least criteria decision analysis(LCDA). Forty two major MDGLs, each having a lake surface area greater than 0.2 km2, that were identified in the Himalayan ranges of Nepal, Bhutan, and Sikkim, have been categorized according to their surface area expansion rates in space and time. The lakes have been identified as located within the elevation range of 3800 m and6800 m above mean sea level(a msl). With a total surface area of 37.9 km2, these MDGLs as a whole were observed to have expanded by an astonishing 43.6% in area over the 25 year period of this study. A factor is introduced to numerically sort the lakes in terms of their relative yearly expansion rates, based on their interpretation of their surface area extents from satellite imageries. Verification of predicted GLOF events in the past using this factor with the limited field data as reported in literature indicates that the present analysis may be considered a sufficiently reliable and rapid technique for assessing the potential bursting susceptibility of the MDGLs. The analysis also indicates that, as of now, there are eight MDGLs in the region which appear to be in highly vulnerable states and have high chances in causing potential GLOF events anytime in the recent future.     

Application of S-SEBI model for crop evapotranspiration using Landsat-8 data over parts of North India

Estimation and monitoring of crop evapotranspiration (ET_c) or consumptive water use over large-area holds the key to irrigation management plans and regional drought preparedness. The objective of this study was to estimate ET_c by applying the simplified-surface energy balance index (S-SEBI) model to Landsat-8 data for the 2014–2015 period in parts of North India. An average ET_c was estimated 2.72 and 2.47 in mm day^?1 with 0.22, 0.18 standard deviation and 0.11, 0.07 standard error for Kharif and Rabi crops, respectively. On validation part, a close relationship was observed between S-SEBI derived and scintillometer observed evaporative fraction with 0.85 correlation coefficient and 0.86 agreement index. The statistical analysis also endorses the results accuracy and reliability with 0.026 and 0.602, relative root-mean square errors and model efficiency for wheat crop, respectively. The study showed that normalized difference vegetation index and LST are closely related and serve as a proxy for qualitative representation of ET_c.