断陷盆地缓坡带河流沉积砂体定量表征及控制因素分析:以霸县凹陷文安斜坡东营组三段为例

断陷湖盆缓坡河流成因砂体是重要的油气储集单元.根据岩心观察、钻井岩/电特征并结合地震沉积学方法,分析断陷湖盆缓坡河流沉积体系和砂体时空分布特征,能为油气精细勘探提供可靠的依据.研究表明,霸县凹陷文安斜坡中部东营组三段周期性地发育4条呈NE-SW辫-曲复合型河流沉积,由河道沉积、砂坝沉积和泛滥平原沉积3种亚相以及辫状河道...     

2022年1月8日门源6.9级地震山东地震台网测定面波震级对比分析

通过对山东地震台网记录的2022年1月8日门源M_S 6.9地震原始波形进行分析,测算出88个测震台站的M_S、M_S7、M₍S(BB))等3种面波震级,并与中国地震台网速报和青海区域地震台网编目测定结果进行对比分析。结果表明：①山东地震台网测定门源M_S 6.9地震的面波震级M_S、M_S7、M₍S(BB))分别为7.20、7.16、6.96;②M₍S(BB))震级的测定方法简单,不同台站之间的偏差较小,一致性较好,适合在地震台网的地震速报中使用。这与震级国家标准GB 17740—2017的规定相一致。     

WP和NAO对中国东南部冬季温度的协同影响

利用NCEP/NCAR和ERA-Interim再分析资料,通过多元线性回归等分析方法,研究了西太平洋遥相关型(Western Pacific teleconnection,WP)和北大西洋涛动(North Atlantic Oscillation,NAO)的不同配置对中国东南部冬季气温的影响.结果 表明:WP正位相年,...     

地震安评中地震活动性的统计区域与b值

本文讨论我国现行地震安全性评价中,地震活动性研究统计区域的选择及b值计算中存在的问题,提出不一定以地震区带作为统计区域的建议。文中同时指出,累计b值的正确概念应该是无震级上限累计b值,应采用迭代回归计算。文中用实际例子说明作者的建议。     

Effects of periodically varying codes on separation of multisource blended data

Current exploration needs are satisfied by multisource technology,which offers low cost,high efficiency,and high precision.The delay time,which determines the s...     

基于显著性图像与纹理特征的遥感影像云检测

遥感影像云检测是遥感影像处理中非常关键的环节,准确识别影像含云区域能够提升影像的利用价值.根据遥感影像的成像特点,将阈值法和纹理特征结合实现云和下垫面的分割.首先将影像从RGB(red-green-blue)空间转化为HSI(hue-saturation-intensity)空间,进而构建影像的显著性图像,利用Otsu...     

山东省菏泽凸起地热田岩溶地热水水化学水平演化特征

在前人研究成果的基础上,选择A-A'和B-B'两条路径,采用Piper三线图解、Schoeller图解、Na-K-Mg平衡图解、饱和指数计算评价等方法,研究山东菏泽凸起地热田地热水沿路径上的循环演化特征.结果表明:沿A-A'、B-B'剖面岩溶冷水→岩溶热水,水化学类型由SO4?HCO3-Ca?Mg?Na或SO4?HCO...     

初夏孟加拉湾低压与云南雨季开始期

通过对46年(1961—2006年)的初夏(4月21日~5月31日)孟加拉湾低压的研究,发现影响云南雨季开始期的初夏孟加拉湾低压系统源地大致位于9°~12°N,88°~91°E之间,较强的低压系统从源地移出后分别沿着两条路径影响云南,这两条路径对应着不同强弱的南亚高压环流。初夏孟加拉湾低压出现频率与云南雨季开始早晚有明显的负相关关系。前期3月中南半岛附近海域的对流强(弱),则有(不)利于初夏孟加拉湾地区产生低压系统。初夏孟加拉湾低压与前期南印度洋海温呈负相关,当南印度洋海温下降(上升)时,有(不)利于孟加拉湾地区对流加强、低压系统生成。     

新疆伊吾县马依当地区二叠纪地层的发现及其意义

在新疆伊吾煤矿一带1:5万区域地质矿产调查中,首次在原定石炭系上统妖魔梁组中发现大量透镜状钙质结核,并具明显的陆相冲积扇沉积特征;通过该地层的大量孢粉鉴定属为二叠世晚期,故将原石炭系上统妖魔梁组更名改为库莱组。其时代定为晚二叠世。并初步探讨了它的地质意义。     

Understanding the dynamical-microphysical-electrical processes associated with severe thunderstorms over the Beijing metropolitan region

The Dynamical-microphysical-electrical Processes in Severe Thunderstorms and Lightning Hazards(STORM973)project conducted coordinated comprehensive field observations of thunderstorms in the Beijing metropolitan region(BMR)during the warm season from 2014 to 2018.The aim of the project was to understand how dynamical,microphysical and electrical processes interact in severe thunderstorms in the BMR,and how to assimilate lightning data in numerical weather prediction models to improve severe thunderstorm forecasts.The platforms used in the field campaign included the Beijing Lightning Network(BLNET,consisting of 16 stations),2 X-band dual linear polarimetric Doppler radars,and 4 laser raindrop spectrometers.The collaboration also made use of the China Meteorological Administration’s mesoscale meteorological observation network in the Beijing-Tianjin-Hebei region.Although diverse thunderstorm types were documented,it was found that squall lines and multicell storms were the two major categories of severe thunderstorms with frequent lightning activity and extreme rainfall or unexpected local short-duration heavy rainfall resulting in inundations in the central urban area,influenced by the terrain and environmental conditions.The flash density maximums were found in eastern Changping District,central and eastern Shunyi District,and the central urban area of Beijing,suggesting that the urban heat island effect has a crucial role in the intensification of thunderstorms over Beijing.In addition,the flash rate associated with super thunderstorms can reach hundreds of flashes per minute in the central city regions.The super(5%of the total),strong(35%),and weak(60%)thunderstorms contributed about 37%,56%,and 7%to the total flashes in the BMR,respectively.Owing to the close connection between lightning activity and the thermodynamic and microphysical characteristics of the thunderstorms,the lightning flash rate can be used as an indicator of severe weather events,such as hail and short-duration heavy rainfall.Lightning data can also be assimilated into numerical weather prediction models to help improve the forecasting of severe convection and precipitation at the cloud-resolved scale,through adjusting or correcting the thermodynamic and microphysical parameters of the model.