广西合浦盆地干热岩资源成热条件及潜力评价     

康志强  张起钻  管彦武  冯波  袁金福  孙明行  刘德民  王新宇  杨志强  陆济璞  张勤军  冯民豪 《吉林大学学报(地球科学版)》2020,50(4):1151-1160

为了对广西合浦盆地干热岩资源成热条件及其潜力进行评价，利用广西航磁勘查数据，采用Parker-Oldenburg法反演计算了居里面深度。在此基础上进行大地热流密度值和不同埋深地温计算，发现计算结果与现有测温资料吻合，合浦盆地内西场凹陷和常乐凹陷具有干热岩资源成生条件。结合合浦盆地内基础地质调查资料和油气钻孔资料，分析了合浦盆地干热岩资源的储层和盖层条件。初步圈出2个位于西场凹陷和常乐凹陷的干热岩勘查靶区C1和C2，面积分别为167.10和72.90 km²，干热岩资源量分别为182.48×10¹⁵、77.59×10¹⁵ J。按20%的采收率，合浦盆地干热岩资源量可开采量为52.01×10¹⁵ J，折合标准煤177.48×10⁴ t，占2018年广西全区能源生产总量3 756.69×10⁴ t标准煤的4.72%。在资源量评价基础上，可优先考虑位于合浦盆地西场凹陷的C1靶区开展进一步的勘探工作。  相似文献   

福建省复杂地形下旬平均气温分布式模拟     

李威鹏  邱新法  曾燕  施国萍  徐金勤  王丹丹 《热带地理》2019,39(2):229-236

为建立高时空分辨率的福建省复杂地形下气温栅格数据集，利用福建省及其周边33个常规气象站观测资料，基于数字高程模型（DEM）数据，综合考虑海拔、太阳总辐射、地表长波有效辐射对旬平均气温的影响，模拟了福建省复杂地形下旬均温的空间分布。结果表明：1）常规站验证结果显示：各旬气温绝对误差平均值（MAE）最小为0.46℃，最大为2.3℃，全年平均为0.87℃；加密站验证结果显示，MAE最大为2.3℃，最小0.5℃，全年平均为0.96℃。2）模拟结果能反映旬均温的宏观分布规律与局地细节特征。宏观范围内，旬均温受纬度影响较大，由北至南气温逐渐升高，沿海地区旬均温整体高于内陆，山区旬均温明显较低；局地范围内，各坡向上气温差异显著，海拔越高、坡度越大，差异越明显；地形因子对旬平均温的影响具有季节差异，具体表现为冬季时地形因子对旬均温的影响最大，秋季次之，春夏季节中地形因子对旬均温的影响最弱。  相似文献   

临震前地壳变形不动点现象与机制研究     

牛安福  张凌空  章静  李媛  赵静  闫伟  岳冲  苑争一 《大地测量与地球动力学》2020,40(1):1-6

在综合分析国内外地形变前兆研究现状的基础上,结合汶川8.0级地震前GPS、应变、重力等研究结果,提出临震前震源区域可能出现变形不动点现象。地壳变形过程中的不动点现象是临震前区域应力场进入临界状态的重要标志,是地震潜在危险区域划定的重要依据。借助不动点理论,给出汶川地震前变形不动点集合的演化,结合大区域地震活动空区与远场显著形变异常分布,探讨变形不动点现象发生的动力学背景,验证了汶川地震前地壳变形的不动点现象是大区域应力场有序运动的结果。  相似文献   

基于DEA-TOBIT模型的我国港口业 上市公司经营效率研究          下载免费PDF全文

郭鹏  温艳萍 《海洋开发与管理》2019,36(1):107-113

文章利用DEA-TOBIT两阶段法,对我国17家港口业上市公司2011—2016年经营效率及影响因素进行了测算和分析,并运用Malmquist指数对我国港口业上市公司的经营效率变化进行动态分析。研究结果表明:从静态效率分析,17家港口上市公司综合效率值相对较高,但维持在产出不变的情况下,港口公司投入仍有相对的节能空间;从动态效率上看,在研究期内17家港口上市公司的全要素生产率总体呈下降趋势,技术水平下降和规模效率的降低是造成全要素生产率降低的主要原因;从效率影响因素研究来看,总资产周转率、资产收益率、股权集中度和上市时间与港口经营效率呈正相关,企业的资产负债率对港口经营效率呈负向影响,企业的规模大小对港口经营效率的影响不明显。最后,根据实证结果,提出了科学合理的融资渠道组合,提高港口企业资产周转率;不断提升企业自身管理水平,科学控制企业规模;积极把握时代发展需求,加大企业技术创新,实现港口创新型驱动发展;大力建设港口组合,合作共享,协调发展等对策建议。  相似文献   

Inference of in situ stress from thermoporoelastic borehole breakouts based on artificial neural network     

Hua Zhang  Shunde Yin 《国际地质力学数值与分析法杂志》2019,43(16):2493-2511

The determination of in situ stresses is very important in petroleum engineering. Hydraulic fracturing is a widely accepted technique for the determination of in situ stresses nowadays. Unfortunately, the hydraulic fracturing test is time-consuming and expensive. Taking advantage of the shape of borehole breakouts measured from widely available caliper and image logs to determine in situ stress in petroleum engineering is highly attractive. By finite element modeling of borehole breakouts considering thermoporoelasticity, the authors simulate the process of borehole breakouts in terms of initiation, development, and stabilization under Mogi-Coulomb criterion and end up with the shape of borehole breakouts. Artificial neural network provides such a tool to establish the relationship between in situ stress and shape of borehole breakouts, which can be used to determine in situ stress based on different shape of borehole breakouts by inverse analysis. In this paper, two steps are taken to determine in situ stress by inverse analysis. First, sets of finite element modeling provide sets of data on in situ stress and borehole breakout measures considering the influence of drilling fluid temperature and pore pressure, which will be used to train an artificial neural network that can eventually represent the relationship between the in situ stress and borehole breakout measures. Second, for a given measure of borehole breakouts in a certain drilling fluid temperature, the trained artificial neural network will be used to predict the corresponding in situ stress. Results of numerical experiments show that the inverse analysis based on finite element modeling of borehole breakouts and artificial neural network is a promising method to determine in situ stress.  相似文献   

Multi-band Solar Full-disk Extreme Ultraviolet Imager     

PENG Ji-long  FENG Tao-jun  SHI En-tao  LI Lin  YU Qian  ZHANG Kai  NIE Xiang-yu  MA Zi-liang 《Chinese Astronomy and Astrophysics》2019,43(3):444-456

Solar Extreme Ultraviolet (EUV) imaging observation is an important measure for the researches of solar activities and coronal plasma physics. But the traditional EUV imager and spectrograph can hardly achieve simultaneously the high spectral resolution and wide field-of-view of solar imaging. This paper has designed a new type of solar EUV multi-band imager, by adopting a kind of slitless grating and grazing incidence structure, it can realize the solar full-disk imaging of high spectral and spatial resolution. The field-of-view of the imager can be as broad as 47′. The spectral resolution is 2×10^?3nm per pixel, and the spatial resolution is 1.4′ per pixel. The temporal resolution of the solar full-disk is better than 60 s. The analysis of the solar full-disk spectral image and system response shows that the imager can observe the morphological evolutions of various solar activities, and can provide more comprehensive data for the researches of solar physics and space weather forecast.  相似文献   

基于广义回归神经网络的行星际/太阳风参数和地磁指数的紫外极光强度建模          下载免费PDF全文

胡泽骏  韩冰  连慧芳 《地球物理学报》2020,63(5):1738-1750

极光卵极光强度的空间分布是太阳风-磁层-电离层能量耦合过程的重要表现,并且随着空间环境参数和地磁指数的变化而变化,是空间天气的重要指示器.建立合适的极光强度模型对亚暴的预测以及磁层动力学的研究具有重要意义.本文基于Polar卫星的紫外极光成像仪(Ultraviolet Imager,UVI)数据,采用两种不同的极光强度表征方法,即曲线拟合方法(从UVI图像数据中提取极光强度沿磁余纬方向上的曲线特征,Curve Feature along the Magnetic Co-latitude Direction of the Auroral Intensity,CFMCD_AI)和网格化方法(从UVI图像数据中提取极光强度的网格化特征,Gridding Feature of the Auroral Intensity,GF_AI),来构造极区极光强度特征数据库.然后,利用该数据库,采用广义回归神经网络(Generalized Regression Neural Network,GRNN)构建了以行星际/太阳风参数(行星际磁场三分量、太阳风速度和密度)和地磁指数(AE指数)为输入参数的两种极光强度预测模型(GRNN_CFMCD_AI模型和GRNN_GF_AI模型).利用图像质量评价指数结构相似度(structure similarity,SSIM)作为极光强度模型预测结果和对应的UVI图像的相似性评价标准(完全相似为1,不相似为0,一般认为SSIM大于0.5是具有较好的相似性),对两种极光强度模型进行了性能评价.结果显示,GRNN_GF_AI模型预测结果对应的SSIM值范围为0.36～0.77,均值为0.54,性能优于GRNN_CFMCD_AI模型的.  相似文献   

Dating of rockfall damage in trees yields insights into meteorological triggers of process activity in the French Alps     

R. Mainieri  C. Corona  J. Chartoire  N. Eckert  J. Lopez-Saez  M. Stoffel  F. Bourrier 《地球表面变化过程与地形》2020,45(10):2235-2250

Rockfall release is a rather unpredictable process. As a result, the occurrence of rockfall often threatens humans and (infra)structures. The assessment of potential drivers of rockfall activity therefore remains a major challenge, even if the relative influence of rainfall, snowmelt, or freeze–thaw cycles has long been identified in short-term monitoring projects. In the absence of longer-term assessments of rockfall triggers and possible changes thereof, our knowledge of rockfall dynamics remains still lacunary as a result of the persisting scarcity of exhaustive and precise rockfall databases. Over the last decades, several studies have employed growth disturbances (GDs) in tree-ring series to reconstruct rockfall activity. Paradoxically, these series were only rarely compared to meteorological records. In this study, we capitalize on the homogeneity of a centennial-old reforestation plot to develop two reconstructions – R1 including only growth suppressions, and R2 based on injuries – with limited biases related to decreasing sample size and changes in exposed diameters back in time. By doing so, our study also and quite clearly highlights the large potential that protection forests have in terms of yielding reliable, multidecadal rockfall reconstructions. From a methodological perspective, we find no synchronicity between R1 and R2, as well as an absence of meteorological controls on rockfall processes in R1. This observation pleads for a careful selection of GDs in future reconstructions. In terms of process dynamics, we demonstrate that summer intense rainfall events (>10 mm day⁻¹) are the main drivers for rockfall activity at our study site. Despite the stringency of our detection procedure, correlations between rockfall activity and meteorological variables remain comparable to those reported in previous studies, as a result of the complexity and multiplicity of triggering factors. We therefore call for a more systematic coupling of tree-ring analysis with rockfall and microclimatic monitoring in future studies. © 2020 John Wiley & Sons, Ltd.  相似文献   

Water quality monitoring at a virtual watershed monitoring station using a modified deep extreme learning machine     

Jian Jin  Lei Li  Huan Xu  Guang Lin 《水文科学杂志》2020,65(3):415-426

ABSTRACT

A new deep extreme learning machine (ELM) model is developed to predict water temperature and conductivity at a virtual monitoring station. Based on previous research, a modified ELM auto-encoder is developed to extract more robust invariance among the water quality data. A weighted ELM that takes seasonal variation as the basis of weighting is used to predict the actual value of water quality parameters at sites which only have historical data and no longer generate new data. The performance of the proposed model is validated against the monthly data from eight monitoring stations on the Zengwen River, Taiwan (2002–2017). Based on root mean square error, mean absolute error, mean absolute percentage error and correlation coefficient, the experimental results show that the new model is better than the other classical spatial interpolation methods.  相似文献   

具有低频超宽衰减域的部分埋入式表面波屏障     

秦凯强  刘泽  于桂兰 《地震工程与工程振动》2020,(2):187-194

针对低频Rayleigh表面波,设计了部分埋入式工字形截面周期波屏障。利用有限元方法计算了结构的频散曲线,分析了带隙的形成机理,讨论了屏障埋入土体深度和截面参数对带隙的影响,在此基础上设计了具有低频超宽衰减域的梯度及分段梯度波屏障并计算了其传输谱。结果表明:周期波屏障存在较宽带隙,板埋入深度和端部尺寸是影响带隙的关键参数,通过参数调节可实现不同频段Rayleigh波的调控。工字形变截面波屏障比等截面具有更优越的隔震性能且节省材料。梯度及分段梯度波屏障显著拓宽了衰减域的频率范围,对1.5~20 Hz范围内的Rayleigh表面波实现了全覆盖,用小尺寸控制了大波长。  相似文献