Seismicity of the Hellenic subduction zone in the area of western and central Crete observed by temporary local seismic networks

Temporary local seismic networks were installed in western Crete, in central Crete, and on the island Gavdos south of western Crete, respectively, in order to image shallow seismically active zones of the Hellenic subduction zone.More than 4000 events in the magnitude range between −0.5 and 4.8 were detected and localized. The resulting three-dimensional hypocenter distribution allows the localization of seismically active zones in the area of western and central Crete from the Mediterranean Ridge to the Cretan Sea. Furthermore, a three-dimensional structural model of the studied region was compiled based on results of wide-angle seismics, surface wave analysis and receiver function studies. The comparison of the hypocenter distribution and the structure has allowed intraplate and interplate seismicity to be distinguished.High interplate seismicity along the interface between the subducting African lithosphere and the Aegean lithosphere was found south of western Crete where the interface is located at about 20 to 40 km depth. An offset between the southern border of the Aegean lithosphere and the southern border of active interplate seismicity is observed. In the area of Crete, the offset varies laterally along the Hellenic arc between about 50 and 70 km.A southwards dipping zone of high seismicity within the Aegean lithosphere is found south of central Crete in the region of the Ptolemy trench. It reaches from the interface between the plates at about 30 km depth towards the surface. In comparison, the Aegean lithosphere south of western Crete is seismically much less active including the region of the Ionian trench. Intraplate seismicity within the Aegean plate beneath Crete and north of Crete is confined to the upper about 20 km. Between 20 and 40 km depth beneath Crete, the Aegean lithosphere appears to be seismically inactive. In western Crete, the southern and western borders of this aseismic zone correlate strongly with the coastline of Crete.     

Displacement analysis of tunnel support in soft rock around a shallow highway tunnel at Golovec

Within the last 10 years Slovenia has been constructing its highway network. The Golovec tunnel, as a part of Slovenia's capital ring is thus one of the most important connections of Ljubljana to the east and to the north. It is a double tube three-lane tunnel in soft rock with small to medium overburden. Its construction, following NATM, caused huge problems to all parties involved. The tunnel support was well monitored during its construction, which gave the authors a good opportunity to analyse the results.The Golovec tunnel is constructed through one of few hills surrounding Ljubljana, of Carboniferous age, consisting of clastic rock: siltstone, claystone and sandstone. Golovec hill belongs to the first of two overthrusting zones from this area, so the rock is strongly faulted.Tunnel monitoring consisted of daily 3-D tunnel tube displacement measurements in 97 measuring sections, and of two measuring sections within the tunnel with more complex measuring equipment, to monitor stress changes and rock deformations around both tunnel tubes. Monitoring of the surface 3-D movements gave us the opportunity to study the influence of the tunnel construction on the surface above it. The tunnel, its geology, construction procedure and monitoring results are described in the first part of the paper.The second part consists of the interpretation of monitored results, with an emphasis on results concerning development and evolution of the excavation-damaged zone in the rock around the tunnel. Back-calculations, performed as a basis for the interpretation procedure, are also presented in this part. Calculations of the propagation of the tunnel destressed zone and stress-field around the tunnel, up to the surface, were performed by means of numerical model with the finite difference method. The evolution of tunnel displacements and their prediction was based on the use of Back Propagation Neural Networks, whose principles are presented in one chapter of this paper. Results showed that the most important, for the final settlement at the surface above the tunnel, was the time of installation and rigidity of the primary support. On the basis of the calculated final displacements, this support could easily be strengthened in a short time, when necessary.     

Deep learning for geometric and semantic tasks in photogrammetry and remote sensing

ABSTRACT

During the last few years, artificial intelligence based on deep learning, and particularly based on convolutional neural networks, has acted as a game changer in just about all tasks related to photogrammetry and remote sensing. Results have shown partly significant improvements in many projects all across the photogrammetric processing chain from image orientation to surface reconstruction, scene classification as well as change detection, object extraction and object tracking and recognition in image sequences. This paper summarizes the foundations of deep learning for photogrammetry and remote sensing before illustrating, by way of example, different projects being carried out at the Institute of Photogrammetry and GeoInformation, Leibniz University Hannover, in this exciting and fast moving field of research and development.     

国有大型企业网络变化及对区域经济发展的影响——以中国一拖为例

本文采用企业跟踪调查法,结合中国一拖的案例研究,对改革开放以来大型国有企业的网络变化进行了深入分析。同时探讨了企业网络变化对区域经济发展产生的影响。     

局部三维网平差系统

本文系统地介绍了局部三维网平差的有关理论和作者所设计的相应的软件，指出三维网具有广阔的应用前景．     

剖面二维裂隙网络渗流计算方法

本文针对剖面裂隙网络渗流问题,采用全区域不变网络分析方法,并引用初流量概念,化非线性分析为线性分析,成功的解决了岩体剖面上有自由面的裂隙网络渗流计算问题。     

论测量控制网的优化设计

本文回顾了测量控制网优化设计研究在我国的进展,分析了其中存在的一些问题,对今后的研究和应用提出了建议。     

控制网连接点坐标值粗差的可定位性研究

在原有测量控制网(称旧网)的基础上建立同级扩大网或低级加密网(称新网)时,新旧网之间的重合点(称连接点)坐标值粗差的检验是平差前的一个重要环节。本文将连接点坐标视为带协方差阵的观测值,采用数据探测法定位其粗差。借助于 Gauss-Markov模型下两个备选假设检验的理论,推导了连接点相关坐标观测值粗差可定位性基本公式,讨论了各类平面网中连接点坐标观测值粗差的可发现性和可区分性。     

基于神经网络模型的生物扰动碳酸盐岩储集层识别与孔隙度预测——以塔里木盆地塔河油田奥陶系生物扰动碳酸盐岩储集层为例

塔里木盆地塔河油田奥陶系生物扰动碳酸盐岩储集层非常发育,但利用常规测井数据识别生物扰动储集层发育段和准确预测孔隙度难度较大。本文在对研究区16口取芯井奥陶系岩芯上生物扰动区域扰动等级划分的基础上,通过岩性标定测井,优选常规测井参数,基于BP神经网络模型分别建立了适合研究区生物扰动碳酸盐岩储集层识别和孔隙度预测的模型,并对建立的模型进行了有效性检验。结果表明：① 选择自然电位、自然伽马、井径、深侧向电阻率、浅侧向电阻率、补偿中子和密度等常规测井数据作为生物扰动碳酸盐岩储集层识别模型输入层的参数值,生物扰动指数（Bioturbation Index, BI）作为输出结果;选取rprop、sigmoid symmetric和sigmoid stepwise函数分别作为训练函数、隐含层和输出层的激活函数,建立节点数为3、层数为3的神经网络识别模型,识别效果好,适用于研究区奥陶系生物扰动碳酸盐岩储集层的识别。② 选择自然电位、自然伽马、井径、声波、补偿中子和密度值等常规测井数据作为输入层的参数值,对应深度上岩芯柱塞孔隙度测试结果和利用孔隙度样品检验模型计算得出的孔隙度结果作为输出结果,选取incremental、gaussian和sigmoid分别作为训练函数、隐含层和输出层的激活函数,建立节点数为4,层数为3的生物扰动碳酸盐岩储集层孔隙度预测模型,预测效果良好,适用于研究区奥陶系生物扰动储集层孔隙度的预测。该研究对定量表征研究区生物扰动储层特性、储量估算、油藏描述和储层地质建模等具有重要的借鉴意义。