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1.
We propose to adopt a deep learning based framework using generative adversarial networks for ground-roll attenuation in land seismic data. Accounting for the non-stationary properties of seismic data and the associated ground-roll noise, we create training labels using local time–frequency transform and regularized non-stationary regression. The basic idea is to train the network using a few shot gathers such that the network can learn the weights associated with noise attenuation for the training shot gathers. We then apply the learned weights to test ground-roll attenuation on shot gathers, that are not a part of training input to obtain the desired signal. This approach gives results similar to local time–frequency transform and regularized non-stationary regression but at a significantly reduced computational cost. The proposed approach automates the ground-roll attenuation process without requiring any manual input in picking the parameters for each shot gather other than in the training data. Tests on field-data examples verify the effectiveness of the proposed approach. 相似文献
2.
以云南省红河州元阳县哈尼梯田核心区域2个典型的旅游村寨(大鱼塘村和普高老寨)为例,对两村寨利益相关者从网络凝聚性、网络互惠性、网络核心边缘、网络传递性、网络经纪人等5个方面展开关系数据分析,结果显示:1)大鱼塘村压力集团内部、压力集团与社区、企业与政府之间的利益关联性和联系的紧密性不足;2)两村当地政府和压力集团与社区之间的互惠性低于整体平均互惠性;3)两村利益网络中边缘结构较核心结构更加明显,这导致了利益关系的不平衡;4)两村当地政府利益集团传递性相对较低,当地社区传递性最高;5)两村中利益集团间缺少部分协调人、守门人、代理人、联络人等角色。最后提出相应建议:1)提升哈尼梯田利益关系由弱利益关系转变为强利益关系,改变利益集团间核心边缘利益关系格局;2)进一步加强各利益集团内部及之间的关联性;3)加强以企业和政府机构为顶点的组间利益传递,让利益流动逐步打破哈尼梯田利益集团之间的核心边缘关系结构;4)重点加强社区在利益关系网络中的参与机会与权力,对社区进行增权;5)利益集团内部要重点培育协调人和顾问角色,利益集团之间要重点培育企业与政府、社区、压力集团之间的守门人、代理人和联络人角色,以及社区与政府和企业之间的守门人、代理人角色。 相似文献
3.
由于观测手段有限,目前对月球内部结构的认识还存在很大的不确定性,至今仍没有一个被广泛认可的内部结构模型,且现有对月球内部结构模型的研究几乎很少关注观测值对观测精度的影响.本研究采用混合密度神经网络方法得到了月球内部结构模型的后验概率密度分布,获得了平均月球内部结构模型(Mean模型)、最大后验概率对应的月球内部结构模型(MAP模型)以及满足1-σ准则的月球内部结构模型(1-σ模型),其中MAP模型即为本文给出的最优化月球内部结构模型.此外,研究结果表明月球低速区S波波速低于月幔S波波速,因此本文结果支持月幔底部存在一个低速区的观点.不同观测值观测精度对模型影响的研究结果表明,勒夫数k2存在一个约为0.0220的下边界,且其观测精度对月球内部结构模型的影响显著大于平均密度和平均转动惯量. 相似文献
4.
In the water flooding of mixed-wet porous media, oil may drain down to relatively low residual oil saturations (Sor). Various studies have indicated that such low saturations can only be reached when oil layers in pore corners are included in the pore-scale modelling. These processes within a macroscopic porous medium can be modelled at the pore-scale by incorporating the fundamental physics of capillary dominated displacement within idealised pore network models. Recently, the authors have developed thermodynamic criteria for oil layer existence in pores with non-uniform wettability which takes as input geometrically and topologically representative networks, to calculate realistic Sor values for mixed-wet and oil-wet sandstones [16, 21]. This previous work is developed in this paper to include (i) the visualisation of the 3D structure of this residual oil, and (ii) a statistical analysis of this “residual/remaining” oil. Both the visualisation and the statistical analysis are done under a wide range of wettability conditions, which is reported for the first time in this paper.The structure of residual oil for strongly water wet systems is well known (where residual = remaining oil) and our model agrees with this but this structure changes radically for mixed wet systems (where residual ≠ remaining) and this has not yet been visualised experimentally. We find that for more water-wet systems high final residual oil saturations are reached at relatively small amounts of water injected and this oil is present in the pores as bulk oil. On the other hand, for more oil-wet systems we find a slow decrease of the amount of remaining oil with increasing amounts of injected water. During the process, the remaining connectivity of the oil phase is increasingly provided by oil layers only, hence the slow drainage. The final residual oil saturation, only reached in the theoretical limit of an infinite amount of injected water, is almost entirely contained in large number of (relatively low volume) oil layers, which are present in pores of most radius sizes. 相似文献
5.
利用1951-2013年广西90个气象观测站气温资料、国家气候中心74项指数和美国National Oceanic and Atmospheric Administration(NOAA)的Climate Prediction Center(CPC)60项指数以及海温和陆地雪盖资料、美国国家冰雪研究中心(NSIDC)的两极海冰资料,使用相关分析方法得到广西寒露风开始期气候影响因子,利用逐步回归和神经网络方法进行寒露风开始期的预测。结果表明:寒露风开始期与前一年9-10月北极海冰面积、当年3月南极海冰面积、前一年6月欧亚雪盖、当年5月北美雪盖、北半球雪盖的相关显著。与前一年9月北半球极涡面积指数、前一年10月亚洲区极涡面积指数、前一年3月热带印度洋海温偶极子等指数相关显著。粒子群-神经网络方法预测误差低于逐步回归方法,预报能力有明显提高。 相似文献
6.
Journal of Geographical Sciences - The Interconnected River System Network (IRSN) plays a crucial role in water resource allocation, water ecological restoration and water quality improvement. It... 相似文献
7.
Ye Hong 《International journal of geographical information science》2019,33(8):1569-1587
An in-depth analysis of the urban road network structure plays an essential role in understanding the distribution of urban functional area. To concentrate topologically densely connected road segments, communities of urban roads provide a new perspective to study the structure of the network. In this study, based on OpenStreetMap (OSM) roads and points-of-interest (POI) data, we employ the Infomap community detection algorithm to identify the hierarchical community in city roads and explore the shaping role roads play in urban space and their relation with the distribution of urban functional areas. The results demonstrate that the distribution of communities at different levels in Guangzhou, China reflects the urban spatial relation between the suburbs and urban centers and within urban centers. Moreover, the study explored the functional area characteristics at the community scale and identified the distribution of various functional areas. Owing to the structure information contained in the identification process, the detected community can be used as a basic unit in other urban studies. In general, with the community-based network, this study proposes a novel method of combining city roads with urban space and functional zones, providing necessary data support and academic guidance for government and urban planners. 相似文献
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10.
基于神经网络的页岩微纳米孔隙微结构分析的正则化和最优化方法 总被引:1,自引:1,他引:0
页岩气成藏机理与页岩内部孔隙结构紧密相关,对页岩孔隙结构的研究成为页岩气勘探开发技术中至关重要的一环。页岩内部不同结构体组分对X-射线的吸收能谱不一样,这样就导致观测数据是由不同页岩组分衰减不同波段的X-射线构成的。经过对CT图像分割,能够获得页岩微孔结构的图像,尤其是获得有机质中孔隙类别、形状、尺寸、空间分布、连通特性。本文利用同步辐射X射线扫描重构的页岩CT数据,研究并设计基于多能CT图像的神经网络图像分割技术和算法,以期得到页岩体三维结构特征及空间分布,可以为建立有机质种类和无机矿物组成与微纳孔隙特征的联系以及最终实现页岩气的资源储量评估和勘探开发提供技术支持。 相似文献