卷积神经网络及其在矿床找矿预测中的应用——以安徽省兆吉口铅锌矿床为例   总被引：1，自引：0，他引：1  

刘艳鹏  朱立新  周永章 《岩石学报》2018,34(11):3217-3224

大数据人工智能地质学刚刚起步,基于大数据智能算法的地质研究是非常有意义的探索性实验。利用大数据和机器学习解决矿产预测问题,有助于人们克服不能全面考虑地质变量的困难及评估当前模型在已有数据中的可靠性。元素地表分布特征量主要受原岩成分、成矿作用影响和地表过程的影响,它们携带某些指示矿体就位的信息,即矿体在地下空间就位时在地表的响应,且未在地表过程中消失。以往的地球化学勘查工作仅仅识别异常,但未能发现矿体在地表响应的成矿特征量。本文以安徽省兆吉口铅锌矿床为例,通过机器学习,利用卷积神经网络算法,不断挖掘元素Pb分布特征与矿体地下就位空间的耦合相关性。经过1000次训练后,可以得到准确率0. 93,损失率0. 28的卷积神经网络模型。这种神经网络模型就是矿体在地下就位时元素在地表分布的响应,可以用来进行矿产资源预测。应用该模型对未知区进行预测,结果显示第53号区域具有很大概率存在尚未发现的矿体。  相似文献   

月表构造与深部构造的关系     

奚镜伦  陈建平 《江苏地质》2018,42(3):481-494

地球和月球很可能是通过大撞击形成的。在行星地质学中,研究月球的地质-构造现象,对了解月球、地球乃至太阳系的形成与演化历史都有很大帮助。月球的构造分为深部构造与月表构造,寻找它们在分布或成因上的关系,可以为月球甚至地月系的起源和演化历史提供重要参考。利用LROC的宽视角影像数据以及LOLA数据提取解译月表构造,结合深大断裂进行观察分析,并对月球的撞击盆地进行统计,最后以静海地区为例分析构造分布特征,发现月球的质量瘤盆地中具有环状分布的月岭,外侧具有近环状分布的深大断裂,自前酒海纪至酒海纪,具备上述特征的质量瘤盆地占总撞击盆地的比例突然有一个很大的提升,且静海地区西部具有该构造分布特征。推测该特征与撞击、月海沉降等有关,且在酒海纪与雨海纪期间月球有较多的月海玄武岩分布,由此判断静海西部存在质量瘤,发生过撞击与月海沉降。  相似文献   

综合物探方法在广西妙皇隐伏多金属矿勘查中的应用     

刘星  杨秋访 《江苏地质》2018,42(4):668-674

妙皇多金属矿区位于来宾凹陷东缘与大瑶山隆起西侧交接部位,广西大瑶山及其西侧铅锌成矿带中部成矿条件优越,历年来开展过多种研究和找矿方法,但找矿效果不佳。通过研究妙皇铜铅锌银矿区的地质条件和成矿背景,运用综合物探方法,对区内部分地质问题及矿产特征进行了推断和预测。2012年,依据地质物探综合成果布置了ZK22701号验证孔,取得了突破性的进展。同时,依据物探成果推测了矿区成矿机理和成矿模式,在找矿方向和找矿潜力方面进行了分析探讨,对中深部找矿具有很好的指导意义。  相似文献   

Mapping fractional landscape soils and vegetation components from Hyperion satellite imagery using an unsupervised machine-learning workflow     

Michael J. Friedel  Massimo Buscema  Luiz Eduardo Vicente  Fabio Iwashita  Andréa Koga-Vicente 《International Journal of Digital Earth》2018,11(7):670-690

An unsupervised machine-learning workflow is proposed for estimating fractional landscape soils and vegetation components from remotely sensed hyperspectral imagery. The workflow is applied to EO-1 Hyperion satellite imagery collected near Ibirací, Minas Gerais, Brazil. The proposed workflow includes subset feature selection, learning, and estimation algorithms. Network training with landscape feature class realizations provide a hypersurface from which to estimate mixtures of soil (e.g. 0.5 exceedance for pixels: 75% clay-rich Nitisols, 15% iron-rich Latosols, and 1% quartz-rich Arenosols) and vegetation (e.g. 0.5 exceedance for pixels: 4% Aspen-like trees, 7% Blackberry-like trees, 0% live grass, and 2% dead grass). The process correctly maps forests and iron-rich Latosols as being coincident with existing drainages, and correctly classifies the clay-rich Nitisols and grasses on the intervening hills. These classifications are independently corroborated visually (Google Earth) and quantitatively (random soil samples and crossplots of field spectra). Some mapping challenges are the underestimation of forest fractions and overestimation of soil fractions where steep valley shadows exist, and the under representation of classified grass in some dry areas of the Hyperion image. These preliminary results provide impetus for future hyperspectral studies involving airborne and satellite sensors with higher signal-to-noise and smaller footprints.  相似文献   

Evaluation of effectiveness of three fuzzy systems and three texture extraction methods for building damage detection from post-event LiDAR data     

Milad Janalipour 《International Journal of Digital Earth》2018,11(12):1241-1268

Building damage maps after disasters can help us to better manage the rescue operations. Researchers have used Light Detection and Ranging (LiDAR) data for extracting the building damage maps. For producing building damage maps from LiDAR data in a rapid manner, it is necessary to understand the effectiveness of features and classifiers. However, there is no comprehensive study on the performance of features and classifiers in identifying damaged areas. In this study, the effectiveness of three texture extraction methods and three fuzzy systems for producing the building damage maps was investigated. In the proposed method, at first, a pre-processing stage was utilized to apply essential processes on post-event LiDAR data. Second, textural features were extracted from the pre-processed LiDAR data. Third, fuzzy inference systems were generated to make a relation between the extracted textural features of buildings and their damage extents. The proposed method was tested across three areas over the 2010 Haiti earthquake. Three building damage maps with overall accuracies of 75.0%, 78.1% and 61.4% were achieved. Based on outcomes, the fuzzy inference systems were stronger than random forest, bagging, boosting and support vector machine classifiers for detecting damaged buildings.  相似文献   

Supervised classification of electric power transmission line nominal voltage from high-resolution aerial imagery     

Erik H. Schmidt  Budhendra L. Bhaduri  Nicholas Nagle  Bruce A. Ralston 《地理信息系统科学与遥感》2018,55(6):860-879

For many researchers, government agencies, and emergency responders, access to the geospatial data of US electric power infrastructure is invaluable for analysis, planning, and disaster recovery. Historically, however, access to high quality geospatial energy data has been limited to few agencies because of commercial licenses restrictions, and those resources which are widely accessible have been of poor quality, particularly with respect to reliability. Recent efforts to develop a highly reliable and publicly accessible alternative to the existing datasets were met with numerous challenges – not the least of which was filling the gaps in power transmission line voltage ratings. To address the line voltage rating problem, we developed and tested a basic methodology that fuses knowledge and techniques from power systems, geography, and machine learning domains. Specifically, we identified predictors of nominal voltage that could be extracted from aerial imagery and developed a tree-based classifier to classify nominal line voltage ratings. Overall, we found that line support height, support span, and conductor spacing are the best predictors of voltage ratings, and that the classifier built with these predictors had a reliable predictive accuracy (that is, within one voltage class for four out of the five classes sampled). We applied our approach to a study area in Minnesota.  相似文献   

The effects of visual realism,spatial abilities,and competition on performance in map-based route learning in men     

Arzu Çöltekin  Rebecca Francelet  Kai-Florian Richter  John Thoresen  Sara Irina Fabrikant 《制图学和地理信息科学》2018,45(4):339-353

We report on how visual realism might influence map-based route learning performance in a controlled laboratory experiment with 104 male participants in a competitive context. Using animations of a dot moving through routes of interest, we find that participants recall the routes more accurately with abstract road maps than with more realistic satellite maps. We also find that, irrespective of visual realism, participants with higher spatial abilities (high-spatial participants) are more accurate in memorizing map-based routes than participants with lower spatial abilities (low-spatial participants). On the other hand, added visual realism limits high-spatial participants in their route recall speed, while it seems not to influence the recall speed of low-spatial participants. Competition affects participants’ overall confidence positively, but does not affect their route recall performance neither in terms of accuracy nor speed. With this study, we provide further empirical evidence demonstrating that it is important to choose the appropriate map type considering task characteristics and spatial abilities. While satellite maps might be perceived as more fun to use, or visually more attractive than road maps, they also require more cognitive resources for many map-based tasks, which is true even for high-spatial users.  相似文献   

山东淄博金岭杂岩体分布区深部富铁矿资源潜力及找矿方向     

张保涛  胡兆国  曹其琛  姜晓平  梅贞华  李忠平  杜利明  华北  赵磊  柳森 《地质学报》2021,95(5):1545-1560

深部找矿是目前研究和勘查的热点领域.金岭杂岩体侵入于古生代灰岩中,是燕山运动晚期的产物,与其有关的铁成矿作用是内生铁成矿典型事件之一,形成了金岭富铁矿集区.矿集区目前已发现铁矿体主要分布在-500 m以浅,矿山开采面临资源枯竭的严峻形势,深部找矿亟待突破.区内矿体按赋存介质及空间分布可划分为岩体/地层接触带式、假整合/层间裂隙式、岩体内捕虏体式三种型式.重、磁、电、地综合指示,其深部和外围依然具有优越的矽卡岩型富铁成矿条件,有利找矿深度可延伸至1.3 km,资源潜力大.通过可控源音频大地电磁测深、重磁反演技术对深部和外围成矿地质体的反映,优选出了研究区深部和外围的主要有利找矿区,分别建立了金岭杂岩体两侧矽卡岩型富铁矿地质地球物理综合找矿模型,以期为实现研究区深部和外围找矿发现及相似区域的找矿工作提供理论指导.  相似文献   

基于深反射地震剖面的沂沭断裂带岩石圈精细结构     

张尚坤  罗文强  于学峰  田京祥  唐璐璐  陈军  杨斌  杜圣贤  刘凤臣  仵康林 《地质学报》2021,95(11):3192-3204

为揭示沂沭断裂带深部结构及发生—发展过程,查清断裂切割深度及对岩石圈地幔的破坏,探讨沂沭断裂带的构造组合样式、运动方式、地壳稳定性及其对资源环境的约束作用,研究团队于2019年在沂沭断裂带南段沂南—莒县附近布设了一条长约60 km的深反射地震剖面,系统采集了沂沭断裂带和两侧地块的地震数据,对沂沭断裂带深部岩石圈精细结构进行了解剖.结果显示,该区岩石圈结构在横向上表现为以沂沭断裂带为界的块状结构特征,地壳厚度约30.8～39.5 km;莫霍面总体呈西浅东深态势,并被西倾的沂水—汤头断裂(F2)和昌邑—大店断裂(F4)错断,垂直落差达10.5 km.与浅部"两堑夹一垒"的构造组合样式不同的是,沂沭断裂带在深部剖面上表现为由沂水—汤头断裂(F2)和昌邑—大店断裂(F4)向上延伸与分叉散开的多条断裂组成"双枝状"构造组合样式.断裂带内被断层切割的界面反射波多呈向上的拱弧形,其构造形迹具有伸展、挤压和走滑并存的特征,推断这些界面为层间滑脱构造,它们指示了沂沭断裂带"多层滑移"构造运动方式.该断裂带不仅切穿了近地表、壳内地质界面,F2、F4断裂还向下切割莫霍面,深入岩石圈地幔,是深达地幔的深大断裂构造带,为地幔热物质的上涌提供了通道,对中生代的岩浆活动和内生成矿具有控制作用.地震剖面西端的铜井金矿成矿与沿F2断裂上侵的铜井杂岩体关系密切;剖面东端的火山机构保存完整,没有明显构造破坏痕迹,据此认为沂沭断裂带左行走滑主要发生在早白垩世青山期以前,其后水平滑移量应不大.从区域地质分布及地震反演结果看,昌邑—大店断裂(F4)明显将山东省分割为鲁西和鲁东两个地质构造单元,因此将其作为区域地质构造分界线是合理的.本项研究结果进一步加深了沂沭断裂带深、浅部结构的认识,为分析研究沂沭断裂带的深部过程和浅部构造响应及对资源环境的影响提供了资料约束.  相似文献   

阿尔金山两侧盐湖物质来源、成钾作用及其控制因素研究     

李建森  山发寿  张西营 《地质学报》2021,95(7):2205-2213

塔里木盆地东部的罗布泊盐湖和柴达木盆地西部的盐湖分别位于阿尔金山两侧,均产出有大量富钾卤水,在油气藏开采中还伴随产出富钾油田水.为探讨阿尔金山两侧盐类资源富集机制及其控制因素,综合分析了罗布泊盐湖、柴达木盆地西部盐湖以及油田水的水化学和氢氧同位素地球化学特征,发现:富钾卤水的形成除依靠地表汇入水体的蒸发浓缩作用外,罗布泊晶间水、柴达木晶间水和油田水氢氧同位素均可演化至δD=-30‰,δ18 O=7.5‰左右,可能是深部流体上涌补给的结果.同时,根据87 Sr/86 Sr值并结合δ11 B、3 He/4 He同位素特征确认了盐湖成矿与深部流体有关,且指示罗布泊盐湖更具深源特征.深部流体对于两侧盆地成盐富钾有关键性作用,罗布泊盐湖可能接受深部流体补给,柴达木盆地西部富钾盐湖卤水多数可接受油田水的补给,而少部分可能接受深部流体补给.  相似文献