http://www.sciencedirect.com/science/article/pii/S1674987115000882

A detailed vibrational Raman-IR spectroscopic and diffractional analyses have been performed on basalts from two locations from Tenerife Island:(1) the Arenas Negras volcano which belongs to the historical eruption not showing visible alteration and(2) Pillow Lavas zone from Anaga Massif which shows a clearly fluid-rock interaction caused by submarine alteration.These places have been extensively studied due to its similarity with the surface of Mars.The analysis is based on the mineral detection of selected samples by a Micro-Raman study of the materials.The complementary techniques have confirmed the mineralogy detected by the Raman measurement.The results show a volcanic environment behavior with primary phases like olivine,pyroxene,and feldspar/plagioclase.Moreover,the presence of accessory minerals or secondary mineralization like phosphate,iron oxides,zeolite or carbonates shows the alteration processes on each outcrop.The variation in the crystallinity and amorphous phases is related to fluid-rock interaction caused by hydrothermal episodes and external weathering processes,which shows several analogies with the ancient volcanic activity from Mars.     

The Gondwana Orogeny in northern North Patagonian Massif:Evidences from the Caita Có granite,La Se?a and Pangaré mylonites,Argentina

Structural analyses in the northern part of the North Patagonia Massif,in the foliated Caita Co granite and in La Sena and Pangare mylonites,indicate that the pluton was intruded as a sheet-like body into an opening pull-apart structure during the Gondwana Orogeny.Geochronological studies in the massif indicate a first,lower to middle Permian stage of regional deformation,related to movements during indentation tectonics,with emplacement of foliated granites in the western and central areas of the North Patagonian Massif.Between the upper Permian and lower Triassic,evidence indicates emplacement of undeformed granitic bodies in the central part of the North Patagonian Massif.A second pulse of deformation between the middle and upper Triassic is related to the emplacement of the Caita Co granite,the development of mylonitic belts,and the opening of the Los Menucos Basin.During this pulse of deformation,compression direction was from the eastern quadrant.     

基于GF 1光谱数据的青藏地区冰川资源现状遥感调查

以2014—2015年的GF 1为主、少量OLI影像为基础,参考第二次中国冰川目录等文献资料,修编完成青海省和西藏自治区两省区的现代冰川编目,查明青藏两省区目前共有冰川24 796条,总面积约2624×104 km2,约占青藏两省区区域面积的137%,冰川储量为2027×103~2121×103 km3。调查区冰川数量以面积<10 km2、冰川面积介于10~100 km2之间的冰川为主,其中面积<10 km2的冰川有19 983条,占总数量的8059%,面积介于10~100 km2之间的冰川面积为11 96240 km2,占总面积的4559%;面积最大的中锋冰川的面积达23737 km2。调查区内的山系(高原)均有冰川分布,念青唐古拉山冰川数量最多,其次是喜马拉雅山和冈底斯山,这3座山系冰川数量占调查区内冰川总数量的6333%;念青唐古拉山、喜马拉雅山和昆仑山的冰川面积和冰储量位列前3位,其冰川面积和冰储量分别占总数的6809%和7344%;然而昆仑山和羌塘高原的单条冰川的平均面积大于念青唐古拉山和喜马拉雅山的平均面积。从冰川海拔分布来看,海拔5 000~6 500 m之间是冰川集中发育区域,约占调查区冰川数量和冰川总面积的85%以上。调查区的冰川在各流域的分布差异显著,恒河流域是冰川分布数量最多、面积最大的一级外流区,其数量占冰川总量的47%以上,面积占总面积的52%以上;青藏高原内陆流域的冰川数量、面积次之,其冰川数量占总数量的21%,面积占总面积的24%以上,并且内流区单条冰川的平均面积略大于外流区的平均面积。总体上,西藏的冰川数量、面积和冰储量分别占西藏和青海两省区的8492%、8492%、8668%,单条冰川的平均面积两省区相近。     

Palaeoenvironmental Reconstruction of the Early to Middle Miocene Sequence in West Central Sinai,Egypt, as Revealed from Fossil Diatoms

A detailed analysis of the diatoms from the sedimentary sequence exposed in Abu Qada basin, west central Sinai, was used to determine the palaeoenvironmental changes during the Lower to Middle Miocene. A total of 85 diatom species and varieties belonging to 37 genera were identified from 154 samples collected throughout the stratigraphic succession. The lithological characters of the studied samples varied between sandstone, silty interbeds, sandy shales, shales, and terminated with anhydrite and limestones. These rock units are included in two lithostratigraphic formations (Rudies and Kareem), which are separated by a marked unconformity. The distribution and preservation of fossil diatoms in the sedimentary record are examined with the aim of outlining the temporal and spatial variation in the composition of the diatom assemblages, in order to estimate the changes in depositional environments during the Lower to Middle Miocene. The distributional pattern of the recorded diatom taxa distinguished four diatom eco-zones. The environment of each eco-zone is deduced and a proposed paleobathymetric change and depositional history of the Miocene sediments in the studied area are given.     

Is Ziarat a Potential Site for Conventional or Unconventional Energy Resources?

A structural interpretation of the Ziarat block in the Balochistan region (a part of the Suleiman Fold and Thrust Belt) has been carried out using seismic and seismological data. Seismic data consists of nine 2.5D pre‐stack migrated seismic lines, whereas the seismological data covers the Fault Plane Solution and source parameters. Structural interpretation describes two broad fault sets of fore and back thrusts in the study area that have resulted in the development of pop‐up structures, accountable for the structural traps and seismicity pattern in terms of seismic hazard. Seismic interpretation includes time and depth contour maps of the Dungan Formation and Ranikot group, while seismological interpretation includes Fault Plane Solution, that is correlated with a geological and structural map of the area for the interpretation of the nature of the subsurface faults. Principal stresses are also estimated for the Ranikot group and Dungan Formation. In order to calculate anisotropic elastic properties, the parameters of the rock strength of the formations are first determined from seismic data, along with the dominant stresses (vertical, minimum horizontal, and maximum horizontal). The differential ratio of the maximum and minimum horizontal stresses is obtained to indicate optimal zones for hydraulic fracturing, and to assess the potential for geothermal energy reservoir prospect generation. The stress maps indicate high values towards the deeper part of the horizon, and low towards the shallower part, attributed to the lithological and structural variation in the area. Outcomes of structural interpretation indicate a good correlation of structure and tectonics from both seismological and seismic methods.     

喜马拉雅山地区重大地质灾害遥感调查研究

正科学出版社内容介绍本书介绍了西起阿里地区札达县、葛尔县,东侧以雅鲁藏布江为界,北界为雅鲁藏布江大断裂,南至国界的广大喜马拉雅山地区的重大地质灾害遥感调查成果。从遥感信息源、图像处理、地质灾害分类、地质灾害遥感解译等方面详细介绍了地质灾害遥感调查技术路线;从气候环境特征、地形地貌环境特征、植被类型及盖度、土地利用特征等方     

Intraseasonal oscillation of the southwest monsoon over Sri Lanka and evaluation of its subseasonal forecast skill

斯里兰卡的雨季发生于5-9月间,主要受西南季风的控制.本文发现该地区的西南季风降水存在很强的次季节变率,主导周期为10-35天.降水的季节内变化与西传的异常气旋有关.进一步,利用S2S比较计划中欧洲中心的数值预报模式(ECMWF)提供的回报试验数据,评估了当今动力模式对斯里兰卡西南季风次季节变化的预报技巧.结果显示,对季风指数的预测技巧超过30天,而对降水指数的预测技巧大约两周,且模式的预报技巧具有明显的年际差异.分析表明,能否正确模拟出大尺度环流对热带对流的响应是影响斯里兰卡降水预测的重要因子.     

Geology and Mineral Chemistry of Uranium- and Thorium-bearing Minerals in Rare-Metal (NYF) Pegmatites of Um Solimate,South Eastern Desert,Egypt

The garnet muscovite granitic pegmatite of Um Solimate, in southern Egypt, represents a promising asset for strategic and economic metals, especially Bi–Ni–Ag–Nb–Ta as well as U and Th. The ore bodies occur as large masses, pockets and/or veins of very coarse-grained pegmatites, which consist mainly of K-feldspar, quartz and albite with subordinate muscovite, garnet, and biotite. Radiometric data revealed that eU- and eTh-contents of the pegmatites reach up to 39 ppm and 82 ppm, respectively. The studied pegmatites are enriched in primary U and Th minerals (uraninite, coffinite, thorianite and uranothorite) as well as Hf-rich zircon and monazite, which give rise to anomalous radioactive zones. Niobium-tantalium-bearing minerals (i.e. ferrocolumbite, microlite and uranopyrochlore), xenotime, barite, galena, fluorite, and apatite are ubiquitous, and, consequently, the studied pegmatites belong tothe Niobium–Yttrium–Fluorine-type (NYF) family. The noble metal mineralization includes argentite (Ag2S), native Ni and Bi as well as bismite and bismoclite. In addition, beryl and tourmaline are observed in pegmatites near the contact with metasediments and ultramafic bodies. The observed compositional variations of Ta/(Ta+Nb) and Mn/(Mn+Fe) ratios in columbite (0.08–0.45 and 0.11–0.57, respectively) and Hf contents in zircon (3.54–6.46 wt%) may reflectan extreme degree of magmatic fractionation leading to formation of the pegmatite orebody.     

Spatial landslide susceptibility assessment using machine learning techniques assisted by additional data created with generative adversarial networks

In recent years,landslide susceptibility mapping has substantially improved with advances in machine learning.However,there are still challenges remain in landslide mapping due to the availability of limited inventory data.In this paper,a novel method that improves the performance of machine learning techniques is presented.The proposed method creates synthetic inventory data using Generative Adversarial Networks(GANs)for improving the prediction of landslides.In this research,landslide inventory data of 156 landslide locations were identified in Cameron Highlands,Malaysia,taken from previous projects the authors worked on.Elevation,slope,aspect,plan curvature,profile curvature,total curvature,lithology,land use and land cover(LULC),distance to the road,distance to the river,stream power index(SPI),sediment transport index(STI),terrain roughness index(TRI),topographic wetness index(TWI)and vegetation density are geo-environmental factors considered in this study based on suggestions from previous works on Cameron Highlands.To show the capability of GANs in improving landslide prediction models,this study tests the proposed GAN model with benchmark models namely Artificial Neural Network(ANN),Support Vector Machine(SVM),Decision Trees(DT),Random Forest(RF)and Bagging ensemble models with ANN and SVM models.These models were validated using the area under the receiver operating characteristic curve(AUROC).The DT,RF,SVM,ANN and Bagging ensemble could achieve the AUROC values of(0.90,0.94,0.86,0.69 and 0.82)for the training;and the AUROC of(0.76,0.81,0.85,0.72 and 0.75)for the test,subsequently.When using additional samples,the same models achieved the AUROC values of(0.92,0.94,0.88,0.75 and 0.84)for the training and(0.78,0.82,0.82,0.78 and 0.80)for the test,respectively.Using the additional samples improved the test accuracy of all the models except SVM.As a result,in data-scarce environments,this research showed that utilizing GANs to generate supplementary samples is promising because it can improve the predictive capability of common landslide prediction models.     

Brittleness index predictions from Lower Barnett Shale well-log data applying an optimized data matching algorithm at various sampling densities

The capability of accurately predicting mineralogical brittleness index(BI)from basic suites of well logs is desir-able as it provides a useful indicator of the fracability of tight formations.Measuring mineralogical components in rocks is expensive and time consuming.However,the basic well log curves are not well correlated with BI so correlation-based,machine-learning methods are not able to derive highly accurate BI predictions using such data.A correlation-free,optimized data-matching algorithm is configured to predict BI on a supervised basis from well log and core data available from two published wells in the Lower Barnett Shale Formation(Texas).This transparent open box(TOB)algorithm matches data records by calculating the sum of squared errors be-tween their variables and selecting the best matches as those with the minimum squared errors.It then applies optimizers to adjust weights applied to individual variable errors to minimize the root mean square error(RMSE)between calculated and predicted(BI).The prediction accuracy achieved by TOB using just five well logs(Gr,pb,Ns,Rs,Dt)to predict BI is dependent on the density of data records sampled.At a sampling density of about one sample per 0.5 ft BI is predicted with RMSE～0.056 and R2～0.790.At a sampling density of about one sample per 0.1 ft BI is predicted with RMSE～0.008 and R2～0.995.Adding a stratigraphic height index as an additional(sixth)input variable method improves BI prediction accuracy to RMSE～0.003 and R2～0.999 for the two wells with only 1 record in 10,000 yielding a BI prediction error of＞±0.1.The model has the potential to be applied in an unsupervised basis to predict BI from basic well log data in surrounding wells lacking mineralogical measure-ments but with similar lithofacies and burial histories.The method could also be extended to predict elastic rock properties in and seismic attributes from wells and seismic data to improve the precision of brittleness index and fracability mapping spatially.