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101.
影响地下应力状态的构造作用 总被引:4,自引:0,他引:4
成岩成矿的外部条件中压力是很重要的因素。地下岩石所受的压力不仅来自上覆岩石的重力,而且来自构造力和热力及其它力。这些力合成一个三轴不等的应力状态,相当一个以最短轴为半径的球状应力迭加一个差应力。前者影响成岩成矿和变质作用,后者控制岩石变形和组构的变化。通过三维应变应力测量,这两部分力通过计算是可以区分开的,因而这将是建立地下深度测算新方法的一个基础。 相似文献
102.
在中国大陆科学钻探孔区 (江苏省东海县南部 )进行了系统的地球物理调查 ,包括二维地震测网和专门的地震剖面 ,大地电磁法和位场方法等 .地震调查表明 ,在超高压变质岩出露区上地壳充满了反射体 ,包括倾斜反射体与上拱的反射弧 .本文介绍大陆科学钻探先行研究中地震调查的成果 .根据大陆科学钻探预先导孔的岩芯和测井资料、井旁VSP和数值模拟结果证实 ,高波速的榴辉岩体、破碎断裂带和大型韧性剪切带都可引起倾斜的地震反射 ,而上拱的弧形反射体则是由近似直立的榴辉岩体和其中的破碎带的综合反映 .由于地壳深部广泛分布着经受变质的岩石 ,上述研究结果对标定地壳中的反射地震信号具有一定意义 相似文献
103.
104.
105.
中全新世以来黑龙江同江地区的孢粉组合与植被、气候演化 总被引:2,自引:11,他引:2
对黑龙江省同江县96-QP剖面从下至上划分4个孢粉组合带:1是以蒙古栎-桦属-蒿属-苔草属-木本科-水龙骨科为主组合带;2是以蒿属-莎草科-禾本科-桦属-栎属为主组合带;3是以桦属-蒙古栎松属-蒿属-莎草科-禾本科为主组合带;4是以松属-桦属-蒙古栎-蒿属-苔草属为主组合带。这4个孢粉组合带清楚地反映了古植被,古气候演替4个阶段;依次为温性落叶阔叶林-针,阔叶混交林→以落叶阔叶树稍多的针、阔叶混交林-草原→以松占优势的针、阔叶混交林。其气候变化是温暖湿润-温和略干-温和略湿-温凉湿润。 相似文献
106.
模拟酸雨对福建四种山地土壤的淋溶与风化作用 总被引:6,自引:0,他引:6
在不同pH值 (2 .0、3.5、5 .0、6 .0及蒸馏水 )的模拟酸雨作用下 ,对福建四种类型山地土壤进行了为期 12 0d的淋溶试验。结果表明 ,盐基离子的淋溶量随模拟酸雨pH值的降低而增加 ,尤其当pH≤ 3.5时 ,增加最明显。 4种类型土壤中各离子淋失量大小均为 :Ca2 >Mg2 >K >Na ,这与原土壤中交换性盐基含量一致。在pH≥ 3.5的酸雨作用下 ,土壤中铝的淋失较少 ,而当酸雨pH =2 .0时 ,铝的淋失骤然升高。pH2 .0的模拟酸雨不仅增加了土壤铝离子的释放 ,而且加速了矿物的风化。在pH2 .0的模拟酸雨淋溶下 ,红壤、黄壤、山地草甸土和紫色土中由矿物风化输入的 5种阳离子总量分别为 2 .94、4 .33、4 .35和 6 .0 4 (cmol kg)土 ,显著大于其它酸雨处理。土壤对酸沉降的缓冲作用由阳离子交换、氢氧化铝水解以及原生矿物风化缓冲作用三部分组成 ,其相对重要性不仅决定于土壤酸度、盐基饱和度和矿物组成 ,而且与酸雨的pH值密切相关 相似文献
107.
One of the main factors that affects the performance of MLP neural networks trained using the backpropagation algorithm in mineral-potential mapping isthe paucity of deposit relative to barren training patterns. To overcome this problem, random noise is added to the original training patterns in order to create additional synthetic deposit training data. Experiments on the effect of the number of deposits available for training in the Kalgoorlie Terrane orogenic gold province show that both the classification performance of a trained network and the quality of the resultant prospectivity map increasesignificantly with increased numbers of deposit patterns. Experiments are conducted to determine the optimum amount of noise using both uniform and normally distributed random noise. Through the addition of noise to the original deposit training data, the number of deposit training patterns is increased from approximately 50 to 1000. The percentage of correct classifications significantly improves for the independent test set as well as for deposit patterns in the test set. For example, using ±40% uniform random noise, the test-set classification performance increases from 67.9% and 68.0% to 72.8% and 77.1% (for test-set overall and test-set deposit patterns, respectively). Indices for the quality of the resultant prospectivity map, (i.e. D/A, D × (D/A), where D is the percentage of deposits and A is the percentage of the total area for the highest prospectivity map-class, and area under an ROC curve) also increase from 8.2, 105, 0.79 to 17.9, 226, 0.87, respectively. Increasing the size of the training-stop data set results in a further increase in classification performance to 73.5%, 77.4%, 14.7, 296, 0.87 for test-set overall and test-set deposit patterns, D/A, D × (D/A), and area under the ROC curve, respectively. 相似文献
108.
Joseph S. Duval 《Natural Resources Research》2003,12(2):121-126
The U.S. Geological Survey has developed a technique that allows mineral resource experts to apply economic filters to estimates of undiscovered mineral resources. This technique builds on previous work that developed quantitative methods for mineral resource assessments. A Monte-Carlo calculation uses mineral deposit models to estimate commodity grades and tonnages of undiscovered deposits. The results then are analyzed using simple estimates of capital expenditures and daily operating costs for a mine and associated mill. The daily operating costs and the value of the ore are used to calculate the net present value of the deposit, which is compared to the capital expenditures to determine whether the deposit is economic. Repetition of these calculations for many deposits produces a table that can be interpreted in terms of the probability of there being deposits that have anet present value exceeding some specified amount. Sample calculations indicate that applying economic filters to simulated mineral resources might change the perception of the results compared to presenting the calculations in terms of the expected mean gross-in-place value of the minerals. 相似文献
109.
Use of GIS layers, in which the cell values represent fuzzy membership variables, is an effective method of combining subjective geological knowledge with empirical data in a neural network approach to mineral-prospectivity mapping. In this study, multilayer perceptron (MLP), neural networks are used to combine up to 17 regional exploration variables to predict the potential for orogenic gold deposits in the form of prospectivity maps in the Archean Kalgoorlie Terrane of Western Australia. Two types of fuzzy membership layers are used. In the first type of layer, the statistical relationships between known gold deposits and variables in the GIS thematic layer are used to determine fuzzy membership values. For example, GIS layers depicting solid geology and rock-type combinations of categorical data at the nearest lithological boundary for each cell are converted to fuzzy membership layers representing favorable lithologies and favorable lithological boundaries, respectively. This type of fuzzy-membership input is a useful alternative to the 1-of-N coding used for categorical inputs, particularly if there are a large number of classes. Rheological contrast at lithological boundaries is modeled using a second type of fuzzy membership layer, in which the assignment of fuzzy membership value, although based on geological field data, is subjective. The methods used here could be applied to a large range of subjective data (e.g., favorability of tectonic environment, host stratigraphy, or reactivation along major faults) currently used in regional exploration programs, but which normally would not be included as inputs in an empirical neural network approach. 相似文献
110.
广西德保矿区产出的结晶为双锥状的臭葱石的主要化学成分为Fe2O3 34.5%,As2O5 47.75%;而呈葡萄状的臭葱石含Fe2O3 26.67%,As2O5 44.28%, 它们的FeAs≈1,与理想分子式FeAsO4*2H2O接近.根据该矿物(德保)的粉晶X射线分析数据用最小二乘法计算的晶胞参数为a0=10.28(A),b0=10.00(A),c0=8.90(A).Z=8,为斜方晶系,空间群为Pcab.红外吸收光谱分析显示有波数为3505、3420、3000、820、720、490、470、435、415(cm-1)等吸收带.差热分析显示有256℃、945℃和980℃三个明显的吸热谷,还显示有520℃、725℃两个小的放热峰. 相似文献