Automated Extraction of a Five‐Year LA‐ICP‐MS Trace Element Data Set of Ten Common Glass and Carbonate Reference Materials: Long‐Term Data Quality,Optimisation and Laser Cell Homogeneity

LA‐ICP‐MS is increasingly applied to obtain quantitative multi‐element data with minimal sample preparation, usually achieved by calibration using reference materials (RMs). However, some ubiquitous RMs, for example the NIST SRM 61× series glasses, suffer from reported value uncertainties for certain elements. Moreover, no long‐term data set of analyses conducted over a range of ablation and tuning conditions exists. Thus, there has been little rigorous examination of the extent to which offsets between measured and reported values are the result of error in these values rather than analytically induced fractionation. We present new software (‘LA‐MINE’), capable of extracting LA‐ICP‐MS data with no user input, and apply this to our system, yielding over 5 years of data (~ 5700 analyses of ten glass and carbonate RMs). We examine the relative importance of systematic analytical bias and possible error in reported values through a mass‐specific breakdown of fourteen of the most commonly determined elements. Furthermore, these data, obtained under a wide range of different ablation conditions, enable specific recommendations of how data quality may be improved, for example the role of diatomic gas, the effect of differential inter‐glass fractionation factors and choice of transport tubing material. Finally, these data demonstrate that the two‐volume Laurin ablation cell is characterised by no discernible spatial heterogeneity in measured trace element ratios.     

Defining the Potential of Nanoscale Re‐Os Isotope Systematics Using Atom Probe Microscopy

Atom probe microscopy (APM) is a relatively new in situ tool for measuring isotope fractions from nanoscale volumes (< 0.01 μm³). We calculate the theoretical detectable difference of an isotope ratio measurement result from APM using counting statistics of a hypothetical data set to be ± 4δ or 0.4% (2s). However, challenges associated with APM measurements (e.g., peak ranging, hydride formation and isobaric interferences), result in larger uncertainties if not properly accounted for. We evaluate these factors for Re‐Os isotope ratio measurements by comparing APM and negative thermal ionisation mass spectrometry (N‐TIMS) measurement results of pure Os, pure Re, and two synthetic Re‐Os‐bearing alloys from Schwander et al. (2015, Meteoritics and Planetary Science, 50, 893) [the original metal alloy (HSE) and alloys produced by heating HSE within silicate liquid (SYN)]. From this, we propose a current best practice for APM Re‐Os isotope ratio measurements. Using this refined approach, mean APM and N‐TIMS ¹⁸⁷Os/¹⁸⁹Os measurement results agree within 0.05% and 2s (pure Os), 0.6–2% and 2s (SYN) and 5–10% (HSE). The good agreement of N‐TIMS and APM ¹⁸⁷Os/¹⁸⁹Os measurements confirms that APM can extract robust isotope ratios. Therefore, this approach permits nanoscale isotope measurements of Os‐bearing alloys using the Re‐Os geochronometer that could not be measured by conventional measurement principles.     

Effect of 2D spatial variability on slope reliability: A simplified FORM analysis

To meet the high demand for reliability based design of slopes, we present in this paper a simplified HLRF(Hasofere Linde Rackwitze Fiessler) iterative algorithm for first-order reliability method(FORM). It is simply formulated in x-space and requires neither transformation of correlated random variables nor optimization tools. The solution can be easily improved by iteratively adjusting the step length. The algorithm is particularly useful to practicing engineers for geotechnical reliability analysis where standalone(deterministic) numerical packages are used. Based on the proposed algorithm and through direct perturbation analysis of random variables, we conducted a case study of earth slope reliability with complete consideration of soil uncertainty and spatial variability.     

基于GF-2影像西藏桑耶地区岩性-构造遥感解译

西藏桑耶地区位于青藏高原中南部,区内切割强烈,地势陡峻,属于高山峡谷区。为提高区域地质调查野外工作效率,在调查中率先开展了遥感解译研究。在充分收集已有资料的基础上,通过对GF-2卫星数据进行预处理和影像增强,结合野外验证建立了各地质要素的遥感解译标志,实现了区内不同地层岩性、侵入岩、断裂和褶皱等地质要素的提取,最终编制了研究区1:5万遥感地质解译图,为区域地质调查提供了数据支撑。结果表明: 各地质要素在GF-2数据上均有良好反映,完全满足1:5万尺度的遥感地质解译和编图的需要,充分显示出该卫星数据在区域地质调查等工作中具有良好的应用前景。     

庐枞火山岩盆地南部拔茅山铜矿深部找矿潜力分析

位于庐枞火山岩盆地南部的拔茅山铜矿,是细脉带蚀变岩型脉状铜矿的代表。研究表明,其深部具有斑岩型铜矿的勘探潜力。为了进一步明确其深部找矿潜力,针对研究区斑岩型、热液型铜多金属矿的岩体、断裂、接触带等主要控矿因素,利用高精度磁法和可控源音频大地电磁测深(CSAMT)成果,分别对拔茅山岩体的分布、产状和深部形态及其与围岩的接触带特征进行了剖析。在此基础上,通过与沙溪斑岩铜矿地质、物探异常特征的类比,指明了研究区的找矿方向和有利找矿部位,为进一步找矿提供了思路和依据。     

Multi-factor sensitivity analysis on the stability of submarine hydrate-bearing slope

There are many factors affecting the instability of the submarine hydrate-bearing slope (SHBS), and the interaction with hydrate is very complicated. In this paper, the mechanical mechanism of the static liquefaction and instability of submarine slope caused by the dissociation of natural gas hydrate (NGH) resulting in the rapid increase of pore pressure of gas hydrate-bearing sediments (GHBS) and the decrease of effective stress are analyzed based on the time series and type of SHBS. Then, taking the typical submarine slope in the northern South China Sea as an example, four important factors affecting the stability of SHBS are selected, such as the degree of hydrate dissociation, the depth of hydrate burial, the thickness of hydrate, and the depth of seawater. According to the principle of orthogonal method, 25 orthogonal test schemes with 4 factors and 5 levels are designed and the safety factors of submarine slope stability of each scheme are calculated by using the strength reduction finite element method. By means of the orthogonal design range analysis and the variance analysis, sensitivity of influential factors on stability of SHBS are obtained. The results show that the degree of hydrate dissociation is the most sensitive, followed by hydrate burial depth, the thickness of hydrate and the depth of seawater. Finally, the concept of gas hydrate critical burial depth is put forward according to the influence law of gas hydrate burial depth, and the numerical simulation for specific submarine slope is carried out, which indicates the existence of critical burial depth.     

Depositional setting,provenance, and tectonic-volcanic setting of Eocene–Recent deep-sea sediments of the oceanic Izu–Bonin forearc,northwest Pacific (IODP Expedition 352)

New biostratigraphical, geochemical, and magnetic evidence is synthesized with IODP Expedition 352 shipboard results to understand the sedimentary and tectono-magmatic development of the Izu–Bonin outer forearc region. The oceanic basement of the Izu–Bonin forearc was created by supra-subduction zone seafloor spreading during early Eocene (c. 50–51 Ma). Seafloor spreading created an irregular seafloor topography on which talus locally accumulated. Oxide-rich sediments accumulated above the igneous basement by mixing of hydrothermal and pelagic sediment. Basaltic volcanism was followed by a hiatus of up to 15 million years as a result of topographic isolation or sediment bypassing. Variably tuffaceous deep-sea sediments were deposited during Oligocene to early Miocene and from mid-Miocene to Pleistocene. The sediments ponded into extensional fault-controlled basins, whereas condensed sediments accumulated on a local basement high. Oligocene nannofossil ooze accumulated together with felsic tuff that was mainly derived from the nearby Izu–Bonin arc. Accumulation of radiolarian-bearing mud, silty clay, and hydrogenous metal oxides beneath the carbonate compensation depth (CCD) characterized the early Miocene, followed by middle Miocene–Pleistocene increased carbonate preservation, deepened CCD and tephra input from both the oceanic Izu–Bonin arc and the continental margin Honshu arc. The Izu–Bonin forearc basement formed in a near-equatorial setting, with late Mesozoic arc remnants to the west. Subduction-initiation magmatism is likely to have taken place near a pre-existing continent–oceanic crust boundary. The Izu–Bonin arc migrated northward and clockwise to collide with Honshu by early Miocene, strongly influencing regional sedimentation.     

Effect of loading duration on uncertainty in creep analysis of clay

Some studies suggest that creep parameters should be determined using a greater quantity of creep test data to provide more reliable prediction regarding the deformation of soft soils. This study aims to investigate the effect of loading duration on model updating. One‐dimensional consolidation data of intact Vanttila clay under different loading durations collected from the literature is used for demonstration. The Bayesian probabilistic method is used to identify all unknown parameters based on the consolidation data during the entire consolidation process, and their uncertainty can be quantified through the obtained posterior probability density functions. Additionally, the optimal models are also determined from among 9 model candidates. The analyses indicate that the optimal models can describe the creep behavior of intact soft soils under different loading durations, and the adopted method can evaluate the effect of loading duration on uncertainty in the creep analysis. The uncertainty of a specific model and its model parameters decreases as more creep data are involved in the updating process, and the updated models that use more creep data can better capture the deformation behavior of an intact sample. The proposed method can provide quantified uncertainty in the process of model updating and assist engineers to decide whether the creep test data are sufficient for the creep analysis.     

基于突变级数法的页岩气探采综合环境影响评价研究

为缓解能源紧张,页岩气作为储量丰富的非常规能源在我国正大力开发,而我国页岩气开发起步较晚,受管理与技术限制,页岩气开发造成的综合环境影响问题还得不到有效解决。针对页岩气开发存在的环境问题,本文基于我国页岩气开发现状,借鉴美国页岩气开发的成功经验,从自然环境与人文环境两方面对页岩气开发综合环境影响因素进行分析,建立了页岩气开发综合环境影响评价指标体系;同时为降低评价过程主观因素的影响,简化评估过程,本文引入突变级数法建立了页岩气开发综合环境影响评估模型,运用数值替换方法区分页岩气开发综合环境影响等级。最后将评价体系与评估模型应用到实际案例中,得到的评价结果与实际情况基本符合,为页岩气开发项目的综合环境评价提供了很好的理论依据。     

大数据环境下内蒙古浩布高地区铅锌多金属矿智能矿产预测研究

传统机器学习算法已广泛应用于矿产预测,但面对地质大数据的高维稀疏、不平衡小样本等特性仍缺乏有效处理和分析的方法,设计适合地质大数据特点的机器学习算法是智能矿产预测亟需解决的新问题。本文以内蒙古浩布高地区的铅锌多金属矿产预测为例,提出了一种面向地质大数据的半监督协同训练矿产预测模型。首先对研究区地质找矿信息和地球化学异常信息进行定量分析,提取断裂构造、二叠系地层、燕山期侵入岩、地层与岩体接触带、围岩蚀变及Pb、Zn、Sn、Cu地球化学异常共9种找矿因子。然后利用递归特征消除法优选找矿因子组合,不包括Sn异常在内的8个找矿因子组合被选为最优组合。最后,利用支持向量机和随机森林算法作为基分类器进行半监督协同训练矿产预测,绘制成矿概率分布图。ROC曲线和预测度曲线分析结果表明,半监督协同训练模型的AUC值和预测效率都高于随机森林和支持向量机模型。研究结果也为大数据环境下的智能矿产预测提供了一种新的思路。