The structural characteristics,age of origin,and tectonic attribute of the Erguna Fault,NE China

The Erguna Fault runs along the east bank of the Erguna River in NE China and is a large-scale ductile shear zone comprising granitic mylonites. This paper reports on the geometry, kinematic indicators, and 40Ar/39 Ar biotite ages of the granitic mylonites, to constrain the structural characteristics, forming age, and tectonic attribute of the Erguna ductile shear zone. The zone strikes NE and records a top-to-the-NW sense of shear. A mylonitic foliation and stretching lineation are well developed in the mylonites, which are classified as S-L tectonites. Logarithmic flinn parameters(1.18–2.35) indicate elongate strain which approximates to plane strain. Kinematic vorticity numbers are 0.42–0.92 and 0.48–0.94, based on the polar Mohr diagram and the oblique foliation in quartz ribbons, respectively, suggesting that the ductile shear zone formed under general shear, or a combination of simple and pure shear. According to finite strain and kinematic vorticity analyses, the Erguna Fault is a lengthening-thinning ductile shear zone that formed by extension. The deformation behavior of minerals in the mylonites indicates that the fault was the site of three stages of deformation: an initial stage of middle- to deep-level, high-temperature shear, a post-stress recovery phase of high-temperature static recrystallization, and a final phase of low-temperature uplift and cooling. The 40Ar/39 Ar plateau ages of biotite from the granitic mylonites are 106.16 ± 0.79 and 111.55 ± 0.67 Ma, which constrain the timing of low-temperature uplift and cooling but are younger than the ages of metamorphic core complexes(MCCs) in the Transbaikalia-northeast Mongolia region. Using measured geological sections, microtectonics, estimates of finite strain and kinematic vorticity, and regional correlations and geochronology, we conclude that the Erguna Fault is an Early Cretaceous, NNE-trending, large-scale, sub-horizontal, and extensional ductile shear zone. It shares a similar tectonic background with the MCCs, volcanic fault basins, and large and super-large volcanic-hydrothermal deposits in Transbaikalia-northeast Mongolia and the western Great Khingan Mountains, all of which are the result of overthickened crust that gravitationally collapsed and extended in the Early Cretaceous after plate collision along the present-day Sino-Russia-Mongolia border tract.     

Geochemistry and possible origin of the hydrocarbons from Wells Zhongshen1 and Zhongshen1C,Tazhong Uplift

In 2013, a great breakthrough of deep petroleum exploration was achieved in the Cambrian pre-salt intervals of Wells Zhongshen1 (ZS1) and Zhongshen1C (ZS1C), Tazhong Uplift. However, the hydrocarbon discovery in the Cambrian pre-salt intervals has triggered extensive controversy regarding the source of marine oils in the Tarim Basin. The geochemistry and origin of the Cambrian pre-salt hydrocarbons in Wells ZS1 and ZS1C were investigated using GC, GC-MS and stable carbon isotope technique. These hydrocarbons can be easily distinguished into two genetic families based on their geochemical and carbon isotopic compositions. The oil and natural gases from the Awatage Formation of Well ZS1 are derived from Middle- Upper Ordovician source rocks. In contrast, the condensate and gases from the Xiaoerbulake Formation of Wells ZS1 and ZS1C probably originate from Cambrian source rocks. The recent discovery of these hydrocarbons with two different sources in Wells ZS1 and ZS1C suggests that both Middle-Upper Ordovician-sourced hydrocarbons and Cambrian-sourced petroleums are accumulated in the Tazhong Uplift, presenting a great exploration potential.     

大岗山库区主动震源探测系统性能及其影响因素

利用大岗山水库地震监测台网,在大岗山库区建立了主动震源探测系统。主动震源设备为10t精密控制机械震源,接收台站包括大岗山水库地震台网的8个固定台站、2个加密流动台站和1个震源接收台。本文介绍了大岗山库区主动震源探测系统的基本情况、震源与地基的耦合特征、系统的性能及其影响因素等,并通过初步数据处理获取了大岗山库区地壳波速的相对变化。     

新疆地区县(市)地震应急能力指标体系的建立与区域差异初探

从新疆地区地震活动性、灾害背景及区域协同联动应急模式出发,在遵循科学性、系统优化和可操作性及区域特性等原则的基础上,采用层次分析法建立了县级行政单元的地震应急能力评价指标体系;继而建立了基于基础设施条件、基础人力物力财力、(县级)专项能力和专项经验及基础环境背景4个一类指标集的县(市)绝对地震应急能力综合评价模型,并根据新疆地区4类人员问卷调查资料,计算和分析了样本支持条件下各指标的权重及结果,将其应用在新疆地区县(市)地震应急能力等级划分中。结果表明,地震应急能力的空间分布格局的产生与区域经济发展水平和地理位置等方面所具备的优势是相适应的,安居富民工程对提升区域地震应急能力发挥了重要作用,少数民族聚集区应急能力有待加强,寒旱、高海拔地区等特殊地理因素影响不可忽视。     

3D modeling of geological anomalies based on segmentation of multiattribute fusion

3D modeling of geological bodies based on 3D seismic data is used to define the shape and volume of the bodies, which then can be directly applied to reservoir prediction, reserve estimation, and exploration. However, multiattributes are not effectively used in 3D modeling. To solve this problem, we propose a novel method for building of 3D model of geological anomalies based on the segmentation of multiattribute fusion. First, we divide the seismic attributes into edge- and region-based seismic attributes. Then, the segmentation model incorporating the edge- and region-based models is constructed within the levelset-based framework. Finally, the marching cubes algorithm is adopted to extract the zero level set based on the segmentation results and build the 3D model of the geological anomaly. Combining the edge-and region-based attributes to build the segmentation model, we satisfy the independence requirement and avoid the problem of insufficient data of single seismic attribute in capturing the boundaries of geological anomalies. We apply the proposed method to seismic data from the Sichuan Basin in southwestern China and obtain 3D models of caves and channels. Compared with 3D models obtained based on single seismic attributes, the results are better agreement with reality.     

Water quality assessment of the Huaihe River segment of Bengbu (China) using multivariate statistical techniques

In the study, multivariate statistical methods including principal component analysis (PCA)/factor analysis (FA) and cluster analysis (CA) were applied to analyze surface water quality data sets obtained from the Huaihe River segment of Bengbu (HRSB) and generated during 2 years (2011–2012) monitoring of 19 parameters at 7 sampling sites. The results of PCA for 7 sampling sites revealed that the first four components of PCA showed 94.89% of the total variance in the data sets of HRSB. The Principal components (Factors) obtained from FA indicated that the parameters for water quality variations were mainly related to heavy metals (Pb, Mn, Zn and Fe) and organic related parameters (COD, PI and DO). The results revealed that the major causes of water quality deterioration were related to inflow of industrial, domestic and agricultural effluents into the Huaihe River. Three significant sampling locations—(sites 2, 3 and 4), (sites 1 and 5) and (sites 6 and 7)—were detected on the basis of similarity of their water quality. Thus, these methods were believed to be valuable to help water resources managers understand complex nature of water quality issues and determine the priorities to improve water quality.     

Copula‐based joint probability function for PGA and CAV: a case study from Taiwan

This study aims to develop a joint probability function of peak ground acceleration (PGA) and cumulative absolute velocity (CAV) for the strong ground motion data from Taiwan. First, a total of 40,385 earthquake time histories are collected from the Taiwan Strong Motion Instrumentation Program. Then, the copula approach is introduced and applied to model the joint probability distribution of PGA and CAV. Finally, the correlation results using the PGA‐CAV empirical data and the normalized residuals are compared. The results indicate that there exists a strong positive correlation between PGA and CAV. For both the PGA and CAV empirical data and the normalized residuals, the multivariate lognormal distribution composed of two lognormal marginal distributions and the Gaussian copula provides adequate characterization of the PGA‐CAV joint distribution observed in Taiwan. This finding demonstrates the validity of the conventional two‐step approach for developing empirical ground motion prediction equations (GMPEs) of multiple ground motion parameters from the copula viewpoint. Copyright © 2016 John Wiley & Sons, Ltd.     

Dynamic programming approach for segmentation of multivariate time series

In this paper, dynamic programming (DP) algorithm is applied to automatically segment multivariate time series. The definition and recursive formulation of segment errors of univariate time series are extended to multivariate time series, so that DP algorithm is computationally viable for multivariate time series. The order of autoregression and segmentation are simultaneously determined by Schwarz’s Bayesian information criterion. The segmentation procedure is evaluated with artificially synthesized and hydrometeorological multivariate time series. Synthetic multivariate time series are generated by threshold autoregressive model, and in real-world multivariate time series experiment we propose that besides the regression by constant, autoregression should be taken into account. The experimental studies show that the proposed algorithm performs well.     

新疆于田MS7.3地震主震精定位研究

新疆、青海、西藏数字地震台网和新疆和田台阵都十分清晰、完整地记录到2014年2月12日新疆于田MS7.3地震的波形,故采用区域地震台网和地震台阵联合定位的方法来精确测定该地震的震源位置。具体定位时采用了以下技术：①根据MS7.3地震震中的位置,360o等方位均匀选取台站,平均每隔约15o取1个台站参与初始定位;②将于田台的记录波形旋转至径向和切向上精确测定S波的到时,并以此控制震中距;③测定震中位置时采用的速度模型,是以震源为中心、半径约为1.0o范围内发生的历史地震资料为基础,重新拟合后获得的速度模型;④利用和田地震台阵记录的主震波形资料,经波形聚束方法处理后进行方位角测定,并以此方位角修正震中位置;⑤采用确定性方法测定震源深度。最终得到新疆于田MS7.3地震主震的震中位置为36.197oN、82.467oE,震源深度为12km,发震时刻为2014年2月12日17:19:48.2。