酸改性红辉沸石特征研究

采用物理比表面积、扫描电镜、红外光谱、X射线衍射、差热等方法来表征酸改性后的红辉沸石矿石特征,获得通过酸改性后红辉沸石比表面积、孔容和原矿中的杂质都会发生变化,从而可提高红辉沸石的吸附和交换性能,达到改性红辉沸石处理污染物的能力。     

垂直上升管中气液两相流电导波动信号的混沌特性分析

首先以Lorenz混沌方程产生的非线性时间序列为例,讨论了在不同时间序列长度下各种延迟时间算法对噪声的适用性.研究发现,采用C_C算法计算延迟时间的鲁棒性强.在此基础上,给出了垂直上升管中气水两相流电导波动信号混沌表征结果,发现在较低水相表观速度时,随着气相表观速度增加,泡状流及混状流动力学特性变得愈加复杂,而段塞流动力学特性受液相表观速度影响较大;在较高水相表观速度时,随着气相表观速度增加,当流型从泡状流向段塞流转变时,气液两相流动力学特性变得相对简单.但是,由于受液相湍流作用影响,段塞流的动力学特性表现出了涨落现象,呈现不稳定性,当流型从段塞流向混状流转变时,气液两相流动力学特性则变得愈加复杂.研究结果表明：基于电导波动信号的混沌分析可以较好地表征气液两相流流型变化,是理解流型转变机理及其动力学演变特性的有用工具.     

太湖梅梁湾藻华暴发消退-周期表层水体溶解性有机质分子特征

人类活动引起的富营养化对太湖的碳循环模式可能产生严重影响,精细描述太湖藻华暴发-消退周期的溶解性有机质分子是了解太湖碳库动态变化的关键.本研究利用傅立叶变换离子回旋共振质谱技术,以太湖北部梅梁湾2017年5月至2018年5月的表层水体为研究对象,解析藻华暴发-消退周期溶解性有机质的来源和分子组成特征,进而理解浮游藻类异常增殖对水体溶解性有机质的影响及其在区域碳循环中的角色.研究结果表明,藻华暴发期浮游藻类生产力显著增加,使得表层水体的溶解性有机质从含量到分子组成均发生剧烈改变.含量上表现为溶解性有机碳浓度升高,分子组成上表现为CHO类化合物和以脂肪族类化合物为代表的活性组分占比增加,特征化合物以相对高饱和度和高含氧的小质量数分子为主.而在藻华消退期,随着藻类有机质贡献的减少和有机质降解过程的持续进行,含量上表现为溶解性有机碳浓度下降,分子组成上表现为CHOS、CHONS类化合物和富羧酸脂环类化合物等惰性分子占比增加,特征化合物以大质量数分子和相对低饱和度和低含氧的小质量数分子为主.研究结果表明,太湖水体的溶解性有机质分子组成在藻华暴发期受藻类有机质输入控制,在消退期受藻类有机质降解的影响.     

联合多点地质统计学与序贯高斯模拟的随机反演方法

岩相和储层物性参数是油藏表征的重要参数,地震反演是储层表征和油气藏勘探开发的重要手段.随机地震反演通常基于地质统计学理论,能够对不同类型的信息源进行综合,建立具有较高分辨率的储层模型,因而得到广泛关注.其中,概率扰动方法是一种高效的迭代随机反演策略,它能综合考虑多种约束信息,且只需要较少的迭代次数即可获得反演结果.在概率扰动的优化反演策略中,本文有效的联合多点地质统计学与序贯高斯模拟,并结合统计岩石物理理论实现随机反演.首先,通过多点地质统计学随机模拟,获得一系列等可能的岩相模型,扰动更新初始岩相模型后利用相控序贯高斯模拟建立多个储层物性参数模型;然后通过统计岩石物理理论,计算相应的弹性参数;最后,正演得到合成地震记录并与实际地震数据对比,通过概率扰动方法进行迭代,直到获得满足给定误差要求的反演结果.利用多点地质统计学,能够更好地表征储层空间特征.相控序贯高斯模拟的应用,能够有效反映不同岩相中储层物性参数的分布.提出的方法可在较少的迭代次数内同时获得具有较高分辨率的岩相和物性参数反演结果,模型测试和实际数据应用验证了方法的可行性和有效性.     

安徽省大气颗粒物污染特征分析

对2016年全年颗粒物监测浓度数据进行统计分析,得到了安徽省颗粒物污染的空间分布、浓度和粒径,以及污染传输特征。结果表明,淮河以北、沿江和江淮之间、长江以南和皖南山区城市颗粒物污染随地理位置不同表现出明显的区域化特征,污染程度由北向南减轻,污染过程明显表现出由北向南逐步扩散传输的规律,污染程度越重,污染深入南方的范围越广,持续时间也越长。冬季污染较重的城市,上午出现明显的高浓度时段,全天变化为"双峰双谷"型。夏、秋季节夜间细颗粒物(PM_2.5)浓度贡献比增加。PM_2.5与PM₁₀(可吸入颗粒物)质量浓度比值冬季最高,春季较低。污染重的城市冬季PM_2.5占比高。     

红鳍东方鲀(Takifugu rubrips)病原杀对虾弧菌的主要生物学特性研究

采用表观分类学及分子生物学方法,对从发病的养殖红鳍东方()中分离的细菌进行了主要生物学特性研究.主要包括形态特征、理化特性等较系统的表观分类学指征鉴定;同时对代表菌株进行了16S rRNA基因的分子鉴定,测定了16S rRNA基因序列、分析了相关细菌相应序列的同源性、构建了系统发生树;结果表明,分离菌为弧茵属(Vibrio Pacini 1954)的杀对虾弧菌(Vibrio penaeicidasp.nov.Ishimaru et al 1995).代表菌株(Hc051105-6株)16s rRNA基因序列长度(不包括引物结合区)为1443bp(GenBank登录号:EU073023),代表菌株(HC051105-8株)16S rRNA基因序列长度(不包括 引物结合区)为1450bp(GenBank登录号:Eu073024).择代表菌株做对健康红鳍东方鲀的人工感染试验,认为分离鉴定的杀对虾弧菌在被检红鳍东方鱼电病例具有一定的病原学意义.药敏试验结果显示,对供试37种抗菌药物中,在一些药物中存在耐药性的菌株间差异.     

Characterization of landscape pattern based on land economic niche change: A case study in Ganzhou,Gansu Province,China

Land use change has a profound impact on biodiversity and ecological processes, and is closely related to changes in landscape patterns. This paper introduces the theory and method of land economic niche into landscape ecology, which provides a new method for spatial characterization of urban and rural spatial landscape patterns. Based on this theory, this paper analyzes the landscape pattern of Ganzhou District by using Landsat images as data source in 1995, 2000, 2005,2010 and 2015. We calculated the land economic niche by applying the niche potential theory. Combined with the theory of landscape ecology, we explored the effects of the land economic niche change on the landscape pattern at a county scale.The results show that economic niche of construction land, watershed and farmland increased during 1995–2015, and grassland declined significantly. The economic niche of farmland, construction land, watershed and grassland show a negative correlation with the number of patches(NP), fragmentation index(FN) and the fractal dimension index(FD), and had a positive correlation with the aggregation index(AI). There was no significant correlation between the forest land economic niche and landscape metrics. The change of land economic niche has a driving effect on the landscape pattern of the county, which can represent the economic development direction of Ganzhou District. The land economic niche is closely related to the landscape type which can directly obtain an economic benefit.     

Applying energy theory to understand the relationship between the Yangtze River and Poyang Lake

The complex relationship between the Yangtze River and Poyang Lake controls the exchange of water and sediment between the two, and exerts effects on water resources, flooding, shipping, and the ecological environment. The theory of energy is applied in this paper to investigate the physical mechanisms that determine the nature of the contact between the Yangtze River and Poyang Lake and to establish an energy difference (F_e) index to quantify the interactions between the two systems. Data show that F_e values for this interaction have increased since the 1950s, indicating a weakening in the river effect while the lake effect has been enhanced. Enclosure of the Three Gorges Reservoir (TGR) has also significantly influenced the relationship between the river and the lake by further reducing the impacts of the Yangtze River. The river effect also increases slightly during the dry season, and decreases significantly at the end of the flooding period, while interactions between the two to some extent influence the development of droughts and floods within the lake area. Data show that when the flow of the five rivers within this area is significant and a blocking effect due to the Yangtze River is also clearly apparent, floods occur easily; in contrast, when the opposite is true and the flow of the five rivers is small, and the Yangtze River can accommodate the flow, droughts occur frequently. Construction and enclosure of the TGR also means that the lake area is prone to droughts during September and October.     

Kernel Principal Component Analysis for Efficient,Differentiable Parameterization of Multipoint Geostatistics

This paper describes a novel approach for creating an efficient, general, and differentiable parameterization of large-scale non-Gaussian, non-stationary random fields (represented by multipoint geostatistics) that is capable of reproducing complex geological structures such as channels. Such parameterizations are appropriate for use with gradient-based algorithms applied to, for example, history-matching or uncertainty propagation. It is known that the standard Karhunen–Loeve (K–L) expansion, also called linear principal component analysis or PCA, can be used as a differentiable parameterization of input random fields defining the geological model. The standard K–L model is, however, limited in two respects. It requires an eigen-decomposition of the covariance matrix of the random field, which is prohibitively expensive for large models. In addition, it preserves only the two-point statistics of a random field, which is insufficient for reproducing complex structures. In this work, kernel PCA is applied to address the limitations associated with the standard K–L expansion. Although widely used in machine learning applications, it does not appear to have found any application for geological model parameterization. With kernel PCA, an eigen-decomposition of a small matrix called the kernel matrix is performed instead of the full covariance matrix. The method is much more efficient than the standard K–L procedure. Through use of higher order polynomial kernels, which implicitly define a high-dimensionality feature space, kernel PCA further enables the preservation of high-order statistics of the random field, instead of just two-point statistics as in the K–L method. The kernel PCA eigen-decomposition proceeds using a set of realizations created by geostatistical simulation (honoring two-point or multipoint statistics) rather than the analytical covariance function. We demonstrate that kernel PCA is capable of generating differentiable parameterizations that reproduce the essential features of complex geological structures represented by multipoint geostatistics. The kernel PCA representation is then applied to history match a water flooding problem. This example demonstrates that kernel PCA can be used with gradient-based history matching to provide models that match production history while maintaining multipoint geostatistics consistent with the underlying training image.     

Site characterization for CO<Subscript>2</Subscript> geologic storage and vice versa: the Frio brine pilot,Texas, USA as a case study

Careful site characterization is critical for successful geologic storage of carbon dioxide (CO₂) because of the many physical and chemical processes impacting CO₂ movement and containment under field conditions. Traditional site characterization techniques such as geological mapping, geophysical imaging, well logging, core analyses, and hydraulic well testing provide the basis for judging whether or not a site is suitable for CO₂ storage. However, only through the injection and monitoring of CO₂ itself can the coupling between buoyancy flow, geologic heterogeneity, and history-dependent multi-phase flow effects be observed and quantified. CO₂ injection and monitoring can therefore provide a valuable addition to the site-characterization process. Additionally, careful monitoring and verification of CO₂ plume development during the early stages of commercial operation should be performed to assess storage potential and demonstrate permanence. The Frio brine pilot, a research project located in Dayton, Texas (USA) is used as a case study to illustrate the concept of an iterative sequence in which traditional site characterization is used to prepare for CO₂ injection and then CO₂ injection itself is used to further site-characterization efforts, constrain geologic storage potential, and validate understanding of geochemical and hydrological processes. At the Frio brine pilot, in addition to traditional site-characterization techniques, CO₂ movement in the subsurface is monitored by sampling fluid at an observation well, running CO₂-saturation-sensitive well logs periodically in both injection and observation wells, imaging with crosswell seismic in the plane between the injection and observation wells, and obtaining vertical seismic profiles to monitor the CO₂ plume as it migrates beyond the immediate vicinity of the wells. Numerical modeling plays a central role in integrating geological, geophysical, and hydrological field observations.