官厅水库水体营养状况分析

2001-2002年的调研结果显示,官厅水库为富营养型湖泊.初级生产力为浮游藻类与大型水生高等植物混合型.浮游藻类细胞密度为1126.54×104cells/L,其中蓝藻占53.4%,绿藻占32.1%.优势种为水华微囊藻(Microcystisflos-aquae)和铜绿微囊藻(M.aeruginosa).7-10月库区水体出现大面积的微囊藻水华.TN、TP分别为1.182mg/L和0.045mg/L,水体已达富营养.官厅水库TN和TP的质量浓度比大于7,Chla与TP存在显著的正相关.磷是水体中初级生产力增长的限制性营养盐.官厅水库的污染物主要来自点源,其次是面源和内源.应以点源为主进行综合防治,恢复其饮用水源地功能,以缓解北京市淡水资源的紧缺状态.     

答“评‘紫坪铺水库造成孔隙弹性耦合变化及其对2008年汶川地震触发作用’二维模拟的局限性”

程惠红等(2015)在"评‘紫坪铺水库造成孔隙弹性耦合变化及其对2008年汶川地震触发作用’二维模拟的局限性"一文中提出,陶玮等(2014)采用二维模型模拟紫坪铺水库造成孔隙弹性耦合变化是一个不足,夸大了汶川地震震源处库仑应力增长值.我们认为采用二维模型模拟水库造成汶川地震震源处库仑应力变化确实可能存在一定偏差,但不会如程惠红等认为的"与三维模型相比夸大三倍".这是因为在程惠红等引用的论证中,二维模型计算中选取了接近水库最大剖面宽度而不是水库平均剖面宽度作为加载量参数,造成计算得到震源处库仑应力明显夸大.此外,陶玮等(2014)提出论断的主要依据不是"震源处"库仑应力值的大小,而是紫坪铺水库蓄水"由浅入深影响到整条断层,尤其对浅层范围的加载作用明显,达上百千帕,为整个断层面的失稳提供了基础".初始破裂的发生既可能是由水库蓄水引起,也可能是并非水库蓄水造成的一次普通构造小震,但其发生引发断层面上部已被水库蓄水弱化部分的连锁失稳而发生大震.即汶川地震既可能为直接触发也可能为间接触发,而我们的研究结果认为地震的发生完全可能由间接触发产生.若仅纠结于"震源处"的库仑应力变化,则忽视了水库蓄水影响的主体.水库蓄水对地震触发作用是一个复杂问题,相对这一问题所涉及的一系列不确定性因素来说,二维模拟的局限性所造成的影响并不很大也不是最大的,也不妨碍我们据此得出紫坪铺水库蓄水促进汶川地震发生的结论.     

刘家峡水库西南部水域表层沉积物重金属污染评价

为了研究刘家峡水库西南部水域表层沉积物中重金属的污染状况,对采集的55个表层沉积物样品中的6种重金属元素Cr、Cd、Ni、Cu、Zn和Pb的含量进行测试,其平均含量分别为77.03μg/g、0.16μg/g、33.53μg/g、32.09μg/g、291.77μg/g、22.44μg/g。在研究表层沉积物重金属含量空间分布的基础上,运用单因子污染指数法、内梅罗综合污染指数法、地累积指数法、潜在生态风险指数法,综合判断水库的受污染程度并对其潜在生态风险进行评估。6种元素的地累积指数排序依次为：Zn > Cu > Cd > Ni > Pb > Cr;潜在生态风险系数排序依次为：Cd > Cu > Pb > Zn > Ni > Cr;各区域重金属污染程度或潜在生态风险水平依次为黄河主河道 > 大夏河河口 > 黄河横剖面。综合4种方法的评价结果,认为对刘家峡水库西南部表层沉积物重金属污染及潜在生态风险评价贡献率较高的重金属污染因子是Zn、Cu和Cd;综合相关性分析与主成分分析,认为研究区沉积物重金属污染主要来源于两个方面：（1） Zn、Cu主要来源于生活污染或工业污染;（2） Cd主要来源于工农业活动产生的污染。     

Coupling relationship between reservoir diagenesis and hydrocarbon accumulation in Lower Cretaceous Yingcheng Formation of Dongling,Changling fault depression,Songliao Basin,Northeast China

The Lower Cretaceous Yingcheng Formation in the southern Songliao Basin is the typical tight oil sandstone in China. In order to better predict the petrophysical properties of the tight sandstone reservoirs in the Lower Cretaceous Yingcheng Formation, Songliao Basin, Northeast China, the diagenesis and porosity evolution was investigated using a suite of petrographic and geochemical techniques including thin section analysis, scanning electron microscopy, mercury intrusion and fluid inclusion analysis, on a set of selected tight sandstone samples. Combined with the histories of burial evolution, organic matter thermal evolution and hydrocarbon charge, the matching relationship between reservoir porosity evolution and hydrocarbon accumulation history is analyzed. The result showed that the tight sandstone reservoirs characterized of being controlled by deposition, predominated by compaction, improved by dissolution and enhanced by cementation. The hydrocarbon accumulation period was investigated using a suite of hydrocarbon generation and expulsion history, microfluorescence determination and temperature measurement technology. According to the homogenization temperature of the inclusions and the history of burial evolution, Yingcheng Formation has mainly two phases hydrocarbon accumulation. The first phase of oil and gas is charged before the reservoir is tightened, the oil and gas generated by Shahezi source rocks enter the sand body of Yingcheng Formation, influenced by the carrying capability of sand conducting layer, oil and gas is mainly conducted by the better properties and higher connectivity sand body and enriched in the east, which belongs to the type of densification after hydrocarbon accumulation. The second phase of oil and gas charge after densification, which belongs to the type of densification before the hydrocarbon accumulation.     

Evaluation of clayed silt properties on the behavior of hydrate production in South China Sea

Gas hydrate is one kind of potential energy resources that is buried under deep seafloor or frozen areas. The first trial offshore production from the silty reservoir was conducted in the South China Sea by the China Geological Survey (CGS). During this test, there were many unique characteristics different from the sand reservoir, which was believed to be related to the clayed silt physical properties. In this paper, simulation experiments, facilities analysis, and theoretical calculation were used to confirm the hydrate structure, reservoir thermo-physical property, and bond water movement rule. And the behavior of how they affected production efficiency was analyzed. The results showed that: It was reasonable to use the structure I rather than structure II methane hydrate phase equilibrium data to make the production plan; the dissociation heat absorbed by hydrate was large enough to cause hydrate self-protection or reformation depend on the reservoir thermal transfer and gas supply; clayed silt got better thermal conductivity compared to coarse grain, but poor thermal convection especially with hydrate; clayed silt sediment was easy to bond water, but the irreducible water can be exchanged to free water under high production pressure, and the most obvious pressure range of water increment was 1.9–4.9 MPa.     

Deep neural network application for 4D seismic inversion to changes in pressure and saturation: Optimizing the use of synthetic training datasets

In this work, we tackle the challenge of quantitative estimation of reservoir dynamic property variations during a period of production, directly from four-dimensional seismic data in the amplitude domain. We employ a deep neural network to invert four-dimensional seismic amplitude maps to the simultaneous changes in pressure, water and gas saturations. The method is applied to a real field data case, where, as is common in such applications, the data measured at the wells are insufficient for properly training deep neural networks, thus, the network is trained on synthetic data. Training on synthetic data offers much freedom in designing a training dataset, therefore, it is important to understand the impact of the data distribution on the inversion results. To define the best way to construct a synthetic training dataset, we perform a study on four different approaches to populating the training set making remarks on data sizes, network generality and the impact of physics-based constraints. Using the results of a reservoir simulation model to populate our training datasets, we demonstrate the benefits of restricting training samples to fluid flow consistent combinations in the dynamic reservoir property domain. With this the network learns the physical correlations present in the training set, incorporating this information into the inference process, which allows it to make inferences on properties to which the seismic data are most uncertain. Additionally, we demonstrate the importance of applying regularization techniques such as adding noise to the synthetic data for training and show a possibility of estimating uncertainties in the inversion results by training multiple networks.     

A high-precision time–frequency analysis for thin hydrocarbon reservoir identification based on synchroextracting generalized S-transform

Improving the seismic time–frequency resolution is a crucial step for identifying thin reservoirs. In this paper, we propose a new high-precision time–frequency analysis algorithm, synchroextracting generalized S-transform, which exhibits superior performance at characterizing reservoirs and detecting hydrocarbons. This method first calculates time–frequency spectra using generalized S-transform; then, it squeezes all but the most smeared time–frequency coefficients into the instantaneous frequency trajectory and finally obtains highly accurate and energy-concentrated time–frequency spectra. We precisely deduce the mathematical formula of the synchroextracting generalized S-transform. Synthetic signal examples testify that this method can correctly decompose a signal and provide a better time–frequency representation. The results of a synthetic seismic signal and real seismic data demonstrate that this method can identify some reservoirs with thincknesses smaller than a quarter wavelength and can be successfully applied for hydrocarbon detection. In addition, examples of synthetic signals with different levels of Gaussian white noise show that this method can achieve better results under noisy conditions. Hence, the synchroextracting generalized S-transform has great application prospects and merits in seismic signal processing and interpretation.     

The effect of varied dam release mechanisms and storage volume on downstream river thermal regimes

Temperature plays an essential role in the ecology and biology of aquatic ecosystems. The use of dams to store and subsequently re-regulate river flows can have a negative impact on the natural thermal regime of rivers, causing thermal pollution of downstream river ecosystems. Autonomous thermal loggers were used to measure temperature changes downstream of a large dam on the Macquarie River, in Australia’s Murray-Darling Basin to quantify the effect of release mechanisms and dam storage volume on the downstream thermal regime. The magnitude of thermal pollution in the downstream river was affected by different release mechanisms, including bottom-level outlet releases, a thermal curtain (which draws water from above the hypolimnion), and spill-way release. Dam storage volume was linked to the magnitude of thermal pollution downstream; high storage volumes were related to severe thermal suppressions, with an approximate 10 °C difference occurring when water originated from high and low storage volumes. Downstream temperatures were 8 ̶ 10 °C higher when surface releases were used via a thermal curtain and the spillway to mitigate cold water pollution that frequently occurs in the river. Demonstrating the effectiveness of engineering and operational strategies used to mitigate cold water pollution highlight their potential contribution to fish conservation, threatened species recovery and environmental remediation of aquatic ecosystems.     

三峡水库消落区典型草本植物氮、磷养分计量特征

为明确消落区土壤养分对植物生长的影响,通过室内栽培试验,研究三峡库区秭归消落区土壤3种氮磷水平下4种草本植物—鬼针草(Bidens pilosa)、苍耳(Xanthium sibiricum)、水蓼(Polygonum hydropiper)、藜(Chenopodium album)长势及氮、磷计量特征.结果表明,消落区土壤中生长的植物氮含量为7.98~19.4 mg/g,磷含量为0.740~3.880 mg/g,氮磷比为3.48~13.70,判别植物生长受氮限制.外源氮磷的添加促进植物氮、磷含量明显升高,但氮磷比没有明显变化;外源氮磷添加解除植物受氮的限制作用.4种植物对消落区土壤低氮环境具有一定的适应能力.比较消落区土壤中4种植物长势,鬼针草生物量、相对生长率、根茎生物量比最高,氮磷养分丰富对鬼针草生长促进作用最明显,表明鬼针草更易于在氮、磷贫乏的三峡库区消落区形成优势群落.     

中华蚊母树(Distylium chinense)幼苗对秋、冬季淹水的生长及生理响应

为阐明三峡库区岸生植物中华蚊母树(Distylium chinense)幼苗对水淹的耐淹机理,通过设置对照组(CK)、半淹组(PF)、全淹组(CF)3个水淹处理,模拟库区消落带秋、冬季淹水情况,研究中华蚊母树幼苗在不同水淹时间和深度下的生长及生理生化特性.结果表明,淹水显著影响中华蚊母树幼苗的生物量,水淹150 d后,PF组植株和CF组植株根、茎、叶生物量均呈显著降低趋势,同时受水淹影响,植株根冠比也显著降低;中华蚊母树幼苗在水淹前90 d 2组水淹处理植株叶片丙二醛(MDA)含量均与CK组植株差异不显著,水淹120 d后,中华蚊母树幼苗叶片MDA含量显著增加,且随着水淹深度的增加而逐渐升高;可溶性蛋白在各水淹处理中的变化有所差异,水淹前60 d,淹水并没有影响CF组植株可溶性蛋白含量,但从水淹90 d开始,CF组植株可溶性蛋白含量有所上升,而PF组植株可溶性蛋白含量在整个淹水期间均与CK组植株差异不显著;2组水淹处理植株脯氨酸在水淹前期均显著上升,但自水淹90 d后逐渐下降至CK组水平;与MDA对水淹的响应一致,水淹前期PF组和CF组植株抗氧化酶活性(超氧化物歧化酶、过氧化氢酶和抗坏血酸过氧化物酶)均没有出现明显影响,但水淹后期2组水淹处理植株抗氧化酶活性均显著升高;可溶性糖含量在不同水淹处理下有所差异,PF组植株叶片可溶性糖含量在整个淹水期间均与CK组植株差异不显著;而CF组植株叶片可溶性糖含量随着水淹时间的延长逐渐降低.研究证明,中华蚊母树幼苗生长及生理特性对秋、冬季水淹环境具有一定的调节能力,是中华蚊母树幼苗能够在库区消落带存活生长的一个重要原因.