西安市城市部件普查成果质量评价研究

结合西安市城市部件普查成果,根据成果质量表现形式及特征,总结了部件普查成果的质量评价内容和检验方法,并通过实践加以验证,提高数据质量评价准确率,降低数据不当评价的可能性,促进城市部件成果普查技术规范发展,高效广泛应用.     

Attributes and uncertainty of dissolved zinc data from a mined catchment

This study evaluated the attributes and uncertainty of non‐point source pollution data derived from synoptic surveys in a catchment affected by inactive metal mines in order to help to identify and select appropriate methods for data analysis/reporting and information use. Dissolved zinc data from the Upper Animas River Basin, Colorado, USA, were the focus of the study. Zinc was evaluated because concentrations were highest relative to national water quality criteria for brown trout, and zinc had the greatest frequency of criteria exceedances compared with other metals. Data attributes evaluated included measurement and model error, sample size, non‐normality, seasonality and uncertainty. The average measurement errors for discharges, concentrations and loadings were 0·15, 0·1 and 0·18, respectively. The 90 and 95% coefficients of confidence intervals for mean concentrations based on a sample size of four were 0·48 and 0·65, respectively, and ranged between 0·15 and 0·23 for sample sizes greater than 40. Aggregation of data from multiple stations decreased the confidence intervals significantly, but additional aggregation of all data increased them as a result of increasing spatial variability. Unit area loading data were approximately log‐normal. Concentration data were right‐skewed but not log‐normal. Differences in median concentrations were appreciable between snowmelt and both storm flow and baseflow, but not between storm flow and baseflow. Differences in unit area loadings between all flow events were large. It was determined that the average concentration and unit area loading values should be estimated for each flow event because of significant seasonality. Time weighted values generally should be computed if annual information is required. The confidence in average concentrations and unit area loadings is dependent on the computation method used. Both concentrations and loadings can be significantly underestimated on an annual basis when using data from synoptic surveys if the first flush of contaminants during the initial snowmelt runoff period is not sampled. The ambient standard for dissolved zinc for all events was estimated as 1600 μg l⁻¹ using the 85th percentile of observed concentration data, with a 90% confidence interval width of 200 μg l⁻¹. Copyright © 1999 John Wiley & Sons, Ltd.     

地面气象资料质量控制方法研究概述

为了促进我国地面气象资料质量控制方法的研究,以几个有代表性的数据集,如GHCN、GDCN、ISH为例,概述了国外地面气象资料质量控制技术的进展及新动态。研究表明：传统的质量控制方法仍是主要工具。在计算机技术迅速发展的时代,可以有更好的条件,使用自动控制和人机交互、气候背景资料和统计检验相结合的技术,并适当应用空间检验方法,来设计我国自动站地面气象资料质量控制业务流程。     

连云港海区养殖优质条斑紫菜原因研究

根据条斑紫菜的生物学特性及不同生育期的生长、发育要求,通过对我国沿海主要海区11～4月的海温、雾、风向、降水量及雨日和海区底质状况分析,得出连云港海区养殖条斑紫菜的客观条件比其他海区优越,所养殖的条斑紫菜品质好的结论。     

GE VCT-高图像质量和低剂量的和谐

在本文中讨论了实现图像质量和X射线剂量的和谐和同一的重要性,介绍了GELightSpeedVCT在硬件,软件和临床应用上降低病人剂量的方法。VCT在实现各向同性高分辨率的同时努力提高X射线的有效利用率,降低病人剂量,真正实现了高图像质量和低剂量的和谐。     

浅谈数字地形图的制作流程及其质量检查系统

介绍了地形图数字化过程中的几项关键技术及地形图数据质量的重要性,详细描述了数字地形图质量检查的内容及目前采用的质量检查方法,并指出了现有检查方法的缺点,并结合生产实际研究了一种人机交互式的检查系统。     

水下地形与淤泥厚度测量

目前,我国湖泊污染问题十分严重,主要是水质污染和淤泥污染,且湖泊测绘资料比较缺少。本文就某湖泊的整治作一阐述,较详细说明水下地形与淤泥厚度测量原理及方法。同时说明湖泊整治的重要性和迫切性。     

遥感影像压缩的构像质量评价

本文分析了JPEG2000压缩算法的基本原理,对某地区的数字航空遥感影像进行了压缩试验,通过比较不同压缩比下各种评价指标的变化,来研究JPEG2000压缩算法对重建影像构像质量的影响,评价结果表明压缩比的增加,重建影像灰度平均值、标准方差和信息熵在一定范围内波动;同时,随着压缩比的增加,重建影像纹理越来越粗,视觉效果降低,并且重建影像与原始影像的一致性程度降低,差别越来越大。     

High-resolution sequence stratigraphy,sedimentology and reservoir quality evaluation of the Yaojia Formation in the Longxi area of the Western Slope,Songliao Basin,China

Delta-front sand bodies with large remaining hydrocarbon reserves are widespread in the Upper Cretaceous Yaojia Formation in the Longxi area of the Western Slope, Songliao Basin, China. High-resolution sequence stratigraphy and sedimentology are performed based on core observations, well logs, and seismic profile interpretations. An evaluation of the reservoir quality of the Yaojia Formation is critical for further petroleum exploration and development. The Yaojia Formation is interpreted as a third-order sequence, comprising a transgressive systems tract (TST) and a regressive systems tract (RST), which spans 4.5 Myr during the Late Cretaceous. Within this third-order sequence, nine fourth-order sequences (FS9–FS1) are recognized. The average duration of a fourth-order sequence is approximately 0.5 Myr. The TST (FS9–FS5) mostly comprises subaqueous distributary channel fills, mouth bars, and distal bars, which pass upward into shallow-lake facies of the TST top (FS5). The RST (FS4–FS1) mainly contains subaqueous distributary-channel and interdistributary-bay deposits. Based on thin-sections, X-ray diffraction (XRD), scanning electron microscope (SEM) and high-pressure mercury-intrusion (HPMI) analyses, a petrographic study is conducted to explore the impact of the sedimentary cyclicity and facies changes on reservoir quality. The Yaojia sandstones are mainly composed of lithic arkoses and feldspathic litharenites. The sandstone cements mostly include calcite, illite, chlorite, and secondary quartz, occurring as grain coating or filling pores. The Yaojia sandstones have average core plug porosity of 18.55% and permeability of 100.77 × 10⁻³ μm², which results from abundant intergranular pores and dissolved pores with good connectivity. Due to the relatively coarser sediments and abundant dissolved pores in the feldspars, the FS4–FS1 sandstones have better reservoir quality than the FS9–FS5 sandstones, developing relatively higher porosity and permeability, especially the FS1 and FS2 sandstones. The source–reservoir–cap-rock assemblages were formed with the adjoining semi-deep lake mudstones that were developed in the Nenjiang and Qingshankou Formations. This study reveals the deposition and distribution of the delta-front sand bodies of the Yaojia Formation within a sequence stratigraphic framework as well as the factors controlling the Yaojia sandstones reservoir quality. The research is of great significance for the further exploration of the Yaojia Formation in the Longxi area, as well as in other similar lacustrine contexts.     

Prediction of diagenetic facies using well logs – A case study from the upper Triassic Yanchang Formation,Ordos Basin,China

Understanding diagenetic heterogeneity in tight sandstone reservoirs is vital for hydrocarbon exploration. As a typical tight sandstone reservoir, the seventh unit of the Upper Triassic Yanchang Formation in the Ordos Basin (Chang 7 unit), central China, is an important oil-producing interval. Results of helium porosity and permeability and petrographic assessment from thin sections, X-ray diffraction, scanning electron microscopy and cathodoluminescence analysis demonstrate that the sandstones have encountered various diagenetic processes encompassing mechanical and chemical compaction, cementation by carbonate, quartz, clay minerals, and dissolution of feldspar and lithic fragments. The sandstones comprise silt-to medium-grained lithic arkoses to feldspathic litharenites and litharenites, which have low porosity (0.5%–13.6%, with an average of 6.8%) and low permeability (0.009 × 10⁻³ μm² to 1.818 × 10⁻³ μm², with an average of 0.106 × 10⁻³ μm²).This study suggests that diagenetic facies identified from petrographic observations can be up-scaled by correlation with wire-line log responses, which can facilitate prediction of reservoir quality at a field-scale. Four diagenetic facies are determined based on petrographic features including intensity of compaction, cement types and amounts, and degree of dissolution. Unstable and labile components of sandstones can be identified by low bulk density and low gamma ray log values, and those sandstones show the highest reservoir quality. Tightly compacted sandstones/siltstones, which tend to have high gamma ray readings and relatively high bulk density values, show the poorest reservoir quality. A model based on principal component analysis (PCA) is built and show better prediction of diagenetic facies than biplots of well logs. The model is validated by blind testing log-predicted diagenetic facies against petrographic features from core samples of the Upper Triassic Yanchang Formation in the Ordos Basin, which indicates it is a helpful predictive model.