地震勘探测量数据的快速处理和管理

目前山区地震测量施工主要的困难体现在山区放样难、内业数据处理复杂、测量成果无法进行异常检查等方面,其严重影响后续资料处理和解释质量。针对以上难点,利用AUTOCAD为平台,开发了一套物探测量数据处理系统。该系统具有展点、点内插、绘制测线剖面图、管理测点信息、打印成果报表等功能,实现了地震勘探测量数据的快速处理及有效检核．提高了野外测量放样的施工效率和数据的准确度。另外其图层管理及系统辅助功能,还可为地震勘探施工设计提供参考。     

基于GPS技术监测高层建筑物变形的研究

以武汉大学信息学部教学实验大楼为实验对象,分析了大楼在N、E、U方向上的每h变化、d变化及变形规律,阐明GPS技术在高层建筑变形监测中的应用。     

高速公路勘测定界的的方法研究

本文扼要阐述公路勘测定界测绘与其土地报批图件资料制作过程,借用现有商业软件南方"CASS成图系统"和办公系统软件微软"Microsoft Office Excel",成图、制表及图件资料涉及内容,提出应注意问题及建议。     

三维地震小面元采集技术在晋城矿区的应用

依托“西部煤炭资源高精度三维地震勘探技术”工程,对晋城矿区进行了旨在提高小断层,小陷落柱探测能力的高密度三维地震勘探。根据面元选择因素及该区地质任务,采用5m×5m网格进行野外数据采集;考虑炮检距、方位角、覆盖次数、排列片横纵比及煤层埋深（350～500m）等因素,采用中点放炮、60道接收,24次覆盖（横向4次,纵向6次）的8线16炮束状观测系统,基岩中激发。原始资料经同一处理流程后,获得5m×5m×1ms、5m×10m×1ms、10m×10m×1ms及2.5m×2.5m×1ms不同单元的三维数据体多个,通过对比可以发现小断层,小陷落柱在其小面元叠加时间剖面、顺层切片及相干切片都有清晰的反映。实例说明,小面元采集技术可以提高对小构造的纵、横向分辨能力,满足山区对三维地震精确勘探的要求。     

数值模拟技术在海坨子油田开发调整研究中的应用

讨论分析数值模拟技术在海坨子油田开发调整研究中的思路和方法,采用美国Landmark公司VIP2003．4版本数值模拟软件包进行模拟研究,通过参数准备,静、动态拟合,模拟出海坨子油田海S9—11井组1—9砂组各小层剩余储量大小及不同阶段流体饱和度分布,结合可视化技术形象描述了海坨子油田剩余油变化规律及潜力区,在此基础上预测不同井网加密方式开发指标,并优选出最佳方案,为海坨子油田下步开发调整提供了重要依据,取得了较好的效果。     

自动化监测技术在我国首条大型电力隧道中的应用

通过自动化监测在超大工程项目中的应用,利用现有技术手段,对工程进行有效管理,逐渐将对工程的安全、预判起到越来越重要的作用,它可以在为工程节约大量资金情况下,提高预判安全施工的能力,是提高工程管理的重要手段。     

Bayesian estimation of seismic hazard for two sites in Switzerland

Seismic hazard analysis is based on data and models, which both are imprecise and uncertain. Especially the interpretation of historical information into earthquake parameters, e.g. earthquake size and location, yields ambiguous and imprecise data. Models based on probability distributions have been developed in order to quantify and represent these uncertainties. Nevertheless, the majority of the procedures applied in seismic hazard assessment do not take into account these uncertainties, nor do they show the variance of the results. Therefore, a procedure based on Bayesian statistics was developed to estimate return periods for different ground motion intensities (MSK scale).Bayesian techniques provide a mathematical model to estimate the distribution of random variables in presence of uncertainties. The developed method estimates the probability distribution of the number of occurrences in a Poisson process described by the parameter . The input data are the historical occurrences of intensities for a particular site, represented by a discrete probability distribution for each earthquake. The calculation of these historical occurrences requires a careful preparation of all input parameters, i.e. a modelling of their uncertainties. The obtained results show that the variance of the recurrence rate is smaller in regions with higher seismic activity than in less active regions. It can also be demonstrated that long return periods cannot be estimated with confidence, because the time period of observation is too short. This indicates that the long return periods obtained by seismic source methods only reflects the delineated seismic sources and the chosen earthquake size distribution law.     

CSU－RAMS模式在区域气侯模拟中的应用

将ＣＳＵ－ＲＡＭＳ（中尺度）数值模式改造成“区域气候数值模式”以及进行区域气候数值模拟的试验研究。说明将有限区域中尺度数值模式与ＧＣＭ模式嵌套应用到区域气候数值模拟研究上能够取得有意义的结果。它能在一定程度上改善ＧＣＭ模式的不足。可以更为细致地描述大气环流的变化特征,是了解区域气候变化的有效方法之一。     

Generalized ‘dependencies’ and parameter variance

The autodependence, (a special case of the — now quite obsolete — dependences, which had been introduced for very specialized astrometric purposes) is proportional to the parameter variance which is the expectation of the variance of the systematic error of a function evaluated with estimated parameters.     

Estimation of statistical parameters for censored lognormal hydraulic conductivity measurements

Field tests of hydraulic conductivity (e.g., injection test, pumping test, etc.) in low permeability formations are subject to censoring due to the detection limit of the instruments used. An iterative method of estimating the mean and variance of hydraulic conductivity data with a presumed log-normal distribution function is presented. This method accounts for the data that are actually below the lower detection limit (called truncated data) and thus gives distribution parameters that are more representative for the underlying distribution. The proposed method is then tested on two simulated normally distributed random datasets having different variances. The results show that the means and variances estimated by the proposed method are very accurate. Finally, the method is used to estimate the mean and variance of hydraulic conductivity data from single hole water injection tests in a fractured geological formation.