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。     

VPN技术在煤炭地质档案网络服务中的应用

网络服务是煤炭地质档案业务发展的必由之路,为了解决在公共网络传输过程中的安全问题,本文介绍了一种虚拟专用网络技术,通过分析其应用于煤炭地质档案网络服务中的优势,为行业内外部的信息共享提供了一个新的思路。     

青龙煤矿采探对比及构造分析

通过对青龙井田两次勘查进行采探对比分析,认为存在工程量不足、构造和煤层控制程度低、高级资源量比例低、地质规律研究不足等问题。青龙井田构造以断层为主、褶曲为辅,小断层、小型紧闭褶曲极为发育,断层具有落差大、密度大、延展长度大、相互切割、下盘牵引破坏明显等特点,断层总体以NE向为主,可分为NE向正、逆断层组,NW向正、逆断层组4组。井田F4、F22断层附近及F4断层以南、F22断层东南为构造复杂区,升田深部为构造较复杂区,综合评价井田构造复杂程度为较复杂一复杂类型。目前矿井生产被动局面是由于地质构造复杂、煤层稳定性差和前期勘查程度低造成,通过分析构造和煤层对采区和工作面设计、工作面回采等影响,提出了今后井田勘查、矿井生产和地质丁作建议,对贵州煤矿地质工作具有一定的借鉴作用。     

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。     

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.     

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.