镇泾地区延长组河流相砂体分布与圈闭形成的关系研究

鄂尔多斯盆地镇泾地区侏罗系地层以三角洲-湖泊沉积体系为主,研究区范围内主要发育主河道和部分分流河道砂体。研究区构造平缓,主要为单斜地层、在东南部存在大型鼻状构造。通过对主要储层段(长6、8油层组)砂体分布及与构造之间关系进行研究,分析砂体走向与构造线方向的关系认为在构造单斜地区,当两者相交时(交角β≠0)是形成圈闭的关键因素之一,在大型鼻状构造地区因构造线的弯曲与河道砂体组合可以形成圈闭。根据研究区砂体分布和构造线组合出4种地层-岩性及岩性圈闭。利用构造图与砂体分布图对主要储层段存在的圈闭确定出长6、8油层组10个层圈闭。     

GIS空间分析与模糊综合评判在银行ATM网点选址中的应用

空间分析是GIS的核心和灵魂,是GIS区别于一般信息系统的主要标志之一。运用GIS空间分析中的叠置分析、缓冲区分析、网络分析等功能对自动柜员机(ATM)网点进行选址,应用模糊综合评判模型对选址区位评价确定出ATM布放的最终布局,并通过实例验证该方法能为在ATM网点选址中提供决策依据,最后探讨了今后研究的方向。     

低渗透储层水平井—直井联合布井极限注采井距研究

低渗透储层水平井—直井联合布井技术具有广泛的应用前景,其布井方式至关重要。首先利用劈分流场的方法直观地给出常规储层水平井—直井联合布井的产能评价方法;然后针对低渗透储层的渗流特点,在考虑启动压力梯度条件下建立新的井网渗流物理模型并求解得到产能评价公式;最后经分析计算给出启动压力梯度影响的面积井网极限注采井距关系曲线。研究结果为低渗透储层部署水平井—直井联合井网提供理论依据。     

发挥自身优势 扩大经营 走探采一体化道路

煤炭地质勘查单位,通过几十年的艰苦奋斗,不仅为国家找出了大量的煤炭资源,同时也积累了丰富的管理、施工和技术工作经验,以及大量的地质资料。应该发挥自身优势,充分利用大量的以往地质资料,结合新的找矿理论和先进的地面勘查手段,加大人才培养和引进力度,逐步提升专业技术人员的学识和科技水平,加强基础地质工作,不断寻找新的工作靶区,把握住煤炭勘查市场的主动权。抓住机遇,做好资金积累,加强资本运做,充分利用已有探矿权,走探采一体化道路,做精做强到做大地勘单位,是生存和发展的良好出路。     

小面元三维地震勘探技术在西山屯兰矿南五采区的应用

屯兰矿南五采区地形复杂,最大高差达271m,地表大面积为第四系黄土覆盖,激发困难。为探索研究小面元三维地震勘探技术的应用效果。在常规三维地震勘区域内划出1km^2,采用5m×5m小面元进行采集。在地震数据采集过程中,采取了加大激发井深、提高覆盖次数、减小CMP面元网格和加大接收排列等技术措施,做到“四小三高、二中一深、两个等高面”。通过插值、抽线及扩大面元处理。获得2．5m×2．5m×1ms、5m×5m×1ms、5m×10m×1ms、10m×10m×1ms以及不同叠加次数的三维数据体。资料解释工作主要是在5m×5m×1ms、2．5m×2．5m×1ms两个数据体上进行,解释落差大于或等于5m的断层6条,落差3～5m的断层8条;查明长轴直径20～30m的陷落柱4个。30～100m的陷落柱1个,大于100m的陷落柱3个。与相邻区常规三维地震比较,小面元三维地震勘探有利于对小陷落柱、小断层的控制和解释。     

试论我国城市发展方针

在执行重重工业的发展战略和城乡分割体制的计划经济背景下,我国制定了“控制大城市规模,合理发展中等城市,积极发展小城市”的城市建设方针。但是分析表明,这一方针不能适应市场经济和对外开放形势的需要,也不符合我国人多地少、农村剩余劳动力多的国情,必须调整现有的城市发展方针,选择适宜的城市化发展道路。因此,本文就适度发展大中城市,提高城市现代化水平;加速乡村城市化,积极合理发展小城镇;以及根据不同地区的具体情况,因地制宜地指定城市化途径等方面作了探讨。     

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.     

Oil-generation kinetics for organic facies with Type-II and -IIS kerogen in the Menilite Shales of the Polish Carpathians

The Menilite Shales (Oligocene) of the Polish Carpathians are the source of low-sulfur oils in the thrust belt and some high-sulfur oils in the Carpathian Foredeep. These oil occurrences indicate that the high-sulfur oils in the Foredeep were generated and expelled before major thrusting and the low-sulfur oils in the thrust belt were generated and expelled during or after major thrusting. Two distinct organic facies have been observed in the Menilite Shales. One organic facies has a high clastic sediment input and contains Type-II kerogen. The other organic facies has a lower clastic sediment input and contains Type-IIS kerogen. Representative samples of both organic facies were used to determine kinetic parameters for immiscible oil generation by isothermal hydrous pyrolysis and S₂ generation by non-isothermal open-system pyrolysis. The derived kinetic parameters showed that timing of S₂ generation was not as different between the Type-IIS and -II kerogen based on open-system pyrolysis as compared with immiscible oil generation based on hydrous pyrolysis. Applying these kinetic parameters to a burial history in the Skole unit showed that some expelled oil would have been generated from the organic facies with Type-IIS kerogen before major thrusting with the hydrous-pyrolysis kinetic parameters but not with the open-system pyrolysis kinetic parameters. The inability of open-system pyrolysis to determine earlier petroleum generation from Type-IIS kerogen is attributed to the large polar-rich bitumen component in S₂ generation, rapid loss of sulfur free-radical initiators in the open system, and diminished radical selectivity and rate constant differences at higher temperatures. Hydrous-pyrolysis kinetic parameters are determined in the presence of water at lower temperatures in a closed system, which allows differentiation of bitumen and oil generation, interaction of free-radical initiators, greater radical selectivity, and more distinguishable rate constants as would occur during natural maturation. Kinetic parameters derived from hydrous pyrolysis show good correlations with one another (compensation effect) and kerogen organic-sulfur contents. These correlations allow for indirect determination of hydrous-pyrolysis kinetic parameters on the basis of the organic-sulfur mole fraction of an immature Type-II or -IIS kerogen.     

T -distributed Random Fields: A Parametric Model for Heavy-tailedWell-log Data1

Histograms of observations from spatial phenomena are often found to be more heavy-tailed than Gaussian distributions, which makes the Gaussian random field model unsuited. A T-distributed random field model with heavy-tailed marginal probability density functions is defined. The model is a generalization of the familiar Student-T distribution, and it may be given a Bayesian interpretation. The increased variability appears cross-realizations, contrary to in-realizations, since all realizations are Gaussian-like with varying variance between realizations. The T-distributed random field model is analytically tractable and the conditional model is developed, which provides algorithms for conditional simulation and prediction, so-called T-kriging. The model compares favourably with most previously defined random field models. The Gaussian random field model appears as a special, limiting case of the T-distributed random field model. The model is particularly useful whenever multiple, sparsely sampled realizations of the random field are available, and is clearly favourable to the Gaussian model in this case. The properties of the T-distributed random field model is demonstrated on well log observations from the Gullfaks field in the North Sea. The predictions correspond to traditional kriging predictions, while the associated prediction variances are more representative, as they are layer specific and include uncertainty caused by using variance estimates.