煤层气开发中的层间矛盾问题——以柳林地区为例   总被引：2，自引：0，他引：2  

孟艳军  汤达祯  许浩  张文忠  陈同刚 《煤田地质与勘探》2013,41(3):29

直井分层压裂及合层排采能有效降低煤层气勘探开发成本,提高煤层气产能,但层间矛盾的干扰制约了这一排采工艺的推广。借鉴常规油气层间矛盾问题相关理论,首次提出并总结了煤层气开发中层间矛盾的概念、特点和影响因素。通过分析柳林地区典型井产能曲线特征,剖析了该区层间矛盾的特征和原因。结果表明:柳林地区合层排采太原组煤层（8号+9号）和合层排采山西组与太原组煤层（3号+4号+5号与8号+9号）时,层间矛盾问题严重;引起该层间矛盾的原因有煤层物性特征和煤层顶底板水文地质条件因素,其中8号煤层顶板水文地质条件是引发该区层间矛盾的主要因素。   相似文献   

北京市门头沟区某公路岩质边坡稳定性分级研究          下载免费PDF全文

郭松峰  祁生文  李星星  邹宇  廖海军  张世殊 《中国地质调查》2016,3(3):55-61

北京市门头沟区某公路岩质边坡数量多,边坡物理力学性质及其影响因素复杂多变,无法获取每个边坡岩体的物理力学参数,因此,对大量边坡进行力学稳定性分析十分困难。采用层次分析和模糊综合评价方法,根据各种因素对岩质边坡稳定性影响的定性分析,确定了2级4类共9个边坡稳定性影响因子,将边坡的稳定性级别划分为4级,即稳定、基本稳定、较不稳定和不稳定; 然后,构建了隶属度矩阵和权重矩阵; 最后,对每个边坡的稳定性进行模糊综合评价。分析结果表明,在所研究的113个边坡中,不稳定边坡3个,占总边坡的3%,较不稳定边坡27个,占24%,基本稳定边坡52个,占46%,稳定边坡31个,占27%。因此认为: 当边坡数量众多、边界条件模糊、影响因素复杂时,模糊综合评判是比较合适的边坡稳定性分析方法; 应用最大隶属度原则时,需根据各种因素对边坡稳定性影响的因果关系,对最大隶属度原则的有效性进行评估,以防出现评判失效。  相似文献   

我国1小时雨强的时空分布特征   总被引：12，自引：3，他引：9  

姚莉  李小泉  张立梅 《气象》2009,35(2):80-87

基于我国1991-2005年485站高时间分辨率的雨强资料,利用概率分布与统计检验等方法,分析了其时空分布特征,并将雨强分为>1mm·h-1、>2mm·h-1、>4mm·h-1、>8mm·h-1四个级别,探讨了各级别雨强的年平均发生频率、日变化和极端降水等问题.结果表明:雨强的日变化具有明显的地区差异,其中西南和华南地区日变化最为明显.1小时最大雨强50年和100年重现期初步估算值的空间分布形态具有一致性,高值区主要在东南沿海一带,其中百年一遇的1小时雨强达100～150mm·h-1.  相似文献   

新疆渭干河流域地下水三维流数值模拟   总被引：2，自引：0，他引：2  

黎明  陈崇希  张明江 《地质科技情报》2005,24(1):74-78

采用任意多边形网格有限差分法求解模型,根据地下水水头长观资料识别模型的水文地质参数,建立了含混合井孔的6层模拟系统的地下水三维不稳定流模型来刻画渭干河流域地下水流动的基本规律.运用识别后的模型进行了地下水资源评价,预测了未来10 a不同开采条件下的地下水动态变化,探讨了地下水资源的合理开发模式,提出在以蒸发排泄为主的条件下,应在保证生态用水的前提下最大限度地夺取无效蒸发.  相似文献   

Coastal Wave Height Prediction using Recurrent Neural Networks (RNNs) in the South Caspian Sea     

Tayeb Sadeghifar  Maryam Nouri Motlagh  Massoud Torabi Azad  Mahdi Mohammad Mahdizadeh 《Marine Geodesy》2017,40(6):454-465

The prediction of wave parameters has a great significance in the coastal and offshore engineering. For this purpose, several models and approaches have been proposed to predict wave parameters, such as empirical, soft computing, and numerical based approaches. Recently, soft computing techniques such as recurrent neural networks (RNN) have been used to develop sea wave prediction models. In this study, the RNN for wave prediction based on the data gathered and the measurement of the sea waves in the Caspian Sea, in the north of Iran is used for this study. The efficiency of RNNs for 3, 6, and 12 hourly and diurnal wave prediction using correlation coefficients is calculated to be 0.96, 0.90, 0.87, and 0.73, respectively. This indicates that wave prediction by using RNNs yields better results than the previous neural network approaches.  相似文献   

Quantifying a critical marl thickness for vertical fracture extension using field data and numerical experiments     

《地学前缘(英文版)》2019,10(6):2135-2145

In fractured reservoirs characterized by low matrix permeability,fracture networks control the main fluid flow paths.However,in layered reservoirs,the vertical extension of fractures is often restricted to single layers.In this study,we explored the effect of changing marl/shale thickness on fracture extension using comprehensive field data and numerical modeling.The field data were sampled from coastal exposures of Liassic limestone-marl/shale alternations in Wales and Somerset(Bristol Channel Basin,UK).The vertical fracture traces of more than 4000 fractures were mapped in detail.Six sections were selected to represent a variety of layer thicknesses.Besides the field data also thin sections were analyzed.Numerical models of fracture extension in a two-layer limestone-marl system were based on field data and laboratory measurements of Young's moduli.The modeled principal stress magnitude σ_3 along the lithological contact was used as an indication for fracture extension through marls.Field data exhibit good correlation(R~2=0.76) between fracture extension and marl thickness,the thicker the marl layer the fewer fractures propagate through.The model results show that almost no tensile stress reaches the top of the marl layer when the marls are thicker than 30 cm.For marls that are less than 20 cm,the propagation of stress is more dependent on the stiffness of the marls.The higher the contrast between limestone and marl stiffness the lower the stress that is transmitted into the marl layer.In both model experiments and field data the critical marl thickness for fracture extension is ca.15-20 cm.This quantification of critical marl thicknesses can be used to improve predictions of fracture networks and permeability in layered rocks.Up-or downsampling methods often ignore spatially continuous impermeable layers with thicknesses that are under the detection limit of seismic data.However,ignoring these layers can lead to overestimates of the overall permeability.Therefore,the understanding of how fractures propagate and terminate through impermeable layers will help to improve the characterization of conventional reservoirs.  相似文献   

Prediction of Displacements in Unstable Areas Using a Neural Model     

E. Binaghi  M. Boschetti  P.A. Brivio  I. Gallo  F. Pergalani  A. Rampini 《Natural Hazards》2004,32(1):135-154

In pipeline management the accurate prediction of weak displacements is a crucial factor in drawing up a prevention policy since the accumulation of these displacements over a period of several years can lead to situations of high risk. This work addresses the specific problem related to the prediction of displacements induced by rainfall in unstable areas, of known geology, and crossed by underground pipelines. A neural model has been configured which learns of displacements from instrumented sites (where inclinometric measurements are available) and is able to generalise to other sites not equipped with inclinometers.  相似文献   

Evaluation of Interpolation Accuracy of Neural Kriging with Application to Temperature-Distribution Analysis   总被引：8，自引：0，他引：8  

Katsuaki Koike  Setsuro Matsuda  Bin Gu 《Mathematical Geology》2001,33(4):421-448

An interpolation method based on a multilayer neural network (MNN), has been examined and tested for the data of irregular sample locations. The main advantage of MNN is in that it can deal with geoscience data with nonlinear behavior and extract characteristics from complex and noisy images. The training of MNN is used to modify connection weights between nodes located in different layers by a simulated annealing algorithm (one of the optimization algorithms of the network). In this process, three types of errors are considered: differences in values, semivariograms, and gradients between sample data and outputs from the trained network. The training is continued until the summation of these errors converges to an acceptably small value. Because the MNN trained by this learning criterion can estimate a value at an arbitrary location, this method is a form of kriging and termed Neural Kriging (NK). In order to evaluate the effectiveness of NK, a problem on restoration ability of a defined reference surface from randomly chosen discrete data was prepared. Two types of surfaces, whose semivariograms are expressed by isotropic spherical and geometric anisotropic gaussian models, were examined in this problem. Though the interpolation accuracy depended on the arrangement pattern of the sample locations for the same number of data, the interpolation errors of NK were shown to be smaller than both those of ordinary MNN and ordinal kriging. NK can also produce a contour map in consideration of gradient constraints. Furthermore, NK was applied to distribution analysis of subsurface temperatures using geothermal investigation loggings of the Hohi area in southwest Japan. In spite of the restricted quantity of sample data, the interpolation results revealed high temperature zones and convection patterns of hydrothermal fluids. NK is regarded as an interpolation method with high accuracy that can be used for regionalized variables with any structure of spatial correlation.  相似文献   

磁共振扫描对鼻咽癌放疗后局部复发与纤维化的鉴别诊断   总被引：2，自引：0，他引：2  

陈燕萍  黄其鎏 《CT理论与应用研究》1994,3(1):6-8

本文对３２例鼻咽癌病人进行了Ｇｄ－ＤＴｈＡ增强前后磁共振成像（ＭＲＩ）检查。放疗后局部肿瘤复发（ＲＮＰＣ），纤维化（ＲＦ）的病例。结果表明；Ｇｄ－ＤＴＰＡＭＲ增强扫描下加权像能够提高病块与周围结构的区别。副鼻窦及鼻咽部粘膜看明显的强化作用。ＮＰＣ及ＲＮＰＣ皆为轻度到中等度均匀或四块状强化，ＲＦ组一般无强化，但有５例３８．５％呈轻度索条状强化，且多发生于放疗后间隔时间小于１年内者，ＲＮＰＣ与ＲＦ两组的强化率平均值有显著差别（Ｐ＜０．０５），虽其Ｘ±ＳＤ有部分重叠，但如能结合病灶强化程度和强化形式，对ＲＮＰＣ与ＲＦ的鉴别可提供重要信息．  相似文献