钻屑温度测试煤体法向应力的试验研究

针对煤体法向应力测试问题,基于煤体法向应力的变化引起钻屑温度改变的实际,通过实验室实验,研究了钻屑温度与煤体法向应力的对应关系。实验研究结果表明:在一定范围内,煤体法向应力不同而其余实验条件相同的情况下钻屑温度随着煤体法向应力的增大而升高;钻头温度最大值、钻头温度上升速率、钻孔温度、煤屑温度与煤体法向应力基本呈线性关系。实验方法可用于测试煤体法向应力水平变化,为预测煤层冲击地压危险性提供新的思路。     

黄河流域煤矿区生态环境修复关键技术与战略思考

蒙陕接壤区煤炭高强度开采诱发的煤层顶板水害问题日益凸显,高效智能地判别煤层顶板涌水水源是顶板水害防治的关键。以蒙陕接壤区3个典型矿井为研究对象,将无机指标K⁺+Na⁺、Ca²⁺、Mg²⁺、Cl⁻、SO₄ ²⁻、HCO₃ ⁻、TDS和有机指标UV₂₅₄、TOC、溶解性有机质(DOM)的荧光光谱作为判别指标,利用主成分分析法(PCA)对80组地下水水样数据进行主成分提取,提出一种人工鱼群算法(AFSA)改进随机森林(RF)的PCA-AFSA-RF顶板涌水水源智能判别方法。首先,建立PCA-RF判别模型,其准确率(A_c)、精确率(P_r)、召回率(R_c)和F-measure指数(f₁)分别达到了83.00%、83.17%、80.42%和79.57%;其次,通过AFSA对PCA-RF判别模型中决策树数目、树深和内部节点分裂所需的最小样本数进行寻优,在AFSA中引入遗传机制以避免陷入局部最优,建立基于PCA-AFSA-RF的煤层顶板涌水水源智能判别模型,该模型A_c、P_r、R_c、f₁分别达到92.18%、91.11%、87.58%和88.82%,较PCA-RF分别提高9.18%、7.94%、7.16%和9.25%,回代准确率达到97.50%;最后,利用该模型对12个矿井水水样进行判别,结果与现场实际相一致,表明AFSA改进后的PCA-RF模型具有更好的准确性和泛化能力。研究结果可为煤层顶板涌水水源的准确判别提供新方法。

     

鄂尔多斯盆地靖边西部油区延安组延9油层组储层特征分析

延9油层组的发现,极大拓宽了勘探开发面积,为靖边油田增储上产的主力层系。在勘探开发过程中发现,应用同样的技改措施(压裂、注水等),延9油层组在南北地区呈现出不同的储层改造响应。延9油层组以河湖过渡相沉积为主,受物源、搬运距离与水动力等因素的影响,在研究区南北区块呈现出不同的岩性特征。研究发现,北区延9储层以次长石砂岩和长石砂岩为主,碎屑含量较高(82.0%~89.5%),以石英、长石为主,杂基主要由高岭石、云母和粉砂岩组成,胶结物主要由铁白云石、硅质等组成;南区以岩屑长石砂岩和长石砂岩为主,碎屑含量较高(83.0%~91.0%),以石英为主,其次为长石、岩屑、云母和少量的重矿物,杂基主要为高岭石,胶结物为硅质和碳酸盐岩。整体上,研究区内延9储层孔渗性较好,是较好的储层。由于碎屑与胶结物类型及其含量的不同,在后期开发过程中要区分对待,避免储层受到污染与损坏。     

含底坡项浅水方程的一种数值求解方法

激波捕捉格式能处理含强间断的浅水方程,因为必须采用关于守恒变量的守恒形式方程,作为水流实际驱动力的水位梯度项被分解为压力梯度项和底坡项,如果离散格式不能很好地平衡这两项的作用,将导致不准确的结果。基于理论推导,提出了一种新方法,在单元内部采用非守恒形式,保留水位梯度项,在界面处采用守恒格式捕捉间断。利用4个具有代表性的算例对提出的方法进行了验证,结果表明,该方法能够处理变化地形上的强间断和流态变化,并能够准确捕捉扰动的传播过程。     

四川地区首次深层搅拌法地基处理

在成都东部台地区域针对局部范围内的粘土、淤泥质粉质粘土等土层采用了深层搅拌及CFG桩法进行处理,通过对比,深层搅拌法明显存在优越性。通过该项目的介绍,为四川地区以后深层搅拌施工提供借鉴和指导。     

四川省珙县金堂煤矿区煤层对比研究

煤层对比是一项基础地质工作,对研究煤田沉积环境和聚煤规律,指导煤矿生产,具有重要的理论和现实意义。针对金堂煤矿区煤层的具体情况,采用多种方法对各煤层进行对比研究,揭示煤层赋存规律。     

http://www.sciencedirect.com/science/article/pii/S167498711200031X

Upper Paleozoic coal measures in the Ordos Basin consist of dark mudstone and coal beds and are important source rocks for gas generation.Gas accumulations include coal-bed methane（CBM）, tight gas and conventional gas in different structural areas.CBM accumulations are mainly distributed in the marginal area of the Ordos Basin,and are estimated at 3.5×10¹² m³.Tight gas accumulations exist in the middle part of the Yishan Slope area,previously regarded as the basin-centered gas system and now considered as stratigraphic lithologic gas reservoirs.This paper reviews the characteristics of tight gas accumulations:poor physical properties(porosity < 8%,permeability < 0.85×10^-3μm²),abnormal pressure and the absence of well-defined gas water contacts.CBM is a self-generation and selfreservoir, while gas derived from coal measures migrates only for a short distance to accumulate in a tight reservoir and is termed near-generation and near-reservoir.Both CBM and tight gas systems require source rocks with a strong gas generation ability that extends together over wide area.However,the producing area of the two systems may be significantly different.     

福建泰宁世界地质公园丹霞红层研究

福建省泰宁世界地质公园以典型的年青期丹霞地貌为其地质特色,丹霞地貌由晚白垩世沙县组和崇安组红层构成。考察确认在金湖风洞一带的崇安组红层底部含较厚的流纹质火山岩夹层,这在福建全省境内是唯一的,从而为确定丹霞红层的准确时代提供了可能。研究表明,崇安组底部的火山岩由两次流纹质岩浆爆发性喷发形成,测得其锆石LAICP-MSU-Pb法年龄为98.52±0.96Ma,说明丹霞红层主体的形成时代为早、晚白垩世之交,而非以往认为的晚白垩世中—晚期,因此对华南丹霞红层的形成时代及其地质背景应重新审视,这一新认识对国内其他以丹霞地貌为特色的地质公园也同样有参考价值。     

Spectral sparse Bayesian learning reflectivity inversion

A spectral sparse Bayesian learning reflectivity inversion method, combining spectral reflectivity inversion with sparse Bayesian learning, is presented in this paper. The method retrieves a sparse reflectivity series by sequentially adding, deleting or re‐estimating hyper‐parameters, without pre‐setting the number of non‐zero reflectivity spikes. The spikes with the largest amplitude are usually the first to be resolved. The method is tested on a series of data sets, including synthetic data, physical modelling data and field data sets. The results show that the method can identify thin beds below tuning thickness and highlight stratigraphic boundaries. Moreover, the reflectivity series, which is inverted trace‐by‐trace, preserves the lateral continuity of layers.     

Impact of discretization methods on the rough set-based classification of remotely sensed images

Abstract

In recent years, the rough set (RS) method has been in common use for remote-sensing classification, which provides one of the techniques of information extraction for Digital Earth. The discretization of remotely sensed data is an important data preprocessing approach in classical RS-based remote-sensing classification. Appropriate discretization methods can improve the adaptability of the classification rules and increase the accuracy of the remote-sensing classification. To assess the performance of discretization methods this article adopts three indicators, which are the compression capability indicator (CCI), consistency indicator (CI), and number of the cut points (NCP). An appropriate discretization method for the RS-based classification of a given remotely sensed image can be found by comparing the values of the three indicators and the classification accuracies of the discretized remotely sensed images obtained with the different discretization methods. To investigate the effectiveness of our method, this article applies three discretization methods of the Entropy/MDL, Naive, and SemiNaive to a TM image and three indicators for these discretization methods are then calculated. After comparing the three indicators and the classification accuracies of the discretized remotely sensed images, it has been found that the SemiNaive method significantly reduces large quantities of data and also keeps satisfactory classification accuracy.