碳酸盐岩气藏岩电参数试验研究

为了提高储层参数的精度,针对某区块碳酸盐岩岩心开展试验研究,根据试验分析结果提供更为准确的测井资料解释模型.讨论在不同含水饱和度及围压条件下岩心电阻率的变化规律,并探讨围压对岩心电阻率的影响机理.     

土石坝渗漏的波速-电阻率联合成像诊断试验研究

采用模型试验对3种不同渗漏类型的病险土石坝分别进行了波速-电阻率联合成像诊断试验。试验结果表明,采用电阻率成像诊断坝体的渗漏范围具有较高的精度,但在圈定心墙的渗漏通道时,由成像获得的电阻率异常区域较实际渗漏通道大;采用波速成像诊断坝体的渗漏范围时,诊断效果取决于含水率的变化幅度,含水率变化较小的区域,精度较低,但在圈定心墙渗漏通道时,波速成像却具有较高的精度。因此在土石坝渗漏诊断中,采用单一的电阻率成像或波速成像都具有一定局限性,而联合电阻率和波速成像可以有效提高坝体渗漏区域和心墙渗漏通道的诊断精度。     

高职电气自动化专业校企合作模式的探索与实践

建立可持续双赢的校企合作模式是高职院校专业建设和人才培养的重要课题。以常州信息职业技术学院电气自动化技术专业实践为例,介绍"企—校—企"三轴联动校企合作模式的内涵、举措和实施成效,学校作为主体与两类企业开展不同内容和形式的合作,有力地促进专业人才培养质量和社会服务水平。     

跨孔超高密度电法CT在岩溶勘察中的应用

常用电阻率法的空间效应和视电阻率拟断面记录点对应深度方面的不确定性,以及对场地的要求随深度增加而增加,而分辨率却下降等等制约因素,使其工程应用受到限制,尤其是在解决孔与孔之间的电阻率情况更是一筹莫展。本文所推荐的跨孔超高密度电法是根据电场的基本理论和地震CT勘探的原理,提出了利用在平行钻孔中布设电极、然后利用一孔的两个电极供电、其余的电极同时测量的一种电法测量方式;它不仅比较准确地解决了孔与孔之间的电阻率问题,对场地无太大要求且施工较方便;本文通过对清远伦洲大桥18#、19#桥墩内岩溶发育情况进行电阻率的测试,充分证明该技术在解决此类问题的有效性和准确性。     

提高除尘效率的最佳温度控制系统的研究

为了提高除尘效率,使高压静电除尘器的收尘环境保持在140~150℃的温度区间内,以S7-200为核心,采用变速积分PID算法组成PLC温度控制系统,根据设定值偏差大小,改变积分项的累加速度,结果大大减少了超调量,使控制精度保持在±0.5℃范围内,增加了系统的稳定性.经过Matlab仿真与实际测试,验证该算法在电除尘器高温控制环节有良好的控制性能.     

突出尖锐边界的高密度电阻率反演方法

在高密度电法等工程地球物理实践中,往往采用传统的如最小二乘等光滑反演手段,对其它反演方法及先验信息的利用考虑得较少.本文针对地下电性异常存在尖锐边界的地质体,将传统最小二乘光滑反演和不常用的迭代重加权尖锐反演结果进行了对比分析,通过针对性模型试验和实际资料处理,证明在解决该类地质问题时通过采用合理的反演手段和方法,可达到增加反演精度,突出电性目标和便于地质解释的目的.     

大港油田盐水泥浆测井影响分析研究

结合歧北斜坡地区的地层水性质,借鉴多口盐水泥浆井的测井资料及试油结果,利用泥浆侵入后非储集层比储集层更能准确反映地层信息,提出通过建立储集层深浅电阻率与邻近非储集层段电阻率的相关关系以及储集层径向电阻率差异的方法识别流体类型.在建立地区盐水泥浆井的油气识别图版标准的基础上,将电阻率比值法评价储层流体实现软件模块化,并挂接到Lead3.0软件上进行应用.     

地下瞬变电磁法全区视电阻率二分搜索算法

全空间全区视电阻率的求解方法是地下瞬变电磁理论研究的重要组成部分,为探讨二分搜索算法在井下资料处理中的适用性和精确性,将地面瞬变电磁法二分搜索算法引入至地下,并采用理论数据和实测数据进行对比分析。结果发现,全空间感应电动势随着电阻率增大具有单调递减规律,满足采用二分法求解的前提条件;全区视电阻率二分搜索算法具有较高的精确性,与全空间电阻率的最大误差仅为0.032%,且计算过程稳定、快速,单测点计算仅需十几秒钟便可获得唯一解。研究成果将为地下瞬变电磁法资料解释提供更多参考。     

Fuzzy-Pareto-dominance driven possibilistic model based planning of electrical distribution systems using multi-objective particle swarm optimization

This paper presents a fuzzy-Pareto dominance driven possibilistic model based planning of electrical distribution systems using multi-objective particle swarm optimization (MOPSO). This multi-objective planning model captures the possibilistic variations of the system loads using a fuzzy triangular number. The MOPSO based on the Pareto-optimality principle is used to obtain a set of non-dominated solutions representing different network structures under uncertainties in load demands and these non-dominated solutions are stored in an elite archive of limited size. Normally, choosing the candidate non-dominated solutions to be retained in the elite archive while maintaining the quality of the Pareto-approximation front as well as maintaining the diversity of solutions on this front is very much computationally demanding. In this paper, the principles of fuzzy Pareto-dominance are used to find out and rank the non-dominated solutions on the Pareto-approximation front. This ranking in turn is used to maintain the elite archive of limited size by discarding the lower ranked solutions. The two planning objectives are: (i) minimization of total installation and operational cost and (ii) minimization of risk factor. The risk factor is defined as a function of an index called contingency-load-loss index (CLLI), which captures the effect of load loss under contingencies, and the degree of network constraint violations. The minimization of the CLLI improves network reliability. The network variables that are optimized are: (i) number of feeders and their routes, and (ii) number and locations of sectionalizing switches. An MOPSO (developed by the authors), based on a novel technique for the selection and assignment of leaders/guides for efficient search of non-dominated solutions, is used as the optimization tool. The proposed planning approach is validated on a typical 100-node distribution system. Performance comparisons between the planning approaches with the possibilistic and deterministic load models are provided highlighting the relative merits and demerits. It is also verified that the proposed solution ranking scheme based on the fuzzy-Pareto dominance is very much better from both quality and computational burden point of view in comparison with the other well-known archive truncation techniques based on clustering and solution density measurement etc.