用于电磁法观测系统开机自检的信号发生器实现方法

针对电磁法观测系统在使用过程中的开机自检要求,分析常用测量系统及地球物理仪器的检测信号特征,通过对已有机制进行研究和对比,结合现有信号产生电路的优势,提出一种功耗低、精度高、设计简单的自检信号发生器实现方案.基于该方案设计了一套实现电路,其以CPLD为核心,由精密参考电压源、模拟开关及运算放大器等器件构成,并对该电路进行仿真与测试.通过系统稳定性分析,采用波特图与奈奎斯特图表明信号发生电路的稳定性符合设计要求.经仿真与测试,能够通过换挡开关产生幅值为20 μV~2 V、频率范围在1 Hz~100 kHz的自检脉冲信号,频率稳定在1%,重复测试相位稳定度小于1.5%,幅值误差可以优化到1%以内,且能通过其稳定的谐波分量来获取该系统带宽更宽的通道测试响应.测试结果表明,该自检信号发生器电路实际功耗小于0.3 W,20 μV~2 V幅值范围和1 Hz~100 kHz频率范围内性能指标的测量结果和仿真结果相符,并成功应用于某监控系统.利用该信号发生器电路实现自检具有操作方便、成本低、易于设计等优点,能够有效的弥补其它自检模式的缺陷.

     

电磁勘探中各向异性研究现状和展望

电各向异性广泛存在于自然界中,已成为电磁勘探资料解释中不可忽视的因素.特别是在一些沉积岩地区,由于层理发育导致地下介质电阻率随电流方向发生变化,表现出很强的各向异性导电性.此时,利用各向同性模型进行电磁数据解释将引起很大的误差.本文回顾了电磁勘探中电各向异性研究的历史,简要介绍电各向异性成因、数值模拟中的数学描述及电各向异性介质中电磁场正反演模拟方法等研究现状,总结电各向异性在大地电磁、可控源电磁、航空电磁和感应测井等方面的最新研究进展及未来的挑战.随着多维电磁数据采集及正反演模拟技术的进步和计算能力的提高,给电各向异性信息提取和应用带来了新的契机.电各向异性研究将在矿产资源勘查、油气存储与运移特征分析、地下水和地热、环境工程地质调查、大地构造及地质灾害预测等方面发挥积极作用.

     

电磁勘探数据粗大误差处理的一种新方法

由于存在各种地电干扰, 电磁法勘探采集到的原始电场数据中往往包含粗大误差.电磁法勘探中信号量的测量与传统的精密测量在误差来源与特点、测量值分布等方面均存在较大差异.经试验, 对电磁勘探采集到的原始电场数据采用传统的莱伊达、格拉布斯、狄克逊等准则进行粗大误差的自动判别和剔除, 处理效果不好;采用Robust估计和中值滤波方法, 也不能达到满意的效果;采用手工方式挑拣剔除粗大误差, 处理效率太低, 均不能满足电磁勘探数据预处理的要求.作者提出了一种自适应双向均方差阈值法实现电磁勘探数据粗大误差的自动判别和剔除, 此方法对采集到的原始电场数据样本进行排序后, 采用迭代或递归的方式, 每次均以中点为界分别计算前后两部分数据的均方差, 将较大的一个与预先设置的均方差阈值进行比较, 若其大于阈值, 则判断粗大误差存在于相应的一端, 进而剔除相应端端点位置的数据点;若前后均方差值都小于阈值或样本数量小于3个时算法结束.此方法具有自适应优化、阈值参数化控制、适应小样本数据以及计算简单效率高等特点.大量实验结果表明:在选取均方差阈值在30至90范围内时(经验值), 能够有效地剔除电磁勘探原始电场数据中的粗大误差, 保留最可信数据.目前已在多个实际勘探生产项目中应用此方法处理粗大误差, 取得了令人满意的处理效果.     

Stochastic observation error and uncertainty in water quality evaluation

When evaluating water quality, the influence of physical weight of the observed index is normally taken into account, but the influence of stochastic observation error (SOE) is not adequately considered. Using Monte Carlo simulation, combined with Shannon entropy, the Principle of Maximum Entropy (POME) and Tsallis entropy, this study investigates the influence of stochastic observation error (SOE) for two cases of the observed index: small observation error and large observation error. Randomness and fuzziness represent two types of uncertainties that are deemed significant and should be considered simultaneously when developing or evaluating water quality models. To that end, three models are employed here: two of the models, named as model I and model II, consider both the fuzziness and randomness, and another model, considers only fuzziness. The results from three representative lakes in China show that for all three models, the influence of stochastic observation error (SOE) on water quality evaluation can be significant irrespective of whether the water quality index has a small observation error or a large observation error. Furthermore, when there is a significant difference in the accuracy of observations, the influence of stochastic observation error (SOE) on water quality evaluation increases. The water quality index whose SOE is minimum determines the results of evaluation.     

A comparative study of Monte Carlo simple genetic algorithm and noisy genetic algorithm for cost-effective sampling network design under uncertainty

This study evaluates and compares two methodologies, Monte Carlo simple genetic algorithm (MCSGA) and noisy genetic algorithm (NGA), for cost-effective sampling network design in the presence of uncertainties in the hydraulic conductivity (K) field. Both methodologies couple a genetic algorithm (GA) with a numerical flow and transport simulator and a global plume estimator to identify the optimal sampling network for contaminant plume monitoring. The MCSGA approach yields one optimal design each for a large number of realizations generated to represent the uncertain K-field. A composite design is developed on the basis of those potential monitoring wells that are most frequently selected by the individual designs for different K-field realizations. The NGA approach relies on a much smaller sample of K-field realizations and incorporates the average of objective functions associated with all K-field realizations directly into the GA operators, leading to a single optimal design. The efficacy of the MCSGA-based composite design and the NGA-based optimal design is assessed by applying them to 1000 realizations of the K-field and evaluating the relative errors of global mass and higher moments between the plume interpolated from a sampling network and that output by the transport model without any interpolation. For the synthetic application examined in this study, the optimal sampling network obtained using NGA achieves a potential cost savings of 45% while keeping the global mass and higher moment estimation errors comparable to those errors obtained using MCSGA. The results of this study indicate that NGA can be used as a useful surrogate of MCSGA for cost-effective sampling network design under uncertainty. Compared with MCSGA, NGA reduces the optimization runtime by a factor of 6.5.     

Source of error and uncertainty in sheet erosion rates estimated from dendrogeomorphology

Dendrogeomorphology has been used since the 1960s to estimate sheet erosion rates. To date, most efforts have focused on accurately determining the first year of root exposure. However, an adequate methodological approach that takes into consideration the microtopography of the ground surface when estimating sheet erosion rates using dendrogeomorphology has not been proposed. In this study, terrestrial laser scanning (TLS) was used for the first time to examine how changes in microtopography determine the level of certainty in estimates. To this end, highly accurate TLS‐based digital elevation models representing exposed roots and their immediate vicinity were analysed using geographic information system tools. The results indicate that erosion rates calculated using the standard dendrogeomorphic method have been underestimated by up to 29% because the method does not take into account changes to the microtopography caused by the axial and radial pressure of the roots. Another source of uncertainty, which we estimate to be 50%, was also found and is the result of changes in the ground surface microtopography caused by variations in soil roughness. These findings do not invalidate the usefulness of dendrogeomorphology for assessing soil erosion, although they do show the need for correct characterization of the microtopography to guarantee reliability. Copyright © 2015 John Wiley & Sons, Ltd.     

基于GPU混合反演的隧道电阻率超前探测成像研究

隧道施工期超前探测对于避免突涌水灾害的发生具有重要作用,为满足隧道三维电阻率超前探测快速化解译与成像的要求,本文提出了一种基于GPU并行的蚁群算法与最小二乘方法相结合的混合反演算法.该方法结合线性反演与非线性反演的优点,利用蚁群算法全局搜索能力强的优点为最小二乘反演提供较优的初始模型,以克服最小二乘算法容易陷入局部最优的缺点,提高了隧道三维电阻率反演成像的精度.同时,基于蚁群算法的天然并行性,提出了CUDA环境下的GPU并行策略,实现了三维电阻率反演的快速化成像.其次,开展了基于GPU混合反演的数值算例,与传统最小二乘线性反演进行了对比,基于GPU并行计算的混合反演计算效率得到了显著提高,对含水构造的位置、形态有较好的反映,压制了三维反演的多解性.最后开展了物理模型试验,结果表明基于GPU混合反演探测的低阻异常体与实际含水构造的位置较为相符,发现基于GPU加速的混合反演方法在提高探测精度与加快反演速度方面具有显著优势,为三维电阻率混合反演方法在隧道超前探测实际工程中的应用奠定了基础.     

甘肃金昌金川镍矿SEP系统与国外仪器比对试验

地面电磁探测(SEP)系统在辽宁兴城杨家杖子矿与国外高端仪器对比试验中取得了不错效果.为了检验地面电磁探测(SEP)系统各组成部分在强干扰区中的性能及可靠性,以及由SEP系统各组成部分集成的整体系统的野外实际工作能力,继续在甘肃金川镍矿区,在强干扰背景下开展了与国外先进仪器的比对试验.利用SEP系统和国际高端著名商业仪器系统,通过不同发射机原始曲线、不同接收机原始曲线、反演剖面的对比,表明二者数据一致性较好,SEP系统的抗干扰能力已经和国际先进仪器相当,已经能够胜任各种复杂的勘探任务.     

时空阵列混场源电磁法理论及模拟研究

针对电磁勘探中的混场源输入条件,提出了一种时空阵列混场源电磁勘探方法.假设输入端同时包含天然电磁场源和可控人工场源,输出端进行多站同步观测;基于多输入-多输出系统的分析方法,推导了混场源条件下的时空阵列方程组.提出了系统响应的求解策略,一次性获得所有同步测道对各个场源独立激励时的响应,并分别求取了大地电磁法及可控源电磁法的各种解释参数.在此理论基础上,设计了针对性的施工方案;可控人工场源的选择形式多样,其类型、数量、激励方式及布设位置等不受限制,所有场源的激励可同时进行,无需分步;测区内各测站的布设方式灵活,可根据需要布设单分量测道或多分量测道;同时在测区外布设张量远参考站.利用数值模拟方法,论证了方法的有效性,并与常规方法进行了对比.结果表明,本方法不仅可提高人工场响应的处理精度,还具有一次野外数据采集,可同时获得天然场及人工场电磁响应结果的突出特点,进而提高采集效率,压制噪声影响;本方法集合了天然场源电磁法和人工场源电磁法的优点,为实现不同类型频率域电磁测深方法数据的统一处理提供了思路.

     

Impact of the sampling duration on the uncertainty of averaged velocity measurements with acoustic instruments

Average velocity in streams is a key variable for the analysis and modelling of hydrological and hydraulic processes underpinning water resources science and practice. The present study evaluates the impact of the sampling duration on the quality of average velocity measurements acquired with contemporary instruments such as Acoustic Doppler Velocimeters (ADV) an Acoustic Doppler Current Profilers (ADCP). The evaluation combines considerations on turbulent flows and principles and configurations of acoustic instruments with practical experience in conducting customized analysis for uncertainty analysis purposes. The study sheds new insights on the spatial and temporal variability of the uncertainty in the measurement of average velocities due to variable sampling durations acting in isolation from other sources of uncertainties. Sampling durations of 90 and 150 s are found sufficient for ADV and ADCP, respectively, to obtain reliable average velocities in a flow affected only by natural turbulence and instrument noise. Larger sampling durations are needed for measurements in most of the natural streams exposed to additional sources of data variability.