基于时频稀疏性分析法的低信噪比微震事件识别与恢复

微震监测是直观评价压裂过程和压裂效果的有效手段.微震事件识别是微震监测的首要步骤.然而对于低信噪比微震监测数据,常规识别方法很难取得满意效果.基于微震事件在时频域中的稀疏性,本文提出利用Renyi熵值表示微震监测数据的时频稀疏程度,并以时频距离为约束条件,建立以低熵值的道数为判别阈值的目标函数.本文方法能在识别出微震事件的同时,恢复出较为清晰的微震事件.通过数值计算和对实际监测数据的测试,表明该方法对低信噪比的微震监测数据有较好的处理效果.     

烈度计台站远程监控系统

烈度计台站在地震预警中具有重要作用，对烈度计台站的远程监控是保证观测数据稳定可靠的前提。针对现有监控系统无法对台站供电、网络、设备状态等信息进行智能监控的问题，设计烈度计台站远程监控系统，实现对台站供电、网络、I/O开关量、烈度计状态等信息的采集及远程控制等功能，并在天津烈度计台网进行部署，提高了故障排查及维护效率，保证了烈度计台站数据的连续率。     

Full‐waveform based microseismic event detection and signal enhancement: An application of the subspace approach

Microseismic monitoring has proven invaluable for optimizing hydraulic fracturing stimulations and monitoring reservoir changes. The signal to noise ratio of the recorded microseismic data varies enormously from one dataset to another, and it can often be very low, especially for surface monitoring scenarios. Moreover, the data are often contaminated by correlated noises such as borehole waves in the downhole monitoring case. These issues pose a significant challenge for microseismic event detection. In addition, for downhole monitoring, the location of microseismic events relies on the accurate polarization analysis of the often weak P‐wave to determine the event azimuth. Therefore, enhancing the microseismic signal, especially the low signal to noise ratio P‐wave data, has become an important task. In this study, a statistical approach based on the binary hypothesis test is developed to detect the weak events embedded in high noise. The method constructs a vector space, known as the signal subspace, from previously detected events to represent similar, yet significantly variable microseismic signals from specific source regions. Empirical procedures are presented for building the signal subspace from clusters of events. The distribution of the detection statistics is analysed to determine the parameters of the subspace detector including the signal subspace dimension and detection threshold. The effect of correlated noise is corrected in the statistical analysis. The subspace design and detection approach is illustrated on a dual‐array hydrofracture monitoring dataset. The comparison between the subspace approach, array correlation method, and array short‐time average/long‐time average detector is performed on the data from the far monitoring well. It is shown that, at the same expected false alarm rate, the subspace detector gives fewer false alarms than the array short‐time average/long‐time average detector and more event detections than the array correlation detector. The additionally detected events from the subspace detector are further validated using the data from the nearby monitoring well. The comparison demonstrates the potential benefit of using the subspace approach to improve the microseismic viewing distance. Following event detection, a novel method based on subspace projection is proposed to enhance weak microseismic signals. Examples on field data are presented, indicating the effectiveness of this subspace‐projection‐based signal enhancement procedure.     

Passive (Micro-) Seismic Event Detection by Identifying Embedded “Event” Anomalies Within Statistically Describable Background Noise

Among engineers there is considerable interest in the real-time identification of “events” within time series data with a low signal to noise ratio. This is especially true for acoustic emission analysis, which is utilized to assess the integrity and safety of many structures and is also applied in the field of passive seismic monitoring (PSM). Here an array of seismic receivers are used to acquire acoustic signals to monitor locations where seismic activity is expected: underground excavations, deep open pits and quarries, reservoirs into which fluids are injected or from which fluids are produced, permeable subsurface formations, or sites of large underground explosions. The most important element of PSM is event detection: the monitoring of seismic acoustic emissions is a continuous, real-time process which typically runs 24?h a day, 7?days a week, and therefore a PSM system with poor event detection can easily acquire terabytes of useless data as it does not identify crucial acoustic events. This paper outlines a new algorithm developed for this application, the so-called SEED? (Signal Enhancement and Event Detection) algorithm. The SEED? algorithm uses real-time Bayesian recursive estimation digital filtering techniques for PSM signal enhancement and event detection.     

Drought monitoring

Drought detection, monitoring and indices are closely related to its definition. The specific definition chosen for a particular drought analysis will affect the procedures one uses in drought detection and monitoring. The traditional Palmer Drought Severity Index (PDSI) has been proven to be ineffective in regions of predominantly irrigated agriculture.The recently developed ALERT (Automated Local Evaluation in Real Time) system is proposed for use in monitoring the spatial and temporal variations of drought in real time. The ALERT system uses standardized instruments, radio frequencies, software and hardware. It was originally developed as a flash flood waming system by local flood control districts and the National Weather Service. However, now it has expanded to over 100 other uses in the areas of natural and man-made disaster detection and warning. The successful ALERT system indicates the need for the continued development of a national drought monitoring index that is applicable to a wide range of climate, hydrologic and water resource environments.     

Early detection of brine and CO2 leakage through abandoned wells using pressure and surface-deformation monitoring data: Concept and demonstration

In this paper, we develop a methodology for early detection of potential CO₂ leakage from geological storage formations using pressure and surface-deformation anomalies. The basic idea is based on the fact that leakage-induced pressure signals travel much faster than the migrating CO₂; thus such anomalies may be detected early enough for risk management measures taking effect in avoiding substantial CO₂ leaks. The early detection methodology involves automatic inversion of anomalous brine leakage signals with efficient forward pressure and surface-deformation modeling tools to estimate the location and permeability of leaky features in the caprock. We conduct a global sensitivity analysis to better understand under which conditions pressure anomalies can be clearly identified as leakage signals, and evaluate signal detectability for a broad parameter range considering different detection limits and levels of data noise. The inverse methodology is then applied to two synthetic examples of idealized two-aquifer-and-one aquitard storage systems, with an injection well and a leaky well, for different monitoring scenarios. In Example 1, only pressure data at the monitoring and injection wells are used for leakage detection. Our results show that the accuracy of leakage detection greatly depends on the level of pressure data noise. In Example 2, joint inversion of pressure and surface-deformation measurements significantly improves the speed of convergence toward the true solution of the leakage parameters and enables early leakage detection. In both examples, successful detection is achieved when two monitoring wells are appropriately placed within up to 4 km from the leaky well.     

电磁卫星地震应用进展及未来发展思考

法国DEMETER(Detection of Electro-Magnetic Emissions Transmitted from Earthquake Regions)卫星是世界上第一颗专门针对地震电离层扰动监测的电磁卫星, 于2004年发射, 2010年底结束运行, 共在轨飞行6.5年, 获得3万多条整轨数据, 为地震监测及电离层物理研究提供了坚实的数据基础。 全球科学家利用这颗卫星的数据开展了大量的地震应用研究, 发表文章上百篇, 将电磁卫星的地震应用研究推向了新的阶段。 中国第一颗电磁监测试验卫星CSES(China Seismo-Electromagnetic Satellite)于2018年2月2日成功发射, 目前已完成在轨测试并交付使用, 科学数据也已正式对外发布。 如何充分发挥CSES卫星的应用效能, 将空间电磁监测向业务化运行转化, 总结和思考DEMETER卫星的技术进步、 研究成果及曾经出现过的问题, 十分重要。 因此, 本文着重介绍DEMETER卫星在地震监测应用领域的代表性研究进展, 并结合CSES卫星的设计和运转实践, 对未来空间地震电磁探测及科学研究的发展方向进行一些初步讨论。     

Drought monitoring

Drought detection, monitoring and indices are closely related to its definition. The specific definition chosen for a particular drought analysis will affect the procedures one uses in drought detection and monitoring. The traditional Palmer Drought Severity Index (PDSI) has been proven to be ineffective in regions of predominantly irrigated agriculture.The recently developed ALERT (Automated Local Evaluation in Real Time) system is proposed for use in monitoring the spatial and temporal variations of drought in real time. The ALERT system uses standardized instruments, radio frequencies, software and hardware. It was originally developed as a flash flood waming system by local flood control districts and the National Weather Service. However, now it has expanded to over 100 other uses in the areas of natural and man-made disaster detection and warning. The successful ALERT system indicates the need for the continued development of a national drought monitoring index that is applicable to a wide range of climate, hydrologic and water resource environments.     

New seismic array solution for earthquake observations and hydropower plant health monitoring

We present the novel fusion of seismic safety monitoring data of the hydropower plant in Chirkey (Caucasus Mountains, Russia). This includes new hardware solutions and observation methods, along with technical limitations for three types of applications: (a) seismic monitoring of the Chirkey reservoir area, (b) structure monitoring of the dam, and (c) monitoring of turbine vibrations. Previous observations and data processing for health monitoring do not include complex data analysis, while the new system is more rational and less expensive. The key new feature of the new system is remote monitoring of turbine vibration. A comparison of the data obtained at the test facilities and by hydropower plant inspection with remote sensors enables early detection of hazardous hydrodynamic phenomena.     

Optimizing early detection of non-indigenous species: Estimating the scale of dispersal of a nascent population of the invasive tunicate Ciona intestinalis (L.)

Knowledge of dispersal and establishment during the early stages of invasion is essential for allocating monitoring effort, detecting nascent populations and predicting spread. The scarcity of these data, however, provides little guidance for monitoring programs. Here we present data on the adult distribution and the subsequent pattern of larval recruitment from a nascent population of the invasive tunicate Ciona intestinalis in Prince Edward Island, Canada. Existing niche models indicate the entire study site is suitable for recruitment, suggesting an equal probability of detection throughout the site. In contrast, we found a heterogeneous pattern of larval recruitment, including areas of zero recruitment. By fitting a dispersal kernel, we show Ciona is not capable of naturally dispersing between bays, restricting further spread, and provide guidance for future monitoring. Our results also highlight how large-scale models, although important, lack the small-scale patterns essential for monitoring and early detection of invasive species.     

Biotechnological Advances in Detection of Contaminants from Wastewater

Wastewater from industries causes major environmental pollution problems. The urban development and commercialization in developing countries cause deterioration of surface water resources. Hence, for its improvement, it is essential to develop highly sensitive devices with quick response for monitoring of wastewater contamination. In this respect, biotechnological processes such as biosensors can be promising and a robust option for detection of toxic pollutants. Biosensors can be applied in order to acquire real-time quantitative data. Nowadays, the enzymes or whole cell bio-reporters-based biosensors have promising potential due to the possibility of miniaturization and opportunity for development of in situ biosensors. The growing need of convenient, rapid, and efficient biosensing devices explains the current advancement of biosensors with new transduction materials for multiplexed contaminant detection. Considering the extensive range of sensing strategies including immunochemical-based, enzymatic and nonenzymatic signals, different kinds of biosensors can be classified as electrochemical, optical, thermal, etc. For the past few years, more attention has been paid to nanomaterial-based biosensors which exhibit monitoring on the basis of chemical reactions and biological phenomena. Overall, this review focuses on principle and operation (transduction mechanism) of biosensors based on bio-recognition elements, for the early detection of organic and inorganic contaminants existing in wastewater.     

Long‐range terrestrial laser scanning for geomorphological change detection in alpine terrain – handling uncertainties

Long‐range terrestrial laser scanning (TLS) is an emerging method for the monitoring of alpine slopes in the vicinity of infrastructure. Nevertheless, deformation monitoring of alpine natural terrain is difficult and becomes even more challenging with larger scan distances. In this study we present approaches for the handling of spatially variable measurement uncertainties in the context of geomorphological change detection using multi‐temporal data sets. A robust distance measurement is developed, which deals with surface roughness and areas of lower point densities. The level of detection (LOD), i.e. the threshold distinguishing between real surface change and data noise, is based on a confidence interval considering the spatial variability of TLS errors caused by large laser footprints, low incidence angles and surface roughness. Spatially variable positional uncertainties are modelled for each point according to its range and the object geometry hit. The local point cloud roughness is estimated in the distance calculation process from the variance of least‐squares fitted planes. Distance calculation and LOD assessment are applied in two study areas in the Eastern Alps (Austria) using multi‐temporal laser scanning data sets of slopes surrounding reservoir lakes. At Finstertal, two TLS point clouds of high alpine terrain and scanned from ranges between 300 and 1800 m are compared. At Gepatsch, the comparison is done between an airborne laser scanning (ALS) and a TLS point cloud of a vegetated mountain slope scanned from ranges between 600 and 3600 m. Although these data sets feature different conditions regarding the scan setup and the surface conditions, the presented approach makes it possible to reliably analyse the geomorphological activity. This includes the automatic detection of rock glacier movement, rockfall and debris slides, even in areas where a difference in vegetation cover could be observed. Copyright © 2016 John Wiley & Sons, Ltd.     

中国地球电磁法新进展和发展趋势

本文用有限的篇幅,重点介绍近几年地球电磁法在深部结构探测、能源和资源勘探、环境和工程探查、地震等灾害监测以及新技术和软件等方面的最新发展状况,介绍几个有发展和应用潜力的新电磁技术.     

Improvements in mining induced microseismic source locations at the Lucky Friday mine using an automated whole-waveform analysis system

For years, severe rockburst problems at the Lucky Friday mine in northern Idaho have been a persistent safety hazard and an impediment to production. An MP250 based microseismic monitoring system, which uses simple voltage threshold picking of first arrivals, has been used in this mine since 1973 to provide source locations and energy estimates of seismic events. Recently, interest has been expressed in developing a whole waveform microseismic monitoring system for the mine to provide more accurate source locations and information about source characteristics. For this study, we have developed a prototype whole-waveform microseismic monitoring system based on a 80386 computer equipped with a 50 kHz analog-digital convertor board. The software developed includes a data collection program, a data analysis program, and an event detection program. Whole-waveform data collected and analyzed using this system during a three-day test have been employed to investigate sources of error in the hypocenter location process and to develop an automatic phase picker appropriate for microseismic events.Comparison of hypocenter estimates produced by the MP250 system to those produced by the whole-waveform system shows that significant timing errors are common in the MP250 system and that these errors caused a large part of the scatter evident in the daily activity plots produced at the mine. Simulations and analysis of blast data show that analytical control over the solutions is strongly influenced by the array geometry. Within the geophone array, large errors in the velocity model or moderate timing errors may result in small changes in the solution, but outside the array, the solution is very sensitive to small changes in the data.Our whole-waveform detection program picks event onset times and determines event durations by analysis of a segmented envelope function (SEF) derived from the microseismic signal. The detection program has been tested by comparing its arrival time picks to those generated by human analysis of the data set. The program picked 87% of the channels that were picked by hand with a standard error of 0.75 milliseconds. Source locations calculated using times provided by our entire waveform detection program were similar to those calculated using hand-picked arrival times. In particular, they show far less scatter than source locations calculated using arrival times based on simple voltage threshold picking of first arrivals.     

Detecting Changes in Ground Water Quality at Regulated Facilities

The Resource Conservation and Recovery Act (PL 94–580) and related federal and state legislation have mandated routine monitoring of ground water quality at regulated facilities. The objective of the required monitoring activities is detection of adverse changes in ground water quality caused by the facilities.
Both failure to detect pollution and an incorrect determination of pollution can be very expensive. It is crucial, therefore, that monitoring programs be designed and operated to provide statistically sound information. It is equally important that users of ground water quality data understand the nature and limitations of information from monitoring.
To address the preceding issues, the authors present a general approach to analyzing ground water quality data in light of the stated monitoring objective. The suggested approach accounts for "natural" variation in background water quality through pairing of observations. The limitations of quarterly sampling for detecting small changes in quality over a short time frame are discussed.     

基于物联网的大型地震区域监控系统设计

当前大型地震区域监控系统采用有线网络对人工指挥台进行数据传输,易导致灾害条件下受损无法及时有效地传通监控结果,存在地震实时监测信息准确性低、系统稳定性差的问题。因此设计基于物联网的大型地震区域监控系统。该设计系统进行数据采集交换的网络拓扑采用ZIGBEE实现通信。基于VS.NET基础设计系统架构,通过地震的现场指挥部建设支持可视化的调度指挥台,实现综合调度和集中指挥的目的。系统中智能地震救灾控制中心采用服务器进行数据存储和智能运算,实现对地震检测区的精准、高效检测和工作指导。通过数据采集交换与应急调度平台,监测地震实时监控与设备使用情况。采用地震救灾数据采集分析软件对物联网中地震区域监测数据进行全面、准确分析,系统采用多源信息融合技术实现地震救灾信息多视角的全面处理。实验结果说明,所设计系统测算结果实时性高、功耗低,具有较高的准确度和稳定性。     

中国地震台网监测能力评估和台站检测能力评分(2008—2015年)

针对中国地震台网"十五"项目建成后的地震监测能力科学评估的需求,为进一步优化台网布局、提升边疆海域等重点地区监测能力,本研究利用"基于概率的完整性震级"（PMC）方法,对中国地震台网1001个台站以及2008-10-01-2015-09-17期间实际产出的地震观测资料进行了研究,分析了指定震级档下的检测概率P_E和最小完整性震级M_P的分布.除台网整体监测能力分布外,为直观地用单分值表述逐个台站的地震检测能力,本文发展了基于等振幅曲线的"地震检测能力评分表",给出了国家台和区域台每个台站的地震检测能力评分统计特征和空间分布特征.此外,研究中还采用设定"最佳"地震监测能力目标函数的方式,模拟了通过改进观测条件可获得的地震台网监测能力提升的理论结果.研究结果表明,我国华北和东南沿海等东部地区地震监测能力较高,西部尤其是青藏高原南部地区M_p仅约为4.5,近海海域M_p仅约为3.5;从单个地震台站的运行效益角度,台网运行水平和地震观测资料的分析程度对台站的实际的地震检测能力影响显著,新疆等部分台站稀疏地区地震检测能力较高,而中等台站密度的贵州等部分区域相对较低;国家台的地震检测能力评分D_score系统优于区域台,新疆等西部边疆地区,以及福建等东南沿海地区的D_score明显高于台站密集的东部地区;模拟结果显示,在现有台站布局条件下,通过台站优化改造和提升运维管理水平,可显著提升对内蒙古西部、四川西部、甘肃-青海的北部交界地区、鄂尔多斯地块内部、贵州大部分地区,以及我国近海海域、朝鲜半岛北部和中南半岛北部地区的地震监测能力.     

Quality Assurance in Environmental Monitoring

Over the past decade, there has been a growing awareness of the need for accountable quality assurance (QA) and control in chemical analysis. In environmental monitoring programs, especially those studying metal contaminants at trace and ultratrace concentrations in natural waters, the sampling, sample storage and sample preparation stages prior to analysis, represent potentially greater sources of error than the chemical analysis. The improvements in data reliability and detection limits when appropriate QA is employed, allow meaningful relationships between the measured concentrations and other physical and chemical parameters to be more reliably interpreted. Published data generated from both field and laboratory studies, frequently show no evidence of QA, yet such data are being used to formulate quality guidelines and as the basis for expensive management actions. So that only quality data forms the basis of regulatory action, it is essential that monitoring data not be published without demonstrable evidence of quality practices in all aspects of the monitoring exercise.     

一种基于多相介质理论的油气检测方法研究

目前采用的油气检测方法和技术严格意义上讲都是基于单相介质理论的,而含油气储层是多相介质的,因此,造成了油气检测结果存在多解性和不确定性。本文以BIOT理论和实验室数据为依据,研究出一种快捷的油气检测方法。该方法已在中国塔里木、柴达木、准噶尔等盆地的10多个区块中得到应用,其检测油气的符合率高于现有的其它烃类检测技术。该方法在勘探阶段的油气检测方面和开发阶段油气藏动态监控方面具有广泛的应用前景。     

Bridge health monitoring system based on vibration measurements

A bridge health monitoring system is presented based on vibration measurements collected from a network of acceleration sensors. Sophisticated structural identification methods, combining information from the sensor network with the theoretical information built into a finite element model for simulating bridge behavior, are incorporated into the system in order to monitor structural condition, track structural changes and identify the location, type and extent of damage. This work starts with a brief overview of the modal and model identification algorithms and software incorporated into the monitoring system and then presents details on a Bayesian inference framework for the identification of the location and the severity of damage using measured modal characteristics. The methodology for damage detection combines the information contained in a set of measurement modal data with the information provided by a family of competitive, parameterized, finite element model classes simulating plausible damage scenarios in the structure. The effectiveness of the damage detection algorithm is demonstrated and validated using simulated modal data from an instrumented R/C bridge of the Egnatia Odos motorway, as well as using experimental vibration data from a laboratory small-scaled bridge section.