Laboratory sandbox validation of pollutant source location methods

Inverse methods can be used to recover the pollutant source location from concentration data. In this paper, the relative effectiveness of two proposed methods, simultaneous release function and source location identification (SRSI) and backward probability model based on adjoint state method (BPM-ASM) are evaluated using real data collected by using experimental equipment. The device is a sandbox that reproduces an unconfined aquifer in which all the variables are controlled. A numerical model was calibrated using experimental observations. The SRSI is a stochastic procedure which finds the source location and the release history by means of a Bayesian geostatistical approach (GA). The BPM-ASM provides the backward probability location of the pollutant detected at a monitoring point by means of a reverse transport simulation. The results show that both methods perform well. While the simultaneous release function and SRSI method requires a preliminary delineation of a probable source area and some weak hypotheses about the statistical structure of the unknown release function, the backward probability model requires some hypothesis about the contaminant release time. A case study was performed using two observation points only, and despite the scarcity of data, both methodologies were able to accurately reconstruct the true source location. The GA has the advantage to recover the release history function too, whilst the backward probability model works well with fewer data. If there are many observations, both methodologies may be computationally heavy. A transfer function approach has been adopted for the numerical definition of the sensitivity matrix in the SRSI method. The reliability of the experimental equipment was tested in previous laboratory works, conducted under several different conditions.     

Backward probabilistic model of groundwater contamination in non-uniform and transient flow

Backward location and travel time probabilities, which provide information about the former location of contamination in an aquifer, can be used to identify unknown contamination sources. Backward location probability describes the possible upgradient positions of contamination at a known time in the past, and backward travel time probability describes the time required for contamination to travel from a known upgradient location to an observation point. These probabilities are related to adjoint states of resident concentration, and their governing equation is the adjoint of a forward contaminant transport model. Using adjoint theory to obtain the appropriate governing equation, we extend the backward probability model for conservative solutes to more general non-uniform and transient flow fields. In particular, we address three important extensions, spatially-varying porosity, transient flow and temporally-varying porosity, and internal distributed sources and sinks of solute and water. For the first time we learn that forward and backward location and travel time probabilities are not necessarily equivalent to adjoint states, but are related to them. The extensions are illustrated using a vertically-integrated groundwater model, creating transient flow by a step change in pumping and using areal recharge as an internal distributed source. Both the movement and spread of probabilities are affected. With internal sources of water, there are two interpretations of backward probability, depending on whether or not the source of water is also a source of solute. The results demonstrate how the backward probability model can be applied to other, perhaps more important, non-uniform and transient flow conditions, with time- and space-varying water storage, such as time-varying pumping or unsaturated (or saturated–unsaturated) flow and transport with spatially- and temporally-varying moisture content.     

Numerical implementation of a backward probabilistic model of ground water contamination

Backward location and travel time probabilities can be used to characterize known and unknown sources or prior positions of ground water contamination. Backward location probability describes the position of the observed contamination at some time in the past; backward travel time probability describes the amount of time prior to observation that the contamination was released from its source or was at a particular upgradient location. The governing equation for backward probabilities is the adjoint of the governing equation for contaminant transport, but with new load terms. Numerical codes that have been written to solve the forward equations of contaminant transport, e.g., the advection-dispersion equation, can also be used to solve the adjoint equation for location and travel time probabilities; however, the interpretation of the results is different and some new approximations must be made for the load terms. We present the governing equations for backward location and travel time probabilities, and provide appropriate numerical approximations for these load terms using the cell-centered finite difference method, one of the most popular numerical methods in ground water hydrology. We discuss some additional numerical considerations for the backward model including boundary conditions, reversal of the flow field, and interpretation of the results. We illustrate the implementation of the backward probability model using hypothetical examples in one- and two-dimensional domains. We also present a three-dimensional application of a pump-and-treat remediation capture zone delineation at the Massachusetts Military Reservation. The illustrations are performed using MODFLOW-96 for flow simulations and MT3DMS for transport simulations.     

Variations of the specific barrier model—part II: effect of isochron distributions

The specific barrier model (SBM) is a particular case of a composite earthquake source model where the seismic moment is distributed in a deterministic manner on a rectangular fault plane on the basis of moment and area constraints. It is assumed that the fault surface is composed of an aggregate of subevents of equal diameter, the ‘barrier interval’. Furthermore, the subevents are assumed to rupture randomly and statistically independent of one another as the rupture front sweeps the fault plane. In the formulation of the far-field source spectrum of the SBM the ‘arrival time’ of the seismic radiation emitted by each subevent is specified via a probability density function (PDF). In the SBM the subevents are assumed to be of equal sizes (an assumption relaxed in a companion paper, referred to as Part I) and the PDF of ‘arrival times’ is assumed to be uniform. In this study we investigate the effects of different PDFs of ‘arrival times’ on the far-field source spectrum of the SBM. Different PDFs of ‘arrival times’ affect the source spectra primarily at the intermediate frequency range (between the first and second corner frequencies). Such effects become more pronounced as the earthquake magnitude increases. The far-field spectrum of seismic energy observed/recorded at a site depends on the location of the site relative to the causative fault plane, the location of rupture initiation (hypocenter) and the onset times of the rupturing subevents. All the above factors are effectively taken into account by the ‘isochrons’, which vary with source-site geometry. We investigate the selection of the appropriate PDF of seismic energy arrival times at a given site by computing isochrons for a grid of stations surrounding the earthquake fault, represented by the SBM. We show that only for stations located in a direction normal to the fault plane is the assumption of uniform PDF of ‘arrival times’ valid. At other sites non-uniform PDFs of ‘arrival times’ are observed. We identify and categorize the prevalent types of PDFs by directivity (forward vs. backward vs. neutral) and source-site distance (near-fault vs. far-field), show examples in which we group the stations accordingly. We investigate the effects of the different PDF-groups on the SBM source spectrum. Selection of the appropriate PDF for a given source-site configuration when simulating strong ground motions using the SBM in the context of the stochastic method is expected to yield more self-consistent, and physically realistic simulations.     

Joint probability density function of the stochastic responses of nonlinear structures

The joint probability density fimction （PDF） of different structural responses is a very important topic in the stochastic response analysis of nonlinear structures. In this paper, the probability density evolution method, which is successfully developed to capture the instantaneous PDF of an arbitrary single response of interest, is extended to evaluate the joint PDF of any two responses. A two-dimensional partial differential equation in terms of the joint PDF is established. The strategy of selecting representative points via the number theoretical method and sieved by a hyper-ellipsoid is outlined. A two-dimensional difference scheme is developed. The free vibration of an SDOF system is examined to verify the proposed method, and a flame structure exhibiting hysteresis subjected to stochastic ground motion is investigated. It is pointed out that the correlation of different responses results from the fact that randomness of different responses comes from the same set of basic random parameters involved. In other words, the essence of the probabilistic correlation is a physical correlation.     

地震台站台基噪声功率谱概率密度函数Matlab实现

选取2015年四川数字测震台网中筠连和华蓥山地震台记录的垂直分向连续波形数据,利用Matlab软件,计算地震台站台基噪声功率谱概率密度函数,分析地震台站环境噪声特征。结果表明,台站环境噪声功率谱密度概率密度分布对地震事件波形（体波、面波）、人为噪声（台站周围人为活动、车辆及机器噪声等高频干扰）、系统瞬变（数据丢失、地震计小故障）以及仪器标定信号等反映较好。使用台基噪声功率谱概率密度函数方法,有利于监测地震台站数据记录,提高观测数据质量。     

水力压裂微地震井地联合监测系统及仪器

水力压裂技术是油气田增产和低渗透油田开发的有效技术手段,通过监测油层裂缝延展过程中产生的微地震事件,能够有效地判断裂缝走向.现有的井中监测方法存在成本较高、施工难度大的问题;地面监测存在信号信噪比低、垂向分辨能力差等问题.本文采用井地联合微地震监测的方法,在地面布置采集仪器的同时,选择邻近的单口监测井放置井中仪器,对微地震事件进行联合监测定位.采用联合监测的方法,在水平方向和垂直方向上都能够获得较好的监测视角,对比单一监测方法提高了微地震事件的定位精度.在此方法的基础上研制的井地联合微地震监测仪器系统,解决了现有仪器系统在进行联合监测时通讯链路不通的问题,实现了在压裂施工现场对微地震联合监测数据的实时回收、处理及结果呈现.应用本系统在大庆油田进行现场监测,获取的微地震事件对压裂裂缝进行了有效评价;通过对已知射孔点进行反演定位,采用井地联合监测将定位误差由地面监测的32 m降低至14 m,验证了本文技术的有效性.     

煤矿井下微震震源高精度定位研究

煤矿井下微震震源准确定位,对于动力灾害监测预警具有重要意义.由于微震震源需要通过井下传感器接收信息反演确定,传感器的安装位置限制于煤矿井下巷道周围,传感器沿巷道近平面的不合理布置将大大降低震源定位精度.针对由传感器信息反演震源位置引起的病态问题,本文提出了基于微震监测测点优化布置的震源高精度定位算法.首先通过计算系数矩阵条件数,判定病态问题;然后利用中心化法和行平衡法联合进行病态矩阵预处理.对预处理后的矩阵A、b利用L曲线法计算正则参数,结合Tikhonov正则化算法计算得到震源坐标正则解.研究结果表明,中心化法有效降低了矩阵数量级,行平衡预处理降低了病态条件数,预处理后Tikhonov正则解的震源坐标误差最小可以达到3.09m,与预处理前的高斯消去解相比误差大大降低.通过上述优化处理,实现了井下受限空间微震监测震源高精度定位.     

Simultaneous identification of the pollutant release history and the source location in groundwater by means of a geostatistical approach

This paper describes an innovative procedure that is able to simultaneously identify the release history and the source location of a pollutant injection in a groundwater aquifer (simultaneous release function and source location identification, SRSI). The methodology follows a geostatistical approach: it develops starting from a data set and a reliable numerical flow and transport model of the aquifer. Observations can be concentration data detected at a given time in multiple locations or a time series of concentration measurements collected at multiple locations. The methodology requires a preliminary delineation of a probably source area and results in the identification of both the sub-area where the pollutant injection has most likely originated, and in the contaminant release history. Some weak hypotheses have to be defined about the statistical structure of the unknown release function such as the probability density function and correlation structure. Three case studies are discussed concerning two-dimensional, confined aquifers with strongly non-uniform flow fields. A transfer function approach has been adopted for the numerical definition of the sensitivity matrix and the recent step input function procedure has been successfully applied.     

Study of forward–backward solute dispersion profiles in a semi-infinite groundwater system

ABSTRACT

Forward–backward solute dispersion with an intermediate point source in one-dimensional semi-infinite homogeneous porous media is studied in this paper. Solute transport under sorption conditions, first-order decay and zero-order production terms are included. The first type of boundary condition is taken as a constant point source at an intermediate point from where forward and backward solute dispersion is examined. The Laplace transform method is adopted to solve the governing equation analytically. All the analytical results are obtained in graphical form to investigate the forward–backward solute transport in porous media for various hydrological input data. The graphical nature of the analytical solution is compared with numerical data taken from existing literature and similar results are obtained. Also, numerical solution of the governing equation is obtained by the Crank-Nicolson finite difference scheme and validated with the analytical solution, which demonstrates good agreement between them. Accuracy of the solution is also observed by using RMSE.     

随机地震反演关键参数优选和效果分析(英文)

随机地震反演技术是将地质统计理论和地震反演相结合的反演方法,它将地震资料、测井资料和地质统计学信息融合为地下模型的后验概率分布,利用马尔科夫链蒙特卡洛(MCMC)方法对该后验概率分布采样,通过综合分析多个采样结果来研究后验概率分布的性质,进而认识地下情况。本文首先介绍了随机地震反演的原理,然后对影响随机地震反演效果的四个关键参数,即地震资料信噪比、变差函数、后验概率分布的样本个数和井网密度进行分析并给出其优化原则。资料分析表明地震资料信噪比控制地震资料和地质统计规律对反演结果的约束程度,变差函数影响反演结果的平滑程度,后验概率分布的样本个数决定样本统计特征的可靠性,而参与反演的井网密度则影响反演的不确定性。最后通过对比试验工区随机地震反演和基于模型的确定性地震反演结果,指出随机地震反演可以给出更符合地下实际情况的模型。     

Characterization of groundwater contaminant source using Bayesian method

Contaminant source identification in groundwater system is critical for remediation strategy implementation, including gathering further samples and analysis, as well as implementing and evaluating different remediation plans. Such problem is usually solved with the aid of groundwater modeling with lots of uncertainty, e.g. existing uncertainty in hydraulic conductivity, measurement variance and the model structure error. Monte Carlo simulation of flow model allows the input uncertainty onto the model predictions of concentration measurements at monitoring sites. Bayesian approach provides the advantage to update estimation. This paper presents an application of a dynamic framework coupling with a three dimensional groundwater modeling scheme in contamination source identification of groundwater. Markov Chain Monte Carlo (MCMC) is being applied to infer the possible location and magnitude of contamination source. Uncertainty existing in heterogonous hydraulic conductivity field is explicitly considered in evaluating the likelihood function. Unlike other inverse-problem approaches to provide single but maybe untrue solution, the MCMC algorithm provides probability distributions over estimated parameters. Results from this algorithm offer a probabilistic inference of the location and concentration of released contamination. The convergence analysis of MCMC reveals the effectiveness of the proposed algorithm. Further investigation to extend this study is also discussed.     

Bayesian spectral density approach for modal updating using ambient data

The problem of identification of the modal parameters of a structural model using measured ambient response time histories is addressed. A Bayesian spectral density approach (BSDA) for modal updating is presented which uses the statistical properties of a spectral density estimator to obtain not only the optimal values of the updated modal parameters but also their associated uncertainties by calculating the posterior joint probability distribution of these parameters. Calculation of the uncertainties of the identified modal parameters is very important if one plans to proceed with the updating of a theoretical finite element model based on modal estimates. It is found that the updated PDF of the modal parameters can be well approximated by a Gaussian distribution centred at the optimal parameters at which the posterior PDF is maximized. Examples using simulated data are presented to illustrate the proposed method. Copyright © 2001 John Wiley & Sons, Ltd.     

Using Ancillary Information to Improve Hypocenter Estimation: Bayesian Single Event Location (BSEL)

We have developed and tested an algorithm, Bayesian Single Event Location (BSEL), for estimating the location of a seismic event. The main driver for our research is the inadequate representation of ancillary information in the hypocenter estimation procedure. The added benefit is that we have also addressed instability issues often encountered with historical NLR solvers (e.g., non-convergence or seismically infeasible results). BSEL differs from established nonlinear regression techniques by using a Bayesian prior probability density function (prior PDF) to incorporate ancillary physical basis constraints about event location. P-wave arrival times from seismic events are used in the development. Depth, a focus of this paper, may be modeled with a prior PDF (potentially skewed) that captures physical basis bounds from surface wave observations. This PDF is constructed from a Rayleigh wave depth excitation eigenfunction that is based on the observed minimum period from a spectrogram analysis and estimated near-source elastic parameters. For example, if the surface wave is an Rg phase, it potentially provides a strong constraint for depth, which has important implications for remote monitoring of nuclear explosions. The proposed Bayesian algorithm is illustrated with events that demonstrate its congruity with established hypocenter estimation methods and its application potential. The BSEL method is applied to three events: 1) A shallow Mw 4 earthquake that occurred near Bardwell, KY on June 6, 2003, 2) the Mw 5.6 earthquake of July 26, 2005 that occurred near Dillon, MT, and 3) a deep Mw 5.7 earthquake that occurred off the coast of Japan on April 22, 1980. A strong Rg was observed from the Bardwell, KY earthquake that places very strong constraints on depth and origin time. No Rg was observed for the Dillon, MT earthquake, but we used the minimum observed period of a Rayleigh wave (7 seconds) to reduce the depth and origin time uncertainty. Because the Japan event was deep, there is no observed surface wave energy. We utilize the prior generated from the Dillon, MT event to show that even in the case when a prior is inappropriately applied, high quality data will overcome its influence and result in a reasonable hypocenter estimate.     

A high-resolution real-time forecasting system for predicting the fate of oil spills in the Strait of Bonifacio (western Mediterranean Sea)

The Strait of Bonifacio is a long and narrow area between Corsica and Sardinia. To manage environmental emergencies related to the spill of oil from vessels, an innovative forecasting system was developed. This tool is capable of operationally predicting the dispersion of hydrocarbon spills in the coastal area of the Bonifacio Strait, either from an instantaneous or continuous spill and either in forward or backward mode. Experimental datasets, including ADCP water current measurements and the trajectories of drifter buoys released in the area, were used to evaluate the accuracy of this system. A comparison between the simulation results and experimental data revealed that both the water circulation and the surface transport processes are accurately reproduced by the model. The overall accuracy of the system in reproducing the transport of an oil spill at sea was estimated for both forward and backward prediction mode and in relation to different forecasting time lags.     

福建测震台网观测数据质量检测软件研究

将McNamara提出的地震噪声概率密度函数(PDF)方法应用于日常地震观测系统数据质量的检测,实现了实时的自动运用概率密度函数方法处理台网接收到的观察数据,得到各个台站各个分向的PSD概率密度函数分布图以及RMS值,从而直观的判断观测数据的质量。     

Probabilistic inversion of Rayleigh-wave dispersion data: an application to Mt. Etna, Italy

We present a methodology for determining the elastic properties of the shallow crust from inversion of surface wave dispersion characteristics through a fully nonlinear procedure. Using volcanic tremor data recorded by a small-aperture seismic array on Mount Etna, we measured the surface waves dispersion curves with the multiple signal classification technique. The large number of measurements allows the determination of an a priori probability density function without the need of making any assumption about the uncertainties on the observations. Using this information, we successively conducted the inversion of phase velocities using a probabilistic approach. Using a wave-number integration method, we calculated the predicted dispersion function for thousands of 1-D models through a systematic grid search investigation of shear-wave velocities in individual layers. We joined this set of theoretical dispersion curves to the experimental probability density function (PDF), thus obtaining the desired structural model in terms of an a posteriori PDF of model parameters. This process allowed the representation of the objective function, showing the non-uniqueness of the solutions and providing a quantitative view of the uncertainties associated with the estimation of each parameter. We then compared the solution with the surface wave group velocities derived from diffuse noise Green’s functions calculated at pairs of widely spaced (~5–10 km) stations. In their gross features, results from the two different approaches are comparable, and are in turn consistent with the models presented in several earlier studies.     

地震噪声异常实时监测

本文采用福建省85个测震台站2012年全年噪声资料的垂直向记录作为研究对象,将噪声记录以每5min为单位进行分段,求出每小段的功率谱,应用概率分布函数方法绘出台站的PDF图,之后利用网格概率法确定出台站的高低噪声参照线。另外,根据85个台站的PDF图异常,将噪声异常分成四类：缺数异常、低噪处异常、高噪处异常、中噪处异常。依据四类异常的特征分别研究出四类异常的挑选方法,再将这四种挑选方法结合形成地震噪声实时监测系统。选取福建省85个测震台站2013年7月份的噪声记录进行验证,结果表明：85个台站应用地震噪声实时监测系统识别出来的异常正确率都达到90%以上,挑选效果很好,并可应用于台站噪声实时监测。     

A practical reliability-based method for assessing soil liquefaction potential

The current simplified methods for assessing soil liquefaction potential use a deterministic safety factor in order to judge whether liquefaction will occur or not. However, these methods are unable to determine the liquefaction probability related to a safety factor. An answer to this problem can be found by reliability analysis. This paper presents a reliability analysis method based on the popular Seed'85 liquefaction analysis method. This reliability method uses the empirical acceleration attenuation law in the Taiwan area to derive the probability density distribution function (PDF) and the statistics for the earthquake-induced cyclic shear stress ratio (CSR). The PDF and the statistics for the cyclic resistance ratio (CRR) can be deduced from some probabilistic cyclic resistance curves. These curves are produced by the regression of the liquefaction and non-liquefaction data from the Chi-Chi earthquake and others around the world, using, with minor modifications, the logistic model proposed by Liao [J. Geotech. Eng. 114 (1988) 389]. The CSR and CRR statistics are used in conjunction with the first order and second moment method, to calculate the relation between the liquefaction probability, the safety factor and the reliability index. Based on the proposed method, the liquefaction probability related to a safety factor can be easily calculated. The influence of some of the soil parameters on the liquefaction probability can be quantitatively evaluated.     

基于谱修正方法的非高斯风场模拟

为克服基于H erm ite谱修正方法的缺点,减少该方法中计算H erm ite多项式系数所需耗费的大量机时,提出了一种模拟非高斯风压场的新方法,采用非高斯累积分布函数（CDF）映射技术来代替基于H erm ite的概率密度函数（PDF）修正。选择任意边缘PDF模型作为概率目标模型,采用目标功率谱密度（PSD）作为样本函数,通过迭代修正该样本函数,使其收敛于目标概率密度函数和目标功率谱密度。将该方法应用于实际结构的非高斯风场模拟,模拟结果与目标谱符合良好,表明本文方法模拟非高斯风场具有较高的精确度和计算效率。