Comparison of structural and least-squares lines for estimating geologic relations

Two different goals in fitting straight lines to data are to estimate a true linear relation (physical law) and to predict values of the dependent variable with the smallest possible error. Regarding the first goal, a Monte Carlo study indicated that the structural-analysis (SA) method of fitting straight lines to data is superior to the ordinary least-squares (OLS) method for estimating true straight-line relations. Number of data points, slope and intercept of the true relation, and variances of the errors associated with the independent (X) and dependent (Y) variables influence the degree of agreement. For example, differences between the two line-fitting methods decrease as error in X becomes small relative to error in Y. Regarding the second goal—predicting the dependent variable—OLS is better than SA. Again, the difference diminishes as X takes on less error relative to Y. With respect to estimation of slope and intercept and prediction of Y, agreement between Monte Carlo results and large-sample theory was very good for sample sizes of 100, and fair to good for sample sizes of 20. The procedures and error measures are illustrated with two geologic examples.     

FS方法及其在综合多项震兆中的应用

本文提出了一种模式识别方法--FS方法.该方法的特征取为某些论域上的模糊子集.先以每三个原始特征组成子分类器的特征集,“训练”这些分类器,然后对子分类器进行筛选,最后用筛选出的子分类器的“软”分类结果的加权平均作为判别函数,形成总的分类决策.将FS方法应用于综合多项震兆,并进行了一系列控制试验,还与地震学中几种常用的方法进行了对比试验.结果表明,FS方法是稳定和有效的.     

Increasing critical sensitivity of the Load/Unload Response Ratio before large earthquakes with identified stress accumulation pattern

The Load/Unload Response Ratio (LURR) method is proposed for short-to-intermediate-term earthquake prediction [Yin, X.C., Chen, X.Z., Song, Z.P., Yin, C., 1995. A New Approach to Earthquake Prediction — The Load/Unload Response Ratio (LURR) Theory, Pure Appl. Geophys., 145, 701–715]. This method is based on measuring the ratio between Benioff strains released during the time periods of loading and unloading, corresponding to the Coulomb Failure Stress change induced by Earth tides on optimally oriented faults. According to the method, the LURR time series usually climb to an anomalously high peak prior to occurrence of a large earthquake. Previous studies have indicated that the size of critical seismogenic region selected for LURR measurements has great influence on the evaluation of LURR. In this study, we replace the circular region usually adopted in LURR practice with an area within which the tectonic stress change would mostly affect the Coulomb stress on a potential seismogenic fault of a future event. The Coulomb stress change before a hypothetical earthquake is calculated based on a simple back-slip dislocation model of the event. This new algorithm, by combining the LURR method with our choice of identified area with increased Coulomb stress, is devised to improve the sensitivity of LURR to measure criticality of stress accumulation before a large earthquake. Retrospective tests of this algorithm on four large earthquakes occurred in California over the last two decades show remarkable enhancement of the LURR precursory anomalies. For some strong events of lesser magnitudes occurred in the same neighborhoods and during the same time periods, significant anomalies are found if circular areas are used, and are not found if increased Coulomb stress areas are used for LURR data selection. The unique feature of this algorithm may provide stronger constraints on forecasts of the size and location of future large events.     

Testing earthquake prediction methods: «The West Pacific short-term forecast of earthquakes with magnitude MwHRV ≥ 5.8»

Analyzing the tables and probability maps posted by Yan Y. Kagan and David D. Jackson in April 2002–September 2004 at http://scec.ess.ucla.edu/~ykagan/predictions_index.html and the catalog of earthquakes for the same period, the conclusion is drawn that the underlying method could be used for prediction of aftershocks, while it does not outscore random guessing when main shocks are considered.     

A laboratory experiment to monitor the contact state of a fault by transmission waves

We performed a series of laboratory experiments in which elastic waves were transmitted across a simulated fault. Two types of experiments were carried out: (1) Normal Stress Holding Test (NSHT): normal stress was kept constant for about 3 h without shear stress and transmission waves were observed. (2) Shear Stress Increasing Test (SSIT): shear stress was gradually increased until a stick-slip event occurred. Transmission waves were continuously observed throughout the process of stress accumulation. We focused on the change in transmission waves during the application of shear stress and especially during precursory slips.It was found in NSHT that the amplitude of transmission waves linearly increased with the logarithm of stationary contact time. The increase amounted to a few percent after about 3 h. Creep at asperity contacts is responsible for this phenomenon. From a theoretical consideration, it was concluded that the real contact area increased with the logarithm of stationary contact time.We observed in SSIT a significant increase in wave amplitude with shear stress application. This phenomenon cannot be attributed to the time effect observed in NSHT. Instead, it can be explained by the mechanism of “junction growth” proposed by Tabor. Junction growth yields an increase in real contact area. It is required for junction growth to occur that the material in contact is already plastic under a purely normal loading condition. A computer simulation confirmed that this requirement was satisfied in our experiments. We also found that the rate at which the amplitude increased was slightly reduced prior to a stick-slip event. The onset time of the reduction well coincides with the onset of precursory slip. The cause of the reduction is attributed to the reset of stationary contact time due to displacement. This interpretation is supported by the result of NSHT. Taking the time of stationary contact in SSIT into account, we may expect the change in wave amplitude to be, at most, only a few percent. The observed slight reduction in increasing rate is, in this sense, reasonable. The static stiffness of the fault also decreases with precursory slip. It was also found that low frequency waves are a better indicator of precursory slip than high frequency waves. This might suggest that low frequency waves with longer wavelength are a better indicator of average behavior of faults. The problem, however, merits a further investigation. The shifts in phase were also found to be a good indicator of the change in contact state of the fault. The changes in both amplitude and phase of transmission waves are unifyingly understood through the theory of transmission coefficient presented by Pyrak-Nolte et al. Rough surfaces have a tendency to give larger stick-slips than smooth surfaces. The amount of precursory slip is larger for rough surfaces than for smooth surfaces. Although it was confirmed by a computer simulation that rough surfaces have larger contact diameters than smooth surfaces, the rigorous relationship between the surface roughness (contact diameter) and the amount of precursory slips was not established.     

A way to synchronize models with seismic faults for earthquake forecasting: Insights from a simple stochastic model

Numerical models are starting to be used for determining the future behaviour of seismic faults and fault networks. Their final goal would be to forecast future large earthquakes. In order to use them for this task, it is necessary to synchronize each model with the current status of the actual fault or fault network it simulates (just as, for example, meteorologists synchronize their models with the atmosphere by incorporating current atmospheric data in them). However, lithospheric dynamics is largely unobservable: important parameters cannot (or can rarely) be measured in Nature. Earthquakes, though, provide indirect but measurable clues of the stress and strain status in the lithosphere, which should be helpful for the synchronization of the models.The rupture area is one of the measurable parameters of earthquakes. Here we explore how it can be used to at least synchronize fault models between themselves and forecast synthetic earthquakes. Our purpose here is to forecast synthetic earthquakes in a simple but stochastic (random) fault model. By imposing the rupture area of the synthetic earthquakes of this model on other models, the latter become partially synchronized with the first one. We use these partially synchronized models to successfully forecast most of the largest earthquakes generated by the first model. This forecasting strategy outperforms others that only take into account the earthquake series. Our results suggest that probably a good way to synchronize more detailed models with real faults is to force them to reproduce the sequence of previous earthquake ruptures on the faults. This hypothesis could be tested in the future with more detailed models and actual seismic data.     

Optimization of nonconventional wells under uncertainty using statistical proxies

The determination of the optimal type and placement of a nonconventional well in a heterogeneous reservoir represents a challenging optimization problem. This determination is significantly more complicated if uncertainty in the reservoir geology is included in the optimization. In this study, a genetic algorithm is applied to optimize the deployment of nonconventional wells. Geological uncertainty is accounted for by optimizing over multiple reservoir models (realizations) subject to a prescribed risk attitude. To reduce the excessive computational requirements of the base method, a new statistical proxy (which provides fast estimates of the objective function) based on cluster analysis is introduced into the optimization process. This proxy provides an estimate of the cumulative distribution function (CDF) of the scenario performance, which enables the quantification of proxy uncertainty. Knowledge of the proxy-based performance estimate in conjunction with the proxy CDF enables the systematic selection of the most appropriate scenarios for full simulation. Application of the overall method for the optimization of monobore and dual-lateral well placement demonstrates the performance of the hybrid optimization procedure. Specifically, it is shown that by simulating only 10% or 20% of the scenarios (as determined by application of the proxy), optimization results very close to those achieved by simulating all cases are obtained.     

Towards Formulation of a Space-borne System for Early Warning of Floods: Can Cost-Effectiveness Outweigh Prediction Uncertainty?

The three most important components necessary for functioning of an operational flood warning system are: (1) a rainfall measuring system; (2) a soil moisture updating system; and, (3) a surface discharge measuring system. Although surface based networks for these systems can be largely inadequate in many parts of the world, this inadequacy particularly affects the tropics, which are most vulnerable to flooding hazards. Furthermore, the tropical regions comprise developing countries lacking the financial resources for such surface-based monitoring. The heritage of research conducted on evaluating the potential for measuring discharge from space has now morphed into an agenda for a mission dedicated to space-based surface discharge measurements. This mission juxtaposed with two other upcoming space-based missions: (1) for rainfall measurement (Global Precipitation Measurement, GPM), and (2) soil moisture measurement (Hydrosphere State, HYDROS), bears promise for designing a fully space-borne system for early warning of floods. Such a system, if operational, stands to offer tremendous socio-economic benefit to many flood-prone developing nations of the tropical world. However, there are two competing aspects that need careful assessment to justify the viability of such a system: (1) cost-effectiveness due to surface data scarcity; and (2) flood prediction uncertainty due to uncertainty in the remote sensing measurements. This paper presents the flood hazard mitigation opportunities offered by the assimilation of the three proposed space missions within the context of these two competing aspects. The discussion is cast from the perspective of current understanding of the prediction uncertainties associated with space-based flood prediction. A conceptual framework for a fully space-borne system for early-warning of floods is proposed. The need for retrospective validation of such a system on historical data comprising floods and its associated socio-economic impact is stressed. This proposal for a fully space-borne system, if pursued through wide interdisciplinary effort as recommended herein, promises to enhance the utility of the three space missions more than what their individual agenda can be expected to offer.     

Verification of the motion fields over Southeast Asia by the Florida State University (FSU) superensemble forecast

The Florida State University (FSU) multimodel superensemble forecast is evaluated against several other operational weather models for the Southeast Asia region. The superensemble technique has demonstrated its exceptional skills in forecasting precipitation, motion and mass fields compared to either individual global operational or ensemble mean forecasts. The motion field investigation for the season of 2001 reveals that the superensemble forecasts are closer to the observed data compared to the other global member operational models through its low systematic errors at the 850 hPa level. The FSU multimodel superensemble forecasts exhibit the lowest root mean square errors (RSMEs), the highest correlation against the best observed data and the lowest systematic errors compared to the other operational model members. These forecasts have the potential to provide better daily weather predictions over the Southeast Asia region, particularly during the early northeast monsoon that often causes heavy rainfall in the equatorial part of the Southeast Asia region.     

基于预测的边缘检测方法

提出了一种基于预测的、有一定自适应性的边缘检测方法。介绍了其原理和算法实现过程。通过计算两个相邻像素的灰度值的均值、均方差和梯度来预测下一个像素的灰度值，比较预测值和真实值来判断下一个像素是否是边界点。通过与现有同类算法的比较，证明了该算法的优越性。