Prediction of the occurrence of Related Strong Earthquakes in Italy

In the seismic flow it is often observed that a Strong Earthquake (SE), is followed by Related Strong Earthquakes (RSEs), which occur near the epicenter of the SE with origin time rather close to the origin time of the SE. The algorithm for the prediction of the occurrence of a RSE has been developed and applied for the first time to the seismicity data of the California-Nevada region and has been successfully tested in several regions of the world, the statistical significance of the result being 97%. To date it has been possible to make five successful forward predictions, with no false alarms or failures to predict.The algorithm is applied here to the Italian territory, where the occurrence of RSEs is a particularly rare phenomenon. Our results show that the standard algorithm is successfully directly applicable without adjustment of the parameters. Eleven SEs are considered. Of them, three are followed by a RSE, as predicted by the algorithm, eight SEs are not followed by a RSE, and the algorithm predicts this behaviour for seven of them, giving rise to only one false alarm. Since, in Italy, often the series of strong earthquakes is relatively short, the algorithm has been extended to handle such a situation. The result of this experiment indicates that it is possible to attempt to test a SE, for the occurrence of a RSE, soon after the occurrence of the SE itself, performing timely preliminary recognition on reduced data sets. This fact, the high confidence level of the retrospective analysis, and the first successful forward predictions, made in different parts of the World, indicates that, even if additional tests are desirable, the algorithm can already be considered for routine application to Civil Defence.     

“煤特征指数”与矿井瓦斯危险类型的关系

矿井瓦斯危险程度与煤层中瓦斯赋存状况及其泄出方式有关,并取决于多种地质条件和采掘工艺。其中,煤特征条件特别重要。本文分析了湖南省的5种矿井瓦斯危险类型以及相应的煤特征条件,提出了“煤特征指数(I_c)”这一概念。I_c是一项评价矿井瓦斯危险程度的综合指标。研究表明,矿井瓦斯危险愈严重,则其I_c值愈高。应用该项成果预测了16对矿井的瓦斯危险类型,取得了满意的效果。     

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.     

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 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.     

Parameter identification of inelastic structures under dynamic loads

The generalized model of differential hysteresis contains 13 control parameters with which it can curve‐fit practically any hysteretic trace. Three identification algorithms are developed to estimate the control parameters of hysteresis for different classes of inelastic structures. These algorithms are based upon the simplex, extended Kalman filter, and generalized reduced gradient methods. Novel techniques such as global search and internal constraints are incorporated to facilitate convergence and stability. Effectiveness of the devised algorithms is demonstrated through simulations of two inelastic systems with both pinching and degradation characteristics in their hysteretic traces. Owing to very modest computing requirements, these identification algorithms may become acceptable as a design tool for mapping the hysteretic traces of inelastic structures. Copyright © 2002 John Wiley & Sons, Ltd.     

非常规综合物化探油气预测研究

非常规综合物化探方法油气预测研究中存在的主要问题为：缺乏系统与综合的基础性理论研究，异常形成的机理还不十分清楚，在参数的优化组合及异常的求取上尚有诸多不足。针对后一种情况，选择松辽盆地东岭构造作为实验区进行了有益的探索。选取低能吸附烃、放射性测氡及土壤热释光三类参数进行了优化组合，分别计算了综合指标MAE与MAC及组合熵，然后对各值采用泛克里格法求取异常，取得了良好的效果。下一步研究应从异常形成的机理入手，建立三维非常规综合物化探油气预测模式，以提高油气预测成功率。     

云南中强震的水氡前兆异常特征

2001年云南澜沧5.0、施甸5.2,5.9,5.3、宁蒗5.8、楚雄5.3和江川5.1级地震前，云南49项水氡前兆中的一些台站出现突出的异常。研究发现，根据这些异常项的异常特征和空间分布特征及历史震例，可对这几次地震预报的三要素，尤其是地点和时间做出较好的判断。     

当前我国地震预报面临的主要科学问题及其建议

论述了我国目前在长期、中期和短临预报中所面临的主要科学问题，提出了从哪些方面进行突破的建议。     

川滇地区地震(Ms≥5.0)破裂类型与前兆异常分布的关系

对川滇地区 31次 (组 ) 5 .0级以上地震与余震次数的关系进行了统计 ,结合“强地震分为走滑型地震和断错型地震”的理论 ,确定了各次 (组 )地震的破裂类型。从物理机制上对地震破裂类型与震前前兆异常分布关系进行了讨论 ,由此进一步探讨了 5 .0级以上地震震后趋势预测