2008年10月6日当雄M_s6.6级地震破裂过程          下载免费PDF全文

高星  段宗奇  王卫民  郭志 《地球物理学报》2010,53(9):2083-2090

2008年10月6日16时30分(北京时间),西藏自治区拉萨市当雄县发生M_s6.6级地震.震中位于亚东-谷露近南北向裂谷带北段,是该活动构造带近年来发生的一次较大地震.我们利用中国地震台网中心(CENC)和美国地震学联合研究所(IRIS)提供的宽频带地震记录资料,基于点源和有限断层模型,通过波形拟合反演了该地震的震源过程.结果表明,本次地震的发震断层面走向为183.3°,倾角为49.5°,滑动角约为－115°,最大滑动量达130 cm,地震震源的深度为9.6 km,地震的标量地震矩为2.85×10¹⁸ N·m,破裂持续时间约10 s.根据地震破裂的几何学和运动学特征,推测该地震主要发生在亚东-谷露南北向裂谷活动构造带内的一个高角度西倾断层上,是一个以拉张为主且有一定的右旋分量的破裂事件,这与青藏高原现今GPS测量所揭示的该地区地壳运动特征基本一致,暗示了青藏高原南部从西向东地表运动从北北东向到南东东向的运动学转变所导致的地壳在近东西方向上的拉张变形特征.  相似文献   

基于模拟退火算法的随机模拟方法研究     

海洋  朱培民 《地球物理学进展》2012,27(2):670-679

随着油气田开发难度的加大和技术的进步,储层随机建模技术已经成为储层表征的主要手段.基于地质统计学理论的认识,并结合模拟退火算法,本文研究了退火随机模拟储层地质模型,其结果表明该方法是一种易理解、易实现、较灵活、适应性强、较实用的算法.应用该方法可以建立渗透率、孔隙度、含油饱和度,以及波阻抗等参数的空间分布模型,这些模型很好的保持了已知数据所反映的储层空间特征,并真实地展现了各种参数在储层内的分布,为油气田储层预测和开发提供依据.  相似文献   

Kolmogorov–Smirnov test for spatially correlated data     

Ricardo A. Olea  Vera Pawlowsky-Glahn 《Stochastic Environmental Research and Risk Assessment (SERRA)》2009,23(6):749-757

The Kolmogorov–Smirnov test is a convenient method for investigating whether two underlying univariate probability distributions can be regarded as undistinguishable from each other or whether an underlying probability distribution differs from a hypothesized distribution. Application of the test requires that the sample be unbiased and the outcomes be independent and identically distributed, conditions that are violated in several degrees by spatially continuous attributes, such as topographical elevation. A generalized form of the bootstrap method is used here for the purpose of modeling the distribution of the statistic D of the Kolmogorov–Smirnov test. The innovation is in the resampling, which in the traditional formulation of bootstrap is done by drawing from the empirical sample with replacement presuming independence. The generalization consists of preparing resamplings with the same spatial correlation as the empirical sample. This is accomplished by reading the value of unconditional stochastic realizations at the sampling locations, realizations that are generated by simulated annealing. The new approach was tested by two empirical samples taken from an exhaustive sample closely following a lognormal distribution. One sample was a regular, unbiased sample while the other one was a clustered, preferential sample that had to be preprocessed. Our results show that the p-value for the spatially correlated case is always larger that the p-value of the statistic in the absence of spatial correlation, which is in agreement with the fact that the information content of an uncorrelated sample is larger than the one for a spatially correlated sample of the same size.  相似文献