地统计学用于空间不确定性的描述(英文)

Most geospatial phenomena can be interpreted probabilistically because we are ignorant of the biophysical processes and mechanisms that have jointly created and observed events. This philosophy is important because we are certain about the phenomenon under study at sampled locations, except for measurement errors, but, in between the sampled, we become uncertain about how the phenomenon behaves. Geostatistical uncertainty characterization is to generate random numbers in such a way that they simulate the outcomes of the random processes that created the existing sample data. This set of existing sample is viewed as a partially sampled realization of that random function model. The random function’s spatial variability is described by a variogram or covariance model. The realized surfaces need to honour sample data at their locations, and reflect the spatial structure quantified by the variogram models. They should each reproduce the sample histogram representative of the whole sampling area. This paper will review the fundamentals in stochastic simulation by covering univariate and indicator techniques in the hope that their applications in geospatial information science will be wide-spread and fruitful. Supported by the National 973 Program of China (No. 2006CB701302).     

����С��������Kriging���Ƶ�GPS�߳�ת��

??????????С???任??Kriging?????GPS?????????????????????С?????????Kriging?????????GPS????????????????????GPS????????м????????????????????÷??????????????????????????,????С????????Kriging???????y??????????????     

Nekhoroshev estimate for isochronous non resonant symplectic maps

We prove that non resonant isochronous symplectic maps in a neighborhood of an elliptic fixed point are stable for exponentially long times with the inverse of the distance from the fixed point. In the proof we make use of the majorant series method together with an idea for optimizing remainder estimates first applied to Hamiltonian problems by Nekhoroshev.     

涉及微分多项式及例外函数的正规定则

设φ(z)≠0为区域D(c)C上的亚纯函数,a0(z),a1(z),…ak-1(z)为区域D上的全纯函数,k∈N.F为区域D上一族亚纯函数.对于任意的f(z)∈F,所有零点之级≥k 1,极点之级≥2.并且L(f)(z)=,k((z) ak-1(z)f(k-1)(z) …a1(z)f'(z) a0(z)f(z)≠φ(z),z∈D则F在D上正规.     

Predicting strain using forward modelling of restored cross-sections: Application to rollover anticlines over listric normal faults

A strategy to predict strain across geological structures, based on previous techniques, is modified and evaluated, and a practical application is shown. The technique, which employs cross-section restoration combined with kinematic forward modelling, consists of restoring a section, placing circular strain markers on different domains of the restoration, and forward modelling the restored section with strain markers until the present-day stage is reached. The restoration algorithm employed must be also used to forward model the structure. The ellipses in the forward modelled section allow determining the strain state of the structure and may indirectly predict orientation and distribution of minor structures such as small-scale fractures. The forward model may be frozen at different time steps (different growth stages) allowing prediction of both spatial and temporal variation of strain. The method is evaluated through its application to two stages of a clay experiment, that includes strain markers, and its geometry and deformation history are well documented, providing a strong control on the results. To demonstrate the method's potential, it is successfully applied to a depth-converted seismic profile in the Central Sumatra Basin, Indonesia. This allowed us to gain insight into the deformation undergone by rollover anticlines over listric normal faults.     

双谱拾取时差参数场

研究Siliqi和Meur等提出的高密度拾取均方根速度和非椭圆率参数η的方法。导出了以最大偏移距对应的剩余时差dtn和零偏移距时间τ0为变量的时移双曲线方程,采用相似度扫描拾取dtn以及τ0,然后再把它们换算成均方根速度和非椭圆率参数。在理论数据处理过程中,发现时移双曲线扫描的精度比非双曲线方法有了一定的提高,特别是η值的误差减小了很多,这说明时移双曲线扫描的优越性。