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31.
A multi-lithology diffusive stratigraphic model is considered, which simulates at large scales in space and time the infill
of sedimentary basins governed by the interaction between tectonics displacements, eustatic variations, sediment supply, and
sediment transport laws. The model accounts for the mass conservation of each sediment lithology resulting in a mixed parabolic,
hyperbolic system of partial differential equations (PDEs) for the lithology concentrations and the sediment thickness. It
also takes into account a limit on the rock alteration velocity modeled as a unilaterality constraint. To obtain a robust,
fast, and accurate simulation, fully and semi-implicit finite volume discre tization schemes are derived for which the existence
of stable solutions is proved. Then, the set of nonlinear equations is solved using a Newton algorithm adapted to the unilaterality
constraint, and preconditioning strategies are defined for the solution of the linear system at each Newton iteration. They
are based on an algebraic approximate decoupling of the sediment thickness and the concentration variables as well as on a
proper preconditioning of each variable. These algorithms are studied and compared in terms of robustness, scalability, and
efficiency on two real basin test cases. 相似文献
32.
基于ICCP算法的重力辅助惯性导航 总被引:7,自引:0,他引:7
迭代最近等值线算法(ICCP)是一种重要的匹配导航算法,文中首先介绍ICCP算法的基本原理,随后在0.2′×0.2′重力异常数据库的基础上,利用ICCP算法进行仿真计算得到最佳匹配位置。最后为了验证匹配位置是否可用于修正惯导误差,提出将匹配位置误差作为观测量,用卡尔曼滤波对惯导系统误差进行最优估计。由最后的仿真结果可以看出,ICCP算法可有效抑制惯导纬度误差的增长,且最大纬度误差不超过2,′以匹配位置误差作为观测量可以用来估计惯导方位误差角。 相似文献
33.
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35.
中国煤炭地质总局航测遥感局作为我国煤炭航测技术的主要单位,承担着95%以上的煤炭矿区航测成图任务,并逐步发展成为我国集航空摄影、遥感地质、地图制印、地下管线探测、地理信息技术等全面发展的空间信息产业集团:伴随着计算机技术的发展,煤炭航测技术走过了从模拟测图到解析测图,最后发展到今天的全数字测图的历程。目前煤航已拥有和掌握了IMU/DGPS辅助航空摄影技术、SAR(合成孔径雷达)成图技术、LIDAR(机载激光扫描)技术等空间数据采集最新技术。 相似文献
36.
Hitoshi Oda 《Pure and Applied Geophysics》1996,147(4):719-727
By applying the perturbation theory to theXYZ algorithm (a kind of variational method), the difference f in free vibration frequencies between sphere and ellipsoid was approximated as
, where i and
i
(i = x,y andz) (i=x, y andz) are aspherical coefficients and asphericities of the ellipsoid, respectively. We developed an analytic method to compute the aspherical coefficients719-4 by using theXYZ algorithm. A numerical example was given for an ellipsoidal olivine, and an attempt was made to estimate the asphericities of the specimen by a least-squares method, based on the relationship between frequency shift and asphericity. 相似文献
37.
Characterizing heterogeneous permeable media using flow and transport data typically requires solution of an inverse problem. Such inverse problems are intensive computationally and may involve iterative procedures requiring many forward simulations of the flow and transport problem. Previous attempts have been limited mostly to flow data such as pressure transient (interference) tests using multiple observation wells. This paper discusses an approach to generating stochastic permeability fields conditioned to geologic data in the form of a vertical variogram derived from cores and logs as well as fluid flow and transport data, such as tracer concentration history, by sequential application of simulated annealing (SA). Thus, the method incorporates elements of geostatistics within the framework of inverse modeling. For tracer-transport calculations, we have used a semianalytic transit-time algorithm which is fast, accurate, and free of numerical dispersion. For steady velocity fields, we introduce a transit-time function which demonstrates the relative importance of data from different sources. The approach is illustrated by application to a set of spatial permeability measurements and tracer data from an experiment in the Antolini Sandstone, an eolian outcrop from northern Arizona. The results clearly reveal the importance of tracer data in reproducing the correlated features (channels) of the permeability field and the scale effects of heterogeneity. 相似文献
38.
Many stochastic process models for environmental data sets assume a process of relatively simple structure which is in some sense partially observed. That is, there is an underlying process (Xn, n 0) or (Xt, t 0) for which the parameters are of interest and physically meaningful, and an observable process (Yn, n 0) or (Yt, t 0) which depends on the X process but not otherwise on those parameters. Examples are wide ranging: the Y process may be the X process with missing observations; the Y process may be the X process observed with a noise component; the X process might constitute a random environment for the Y process, as with hidden Markov models; the Y process might be a lower dimensional function or reduction of the X process. In principle, maximum likelihood estimation for the X process parameters can be carried out by some form of the EM algorithm applied to the Y process data. In the paper we review some current methods for exact and approximate maximum likelihood estimation. We illustrate some of the issues by considering how to estimate the parameters of a stochastic Nash cascade model for runoff. In the case of k reservoirs, the outputs of these reservoirs form a k dimensional vector Markov process, of which only the kth coordinate process is observed, usually at a discrete sample of time points. 相似文献
39.
40.
Lars Kristian Nielsen Sam Subbey Mike Christie Trond Mannseth 《Computational Geosciences》2006,10(3):321-342
There is a correspondence between flow in a reservoir and large scale permeability trends. This correspondence can be derived by constraining reservoir models using observed production data. One of the challenges in deriving the permeability distribution of a field using production data involves determination of the scale of resolution of the permeability. The Adaptive Multiscale Estimation (AME) seeks to overcome the problems related to choosing the resolution of the permeability field by a dynamic parameterisation selection. The standard AME uses a gradient algorithm in solving several optimisation problems with increasing permeability resolution. This paper presents a hybrid algorithm which combines a gradient search and a stochastic algorithm to improve the robustness of the dynamic parameterisation selection. At low dimension, we use the stochastic algorithm to generate several optimised models. We use information from all these produced models to find new optimal refinements, and start out new optimisations with several unequally suggested parameterisations. At higher dimensions we change to a gradient-type optimiser, where the initial solution is chosen from the ensemble of models suggested by the stochastic algorithm. The selection is based on a predefined criterion. We demonstrate the robustness of the hybrid algorithm on sample synthetic cases, which most of them were considered insolvable using the standard AME algorithm. 相似文献