Multiscale adaptive estimation of the conductivity field using pump test data

An inverse problem is posed in terms of log-conductivities which are decomposed into macroscale deterministic and microscale stochastic components. The macroscale and microscale conductivities conceptualize hierarchical, scale-dependent aquifer parameters. A deterministic parameter estimation scheme divides a flow domain into a limited number of macroscale constant conductivity zones. A stochastic microscale parameter estimation scheme is used to obtain fluctuations about the macroscale averages in terms of geostatistical models. Both the macroscale and the microscale conductivities are estimated via maximum likelihood, adjoint-state methodologies. Monte Carlo-type approaches are used to examine the distribution of macroscale and microscale conductivity estimates.     

A multiscale method for distributed parameter estimation with application to reservoir history matching

A method for multiscale parameter estimation with application to reservoir history matching is presented. Starting from a given fine-scale model, coarser models are generated using a global upscaling technique where the coarse models are tuned to match the solution of the fine model. Conditioning to dynamic data is done by history-matching the coarse model. Using consistently the same resolution both for the forward and inverse problems, this model is successively refined using a combination of downscaling and history matching until model-matching dynamic data are obtained at the finest scale. Large-scale corrections are obtained using fast models, which, combined with a downscaling procedure, provide a better initial model for the final adjustment on the fine scale. The result is thus a series of models with different resolution, all matching history as good as possible with this grid. Numerical examples show that this method may significantly reduce the computational effort and/or improve the quality of the solution when achieving a fine-scale match as compared to history-matching directly on the fine scale.     

Multiscale tomography of buried magnetic structures: its use in the localization and characterization of archaeological structures

We have previously developed a method for characterizing and localizing 'homogeneous' buried sources, from the measure of potential anomalies at a fixed height above ground (magnetic, electric and gravity). This method is based on potential theory and uses the properties of the Poisson kernel (real by definition) and the continuous wavelet theory. Here, we relax the assumption on sources and introduce a method that we call the 'multiscale tomography'. Our approach is based on the harmonic extension of the observed magnetic field to produce a complex source by use of a complex Poisson kernel solution of the Laplace equation for complex potential field. A phase and modulus are defined. We show that the phase provides additional information on the total magnetic inclination and the structure of sources, while the modulus allows us to characterize its spatial location, depth and 'effective degree'. This method is compared to the 'complex dipolar tomography', extension of the Patella method that we previously developed. We applied both methods and a classical electrical resistivity tomography to detect and localize buried archaeological structures like antique ovens from magnetic measurements on the Fox-Amphoux site (France). The estimates are then compared with the results of excavations.     

基于离散傅里叶变换的线要素节点压缩方法

相较于传统删减顶点的线要素综合方法,基于傅里叶变换的线要素综合更能保留曲线的全局特征,但现有的傅里叶综合方法无法自动减少和控制点数,更多适用于曲线的平滑及多尺度表达。因此本文提出一种利用离散傅里叶变换进行线要素综合的方法。对曲线进行离散傅里叶变换,获得有限项傅里叶描述子;根据期望的压缩比对傅里叶描述子进行截断;根据截断后的描述子项进行离散傅里叶逆变换获得化简曲线。本文提出的这种傅里叶方法能够减少化简后曲线顶点数,适用于地图综合领域。本文通过四组实验验证了算法的可行性,展示其如下优点：① 能够在相应尺度上对线性地物进行平滑、渐进的化简和表达② 在现有傅里叶变换法的基础上能够保留曲线原顶点;③ 以顶点数作为综合过程参数,能够自动减少曲线顶点数;④ 相较于传统节点压缩方法,更注重整体形态的化简,在综合过程中能更好地保留曲线的整体特征;⑤ 在转换尺度较大的综合过程中,相较于传统节点压缩方法所保留的几何精度更高。     

Structural seismic response analysis based on multiscale approach of computing fault–structure system

Structural safety for earthquake waves emitted from a nearby fault is a major concern. For a large complex structure, it might be desired to estimate its seismic response by analyzing a fault–structure system: a full three‐dimensional model in which a source fault and a target structure are modeled so that fault processes, wave propagation and amplification processes, and resulting dynamic responses of the structure can be computed numerically. To analyze this fault–structure system, this paper proposes an efficient approach based on multiscale analysis, i.e. waves emitted from the source fault are computed in the entire system in the geological length‐scale; then they are refined in a small part of the system that includes the structure, and the seismic response of the structure is accurately computed in the engineering length‐scale. Using a long highway tunnel as an example, this paper examines the validity of the proposed approach. The usefulness and applicability of the proposed approach to estimate the structural seismic responses are discussed. Copyright © 2008 John Wiley & Sons, Ltd.     

Regional watershed characterization and classification with river network analyses

In order to understand and manage a hydrological region, one usually needs to comprehensively characterize the watersheds (basins) and their river networks. This usually and primarily involves analysis of hydrological and geomorphological properties of the watershed derived from the digital terrain model (DTM), but this approach neglects the information content of the associated river networks. In this study, we used a combination of traditional DTM and original river network‐related indices to the watersheds of an understudied region, Haiti. We also used Monte Carlo simulations to estimate index confidence levels of these indices. Compared to commonly used indices, the network indices provided valuable information that could then be used in statistical analyses as a way to identify the dominant features of the country's watershed morphology. On this basis, we identified four watershed groups in Haiti: (i) high, elongated watersheds, (ii) lowlands, with sinuous networks and relatively slow runoff, (iii) high watersheds with dendritic networks, and (iv) lowlands with high downstream–upstream contrast in properties and rapid runoffs. We argue that river network features provide complementary information in terms of flow topology, highly relevant to characterize contrasting relief countries, such as Haiti. Hence, more exhaustive characterization of watersheds would predictably benefit from the approach outlined in this paper. Copyright © 2017 John Wiley & Sons, Ltd.     

黑河流域地理观测分析——复杂性科学视角（英文）

Since 2005,dozens of geographical observational stations have been established in the Heihe River Basin(HRB),and by now a large amount of meteorological,hydrological,and ecological observations as well as data pertaining to water resources,soil and vegetation have been collected.To adequately analyze these available data and data to be further collected in future,we present a perspective from complexity theory.The concrete materials covered include a presentation of adaptive multiscale filter,which can readily determine arbitrary trends,maximally reduce noise,and reliably perform fractal and multifractal analysis,and a presentation of scale-dependent Lyapunov exponent(SDLE),which can reliably distinguish deterministic chaos from random processes,determine the error doubling time for prediction,and obtain the defining parameters of the process examined.The adaptive filter is illustrated by applying it to obtain the global warming trend and the Atlantic multidecadal oscillation from sea surface temperature data,and by applying it to some variables collected at the HRB to determine diurnal cycle and fractal properties.The SDLE is illustrated to determine intermittent chaos from river flow data.     

Analyses of geographical observations in the Heihe River Basin: Perspectives from complexity theory

Journal of Geographical Sciences - Since 2005, dozens of geographical observational stations have been established in the Heihe River Basin (HRB), and by now a large amount of meteorological,...     

结合多尺度纹理的高分辨率遥感影像决策树分类

地物具有多尺度特点,遥感影像包含的地物纹理信息很难用单一尺度来描述。通过选择最佳纹理尺度组合,利用光谱数据结合多尺度纹理对高分辨率影像进行决策树分类。研究结果表明:结合多尺度纹理的高分辨遥感影像决策树分类,能够更好地描述地物并有效解决光谱数据分类中存在的地物破碎问题,其分类精度为81.7%,kap-pa系数为0.78;与光谱数据分类和结合单尺度纹理数据分类结果比较,分类精度分别提高了11.2%和6%,该方法有助于提高高分辨率影像的分类精度。