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91.
In order to implement secondary and enhanced oil recovery processes in complex terrigenous formations as is usual in turbidite deposits, a precise knowledge of the spatial distribution of shale grains is a crucial element for the fluid flow prediction. The reason of this is that the interaction of water with shale grains can significantly modify their size and/or shape, which in turn would cause porous space sealing with the subsequent impact in the flow. In this work, a methodology for stochastic simulations of spatial grains distributions obtained from scanning electron microscopy images of siliciclastic rock samples is proposed. The aim of the methodology is to obtain stochastic models would let us investigate the shale grain behavior under various physico-chemical interactions and flux regimes, which in turn, will help us get effective petrophysical properties (porosity and permeability) at core scale. For stochastic spatial grains simulations a plurigaussian method is applied, which is based on the truncation of several standard Gaussian random functions. This approach is very flexible, since it allows to simultaneously manage the proportions of each grain category in a very general manner and to rigorously handle their spatial dependency relationships in the case of two or more grain categories. The obtained results show that the stochastically simulated porous media using the plurigaussian method adequately reproduces the proportions, basic statistics and sizes of the pore structures present in the studied reference images. 相似文献
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Geotechnical modeling at the city scale using statistical and geostatistical tools: The Pessac case (France) 总被引：3，自引：0，他引：3
In the context of the RIVIERA project, the building of a 3D geotechnical model at the city scale (Pessac, France) has been undertaken, from several hundreds of boreholes and geotechnical tests. It is first shown how the combination of the lithological information and of geotechnical results can improve thanks to Bayesian statistics the knowledge of mechanical characteristics in the various alluvial terraces which can be encountered in this area. Secondly the upper and lower limits of the 3D model at the city scale are computed by improving an initial digital elevation model for the upper limit and by kriging under inequality constraints for the lower limit. These limits border Quaternary formations which are of interest for geotechnical applications. In a third stage, it is focused on the spatial modelling of the pressuremeter modulus. The sequential indicator simulation method enables to obtain the spatial probability of occurrence of a given pressiometer modulus class. Coupled with other information, the analysis of these statistical and geostatistical models makes possible to develop decision support tools such as to localise, for instance, areas more prone to the clay shrinkage–swelling hazard. 相似文献
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95.
Ye Zhang 《Mathematical Geosciences》2009,41(2):145-162
A hierarchical geostatistical analysis is conducted on a high-resolution, multiscale hydraulic conductivity (ln K) map, created by scaling up an experimental stratigraphy. Unlike a previous study which evaluates ln K variograms within individual depositional environments, this study analyzes deposits (or samples) that incorporate multiple
depositional environments. Based on conductivity cutoffs selected from a global ln K histogram, an indicator map is created to divide the deposits into 4 categories: sand, silty sand, clayey silt, and clay
(Hierarchy-I). Based on facies and facies assemblage types selected using geological criteria, two more indicator maps are
created at a higher hierarchy (Hierarchy-II) to divide the deposits into 14 units and 2 units, respectively. For each sample,
its experimental ln K variogram is decomposed into 4 auto- and cross-transition component variograms. The decomposition characteristics are then
evaluated against the underlying heterogeneity and specific division rule. The analysis reveals that: (1) ln K cutoffs (sand contents of the physical stratigraphy) can be used to distinguish the shifts in dominant deposition mode; (2) sample
univariate modes depend on the choice of hierarchical division; (3) sample variograms exhibit smooth-varying correlation structures
(exponential-like variograms are observed in samples with a large variance in mean facies length); (4) the decomposition characteristics
are sensitive to the division based on conductivity cutoffs, but not sensitive to the division based on depositional environment
(For all samples, with appropriate division, the sample variogram is closely approximated by the sum of the cross-transition
component variograms.); and (5) at the Hierarchy-II level, the 2-unit division gives similar decomposition characteristics
as the 14-unit division. For the select samples, parsimony in hierarchical division is achieved at the facies assemblage scale. 相似文献
96.
Monte Carlo procedures were used to evaluate the effects of spatial variations in the values of the infiltration parameter on the results of the ANSWERS distributed runoff and erosion model. Simulation results obtained were compared with measured values. Field infiltration measurements indicated spatial correlation at much smaller distances than the size of an element. Therefore, at first only the error of the mean had to be taken into consideration for block infiltration rates. Consequently, not only single hydrographs were produced, but also error bands. Secondly, nine other hypothetical spatial correlation structures were also evaluated using Monte Carlo methods. in particular at low nugget variances, increasing spatial correlation of infiltration resulted in increasing coefficients of variation in model outputs. In general, rainstorms with low rainfall intensities were more difficult to simulate accurately than extreme events with high rainfall intensities. This is explained by the greater influence of the infiltration uncertainties at low rainfall intensities. 相似文献
97.
I.?GausEmail author D.?G.?Kinniburgh J.?C.?Talbot R.?Webster 《Environmental Geology》2003,44(8):939-948
The National Hydrochemical Survey of Bangladesh sampled the water from 3,534 tube wells for arsenic throughout most of Bangladesh. It showed that 27% of the shallow tube wells (less than 150 m deep) and 1% of the deep tube wells (more than 150 m deep) exceeded the Bangladesh standard for arsenic in drinking water (50 µg L–1). Statistical analyses revealed the main characteristics of the arsenic distribution. Concentrations ranged from less than the detection limit (0.5 µg L–1), to as much as 1,600 µg L–1, though with a very skewed distribution, and with spatial dependence extending to some 180 km. Disjunctive kriging was used to estimate concentrations of arsenic in the shallow ground water and to map the probability that the national limit for arsenic in drinking water was exceeded for most of the country (the Chittagong Hill Tracts and the southern coastal region were excluded). A clear regional pattern was identified, with large probabilities in the south of the country and small probabilities in much of the north including the Pleistocene Tracts. Using these probabilities, it was estimated that approximately 35 million people are exposed to arsenic concentrations in groundwater exceeding 50 µg L–1 and 57 million people are exposed to concentrations exceeding 10 µg L–1 (the WHO guideline value). 相似文献
98.
A Digital Elevation Model issued from the SRTM mission was assessed on a study area located in a dense equatorial forest setting in French Guiana. The SRTM DEM defined on a 90-m grid was compared to three check sources: (1) airborne laser altimeter data, (2) an accurate heliborne DEM, and (3) spot heights. The paper also includes a comparison with a radargrammetric RADARSAT DEM. The results show that the accuracy of the SRTM DEM is about 10 m (standard deviation of errors). For a given slope aspect, the absolute value and the standard deviation of elevation errors increase almost linearly with the slope value. The slope aspect has a major influence on the sign of the elevation error: elevations are underestimated for slope facing SRTM signal (foreslopes, northwest), and conversely in the opposite direction (backslopes, southeast). Maximum errors are observed along these two directions. To cite this article: B. Bourgine, N. Baghdadi, C. R. Geoscience 337 (2005). 相似文献
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100.