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Natural Resources Research - In most NI-43-101 resource assessment reports the prediction of global in situ resources is performed by either inverse distance weighting, ordinary kriging (OK) or... 相似文献
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A new and simple method is proposed to obtain estimates of recovery functions: the Bi-Gaussian approach. Existing methods estimate recovery functions with conditional distributions where the conditioning set is all the data available. Here instead the simple kriging estimate of the Gaussian transform is proposed to be used. Results in the point recovery case are identical to the multi-Gaussian approach of Verly (1983, 1984), whereas in the non-point-support situation, an approximation is derived which saves computer time as compared to employing the strict multi-Gaussian hypothesis. Two examples compare favorably with the well-established disjunctive kriging method (discrete Gaussian model). 相似文献
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In boreal forested wetlands, the observed increase in the water table level after clearcutting (watering‐up) is often a threat to sustained ecosystem productivity. Hydrologic recovery refers to the processes by which a water table progressively drops back to its initial level after the cut. In eastern Canada, drainage is used operationally after clearcutting wet sites in order to lower the water table level and accelerate hydrologic recovery. The objective of this study was to evaluate the duration of the watering‐up caused by timber harvesting and the extent to which drainage affected the water table recovery on five peatlands and three hydromorphic mineral sites located in the St. Lawrence Lowlands of Québec (Canada). The mixed wood stands studied are dominated by balsam fir (Abies balsamea (L.) Mill.), eastern white cedar (Thuja occidentalis L.), and red maple (Acer rubrum L). Results indicate that, 10 years after clearcutting, water table levels in undrained plots are still 5 to 7 cm higher than the pre‐cut levels. The slight recovery in water table level plateaued after the third year. Rainfall interception by vegetation was also monitored, and after 10 years had reached nearly 50% of the pre‐cut rate. The immediate water table drawdown following drainage mitigated watering‐up within 40 m of a ditch. The persistent watering‐up observed in this study should encourage using sylvicultural systems adapted to boreal forested wetlands in order to prevent productivity loss and stand conversion. Copyright © 2008 John Wiley & Sons, Ltd. 相似文献
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Min Liang Denis Marcotte Nicolas Benoit 《Stochastic Environmental Research and Risk Assessment (SERRA)》2014,28(7):1733-1741
The estimation of overburden sediment thickness is important in hydrogeology, geotechnics and geophysics. Usually, thickness is known precisely at a few sparse borehole data. To improve precision of estimation, one useful complementary information is the known position of outcrops. One intuitive approach is to code the outcrops as zero thickness data. A problem with this approach is that the outcrops are preferentially observed compared to other thickness information. This introduces a strong bias in the thickness estimation that kriging is not able to remove. We consider a new approach to incorporate point or surface outcrop information based on the use of a non-stationary covariance model in kriging. The non-stationary model is defined so as to restrict the distance of influence of the outcrops. Within this distance of influence, covariance parameters are assumed simple regular functions of the distance to the nearest outcrop. Outside the distance of influence of the outcrops, the thickness covariance is assumed stationary. The distance of influence is obtained thru a cross-validation. Compared to kriging based on a stationary model with or without zero thickness at outcrop locations, the non-stationary model provides more precise estimation, especially at points close to an outcrop. Moreover, the thickness map obtained with the non-stationary covariance model is more realistic since it forces the estimates to zero close to outcrops without the bias incurred when outcrops are simply treated as zero thickness in a stationary model. 相似文献
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Corentin Faucher Antoine Saucier Denis Marcotte 《Stochastic Environmental Research and Risk Assessment (SERRA)》2013,27(1):253-273
We present a new stochastic simulation method that builds two-dimensional images by assembling together square image pieces called blocks. The blocks are taken from a reference image. Our method, called patchwork simulation method (PSM), enforces pattern continuity in the image. Moreover, PSM allows to control the image local-mean histogram. This histogram bin-frequencies can be set to user-defined target values that may differ from the reference image local-mean histogram. This flexibility enhances the PSM generality by enlarging the set of all possible simulations. The local-mean histogram control is achieved by adjusting suitably the transition probabilities that associate a new block to an existing neighborhood in the partly simulated image. For several types of synthetic images and one polymer blend image, we show that PSM reproduces faithfully the reference image visual appearance (i.e. patterns are correctly shaped) and that simulated images are statistically compatible with the target local-mean histogram. Moreover, we show that our method has the ability to produce simulations that respect conditional hard data as well as a target local-mean histogram. 相似文献
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The problem of estimating a regionalized variable in the presence of other secondary variables is encountered in spatial investigations. Given a context in which the secondary variable is known everywhere (or can be estimated with great precision), different estimation methods are compared: regression, regression with residual simple kriging, kriging, simple kriging with a mean obtained by regression, kriging with an external drift, and cokriging. The study focuses on 19 pairs of regionalized variables from five different datasets representing different domains (geochemical, environmental, geotechnical). The methods are compared by cross-validation using the mean absolute error as criterion. For correlations between the principal and secondary variable under 0.4, similar results are obtained using kriging and cokriging, and these methods are superior slightly to the other approaches in terms of minimizing estimation error. For correlations greater than 0.4, cokriging generally performs better than other methods, with a reduction in mean absolute errors that can reach 46% when there is a high degree of correlation between the variables. Kriging with an external drift or kriging the residuals of a regression (SKR) are almost as precise as cokriging. 相似文献
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Denis Marcotte 《Mathematical Geology》1995,27(6):749-762
Conditional simulation with data subject to measurement error has received little attention in the geostatistical literature. The treatment of measurement error in simulation must be different from its treatment in estimation. Two approaches are examined: pre- and post-simulation filtering of data measurement error. The pre-simulation filtering is shown to be inefficient. The post-simulation filtering performs best. It is done by factorial kriging and a modified version of factorial kriging which ensures predetermined theoretical variance for the filtered data. It also is shown that the theoretical variogram of the filtered data reproduces the underlying variogram (i.e., without noise) almost perfectly. A simulation with a high level of correlated noise is used for validation and comparison. The post-simulation filtered values show an experimental variogram in agreement with the previously identified underlying variogram. Moreover, the filtered image compares well with the true image. The theoretical variogram corresponding to the post-simulation filter can be computed beforehand. Thus, the size of the simulation grid and of the filter neighborhood can be adjusted to ensure good reproduction of the underlying variogram. 相似文献
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N.?BenoitEmail author D.?Marcotte A.?Boucher D.?D’Or A.?Bajc H.?Rezaee 《Stochastic Environmental Research and Risk Assessment (SERRA)》2018,32(5):1435-1455
Understanding the geological uncertainty of hydrostratigraphic models is important for risk assessment in hydrogeology. An important feature of sedimentary deposits is the directional ordering of hydrostratigraphic units (HSU). Geostatistical simulation methods propose efficient algorithm for assessing HSU uncertainty. Among different geostatistical methods to simulate categorical data, Bayesian maximum entropy method (BME) and its simplified version Markov-type categorical prediction (MCP) present interesting features. In particular, the zero-forcing property of BME and MCP can provide a valuable constrain on directional properties. We illustrate the ability of MCP to simulate vertically ordered units. A regional hydrostratigraphic system with 11 HSU and different abundances is used. The transitional deterministic model of this system presents lateral variations and vertical ordering. The set of 66 (11 × 12/2) bivariate probability functions is directly calculated on the deterministic model with fast Fourier transform. Despite the trends present in the deterministic model, MCP is unbiased for the HSU proportions in the non-conditional case. In the conditional cases, MCP proved robust to datasets over-representing some HSU. The inter-realizations variability is shown to closely follow the amount and quality of data provided. Our results with different conditioning datasets show that MCP replicates adequately the directional units arrangement. Thus, MCP appears to be a practical method for generating stochastic models in a 3D hydrostratigraphic context. 相似文献
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Zagré Gilles Eric Marcotte Denis Gamache Michel Guibault François 《Natural Resources Research》2019,28(3):609-629
This paper proposes a new approach to the mining exploration drillholes positioning problem (DPP) that incorporates both geostatistical and optimization techniques. A metaheuristic was developed to solve the DPP taking into account an uncertainty index that quantifies the reliability of the current interpretation of the mineral deposit. The uncertainty index was calculated from multiple deposit realizations obtained by truncated Gaussian simulations conditional to the available drillholes samplings. A linear programming model was defined to select the subset of future drillholes that maximizes coverage of the uncertainty. A Tabu Search algorithm was developed to solve large instances of this set partitioning problem. The proposed Tabu Search algorithm is shown to provide good quality solutions approaching 95% of the optimal solution in a reasonable computing time, allowing close to optimal coverage of uncertainty for a fixed investment in drilling.
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