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In the development of naturally fractured reservoirs (NFRs), the existence of natural fractures induces severe fingering and breakthrough. To manage the flooding process and improve the ultimate recovery, we propose a numerical workflow to generate optimal production schedules for smart wells, in which the inflow control valve (ICV) settings can be controlled individually. To properly consider the uncertainty introduced by randomly distributed natural fractures, the robust optimization would require a large ensemble size and it would be computationally demanding. In this work, a hierarchical clustering method is proposed to select representative models for the robust optimization in order to avoid redundant simulation runs and improve the efficiency of the robust optimization. By reducing the full ensemble of models into a small subset ensemble, the efficiency of the robust optimization algorithm is significantly improved. The robust optimization is performed using the StoSAG scheme to find the optimal well controls that maximize the net-present-value (NPV) of the NFR’s development. Due to the discrete property of a natural fracture field, traditional feature extraction methods such as model-parameter-based clustering may not be directly applicable. Therefore, two different kinds of clustering-based optimization methods, a state-based (e.g., s w profiles) clustering and a response-based (e.g., production rates) clustering, are proposed and compared. The computational results show that the robust clustering optimization could increase the computational efficiency significantly without sacrificing much expected NPV of the robust optimization. Moreover, the performance of different clustering algorithms varies widely in correspondence to different selections of clustering features. By properly extracting model features, the clustered subset could adequately represent the uncertainty of the full ensemble. 相似文献
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Hydrologists use the generalized Pareto (GP) distribution in peaks-over-threshold (POT) modelling of extremes. A model with similar uses is the two-parameter kappa (KAP) distribution. KAP has had fewer hydrological applications than GP, but some studies have shown it to merit wider use. The problem of choosing between GP and KAP arises quite often in frequency analyses. This study, by comparing some discrimination methods between these two models, aims to show which method(s) is (are) recommended. Three specific methods are considered: one uses the Anderson-Darling goodness-of-fit (GoF) statistic, another uses the ratio of maximized likelihood (closely related to the Akaike information criterion and the Bayesian information criterion), and the third employs a normality transformation followed by application of the Shapiro-Wilk statistic. We show this last method to be the most recommendable, due to its advantages with sizes typically encountered in hydrology. We apply the simulation results to some flood POT datasets.
EDITOR D. Koutsoyiannis; ASSOCIATE EDITOR E. Volpi 相似文献
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We describe and give hydrological applications of a probabilistic model based on extreme value theory which can be used to study the values of a hydrologic process that exceed a certain threshold level Q
B
.This model is useful in estimating extreme events X
T
of return period T based on N years of available hydrologic record. We also present easy-to-use tables which give confidence intervals for X
T
.The hydrologic applications reported are a flood frequency analysis, a methodology for estimating flood damage, an estimation of precipitation probabilities, and a prediction of extreme tide levels. 相似文献
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The problem of fitting a probability distribution, here log-Pearson Type III distribution, to extreme floods is considered from the point of view of two numerical and three non-numerical criteria. The six techniques of fitting considered include classical techniques (maximum likelihood, moments of logarithms of flows) and new methods such as mixed moments and the generalized method of moments developed by two of the co-authors. The latter method consists of fitting the distribution using moments of different order, in particular the SAM method (Sundry Averages Method) uses the moments of order 0 (geometric mean), 1 (arithmetic mean), –1 (harmonic mean) and leads to a smaller variance of the parameters. The criteria used to select the method of parameter estimation are:
These criteria are transformed into value functions or fuzzy set membership functions and then three Multiple Criteria Decision Modelling (MCDM) techniques, namely, composite programming, ELECTRE, and MCQA, are applied to rank the estimation techniques. 相似文献
| – | - the two statistical criteria of mean square error and bias; |
| – | - the two computational criteria of program availability and ease of use; |
| – | - the user-related criterion of acceptability. |
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The log-Pearson type 3 distribution is widely used in North America and Australia for fitting annual flood series. Four different versions of the method of moments used in fitting this distribution are compared using Monte Carlo simulated samples which reflect some of the characteristics of annual flood series observed at some Canadian rivers. The bias, standard error, root mean square error, and skew, of the parameter estimates, and of estimates of events associated with different probabilities of occurrence are examined. Also examined are the correlation coefficients between probabilities of occurrence are examined. Also examined are the correlation coefficients between the parameter estimates and between the sample moments that are used in each of the four methods of estimation. It is observed that variances, covariances and correlation coefficients calculated using the usual first-order asymptotic approximation might have considerable error and therefore should be used with caution. On the basis of mean square error of events with return period above the range covered by the sample it is observed that a method proposed earlier which uses moments of order 1, 2 and 3 in real space performs better than the other three methods although certain of the other methods follow the recommendation put forward by some investigators that higher order moments (moments of order 3 or more) should be avoided in flood frequency estimation. It is argued in the present study that the use of higher order moments should not be avoided simply because they have high variability because it is not only the variability of the moments which determines the degree of variability of the estimated design flood events but also the correlation that exists between these moments. Some recommendations are given at the end of the study aimed at achieving better efficiency in flood frequency research at a period where more and more distributions and methods of estimation are being proposed. 相似文献
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Parameter and quantile estimation of the 2-parameter kappa distribution by maximum likelihood 总被引：1，自引：1，他引：0
Fran?ois Aucoin Fahim Ashkar Lampouguin Bayentin 《Stochastic Environmental Research and Risk Assessment (SERRA)》2012,26(8):1025-1039
Asymptotic properties of maximum likelihood parameter and quantile estimators of the 2-parameter kappa distribution are studied. Eight methods for obtaining large sample confidence intervals for the shape parameter and for quantiles of this distribution are proposed and compared by using Monte Carlo simulation. The best method is highlighted on the basis of the coverage probability of the confidence intervals that it produces for sample sizes commonly found in practice. For such sample sizes, confidence intervals for quantiles and for the shape parameter are shown to be more accurate if the quantile estimators are assumed to be log normally distributed rather than normally distributed (same for the shape parameter estimator). Also, confidence intervals based on the observed Fisher information matrix perform slightly better than those based on the expected value of this matrix. A hydrological example is provided in which the obtained theoretical results are applied. 相似文献
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Mohammad Abou Romieh Rob Westaway Mohamad Daoud Yousef Radwan Rayan Yassminh Ahlam Khalil Abeer Al‐Ashkar Susan Loughlin Katherine Arrell David Bridgland 《地学学报》2009,21(6):427-437
The Africa–Arabia plate boundary comprises the Red Sea oceanic spreading centre and the left‐lateral Dead Sea Fault Zone (DSFZ); however, previous work has indicated kinematic inconsistency between its continental and oceanic parts. The Palmyra Fold Belt (PFB) splays ENE from the DSFZ in SW Syria and persists for ～400 km to the River Euphrates, but its significance within the regional pattern of active crustal deformation has hitherto been unclear. We report deformation of Euphrates terraces consistent with Quaternary right‐lateral transpression within the PFB, indicating anticlockwise rotation (estimated as 0.3° Ma?1 about 36.0°N 39.8°E) of the block between the PFB and the northern DSFZ relative to the Arabian Plate interior. The northern DSFZ is shown to be kinematically consistent with the combination of Euler vectors for the PFB and the Red Sea spreading, resolving the inconsistency previously evident. The SW PFB causes a significant earthquake hazard, previously unrecognized, to the city of Damascus. 相似文献
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Computational Geosciences - History matching algorithms usually converge to the most prominent solution in the hypercube of parameter space defined by bound values. Here, we present a workflow to... 相似文献