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1.
应用正交试验设计进行数值模型参数的敏感性分析   总被引:6,自引:0,他引:6  
结合深基坑重力式挡土墙侧向变形的有限元分析 ,提出了采用正交试验设计及其统计分析方法研究数值模拟结果对岩土参数敏感性的步骤。该方法能够区分影响计算结果的主要参数和次要参数 ,并对参数的敏感程度进行量化。实例分析表明 ,模拟结果只对个别参数的变化比较敏感 ,而其它参数对模拟结果影响较小。敏感性分析结果符合工程实践经验 ,表明该方法是可行的。  相似文献   

2.
Geologic uncertainties and limited well data often render recovery forecasting a difficult undertaking in typical appraisal and early development settings. Recent advances in geologic modeling algorithms permit automation of the model generation process via macros and geostatistical tools. This allows rapid construction of multiple alternative geologic realizations. Despite the advances in geologic modeling, computation of the reservoir dynamic response via full-physics reservoir simulation remains a computationally expensive task. Therefore, only a few of the many probable realizations are simulated in practice. Experimental design techniques typically focus on a few discrete geologic realizations as they are inherently more suitable for continuous engineering parameters and can only crudely approximate the impact of geology. A flow-based pattern recognition algorithm (FPRA) has been developed for quantifying the forecast uncertainty as an alternative. The proposed algorithm relies on the rapid characterization of the geologic uncertainty space represented by an ensemble of sufficiently diverse static model realizations. FPRA characterizes the geologic uncertainty space by calculating connectivity distances, which quantify how different each individual realization is from all others in terms of recovery response. Fast streamline simulations are employed in evaluating these distances. By applying pattern recognition techniques to connectivity distances, a few representative realizations are identified within the model ensemble for full-physics simulation. In turn, the recovery factor probability distribution is derived from these intelligently selected simulation runs. Here, FPRA is tested on an example case where the objective is to accurately compute the recovery factor statistics as a function of geologic uncertainty in a channelized turbidite reservoir. Recovery factor cumulative distribution functions computed by FPRA compare well to the one computed via exhaustive full-physics simulations.  相似文献   

3.
Leroy natural-gas storage site is an anticlinal, fault-bounded, aquifer-storage system located in Wyoming, USA. Based on its abundant data, uncontrolled leakage history and subsequent control by the facility operators, a modeling framework was developed for studying reservoir behavior, examining pressure and gas-inventory histories, as well as gas and brine leakage, and evaluating the sensitivity of that behavior to uncertainty about reservoir properties. A three-dimensional model capturing the bounding fault, layered geologic stratigraphy, and surface topography was calibrated by history data of reservoir pressure and gas inventory. The calibrated model predicted gas arrival at the ground surface that was consistent with the timing of observed gas bubbling into a creek. A global sensitivity analysis was performed to examine the parameters influencing fault leakage, and a geomechanical stability analysis was conducted to investigate the likelihood of fault reactivation. In general, it is shown that a discrete leakage pathway is required to explain the observed gas leakage and its subsequent operational control by reducing reservoir pressures. Specifically, the results indicate that fault leakage is a plausible explanation for the observed gas leakage. The results are relevant to other natural-gas storage sites, as well as other subsurface storage applications of buoyant fluids, such as CO2.  相似文献   

4.
Natural gas hydrate is widely distributed all over the world and may be a potential resource in the near future, whereas hydrate dissociation during the development affects wellbore stability and drilling safety. However, the present modeling of hydrate reservoir parameters ignored the influence of effective stress and only considered the hydrate saturation. In this paper, a series of stress sensitivity experiments for the unconsolidated sandstone were carried out, and the influence of mean effective stress on physical parameters was obtained; a comprehensive model for the physical parameters of hydrate reservoir was developed subsequently. With the help of ABAQUS finite element software, the established comprehensive model was verified by the use of the wellbore stability numerical model of hydrate reservoir. The verification results show that ignoring the effect of mean effective stress on the parameters of hydrate formation aggravates the invasion of drilling fluid into the hydrate formation. Besides, ignoring the stress sensitivity of reservoir physical parameters will underestimate the wellbore instability during hydrate drilling, which will be a threat to the safety of gas hydrate drilling. At the end of the drilling operation, the maximum plastic strain of the model for considering and not considering stress sensitivity was 0.0145 and 0.0138, respectively. Therefore, the established comprehensive model will provide a theoretical support for accurately predicting the engineering geological disasters in hydrate development process.  相似文献   

5.
生态模型在河口管理中的应用研究综述   总被引:1,自引:0,他引:1       下载免费PDF全文
河口作为河流和海洋的交汇地,具有生态交错带特性,其在自然和人类活动双重压力下发生着演变.生态模型是研究生态系统结构、功能及其时空演变规律以及生物过程对于生态系统的影响及其反馈机制的重要手段.采用不同方法对生态模型进行分类,综述各类生态模型的特性、优缺点及应用领域.讨论建模过程中模型变量与函数、模型整合及时空尺度、模型参数取值及不确定等关键技术问题.分析各类生态模型在河口生态工程设计、生态系统修复、生态系统评价、系统决策支持等管理领域的应用.尽管中国河口生态模型构建及应用已有一些成果,但与国外相比,在理论生态学及数据积累方面仍有一定差距.  相似文献   

6.
In this study, we introduce the application of data mining to petroleum exploration and development to obtain high-performance predictive models and optimal classifications of geology, reservoirs, reservoir beds, and fluid properties. Data mining is a practical method for finding characteristics of, and inherent laws in massive multi-dimensional data. The data mining method is primarily composed of three loops, which are feature selection, model parameter optimization, and model performance evaluation. The method’s key techniques involve applying genetic algorithms to carry out feature selection and parameter optimization and using repeated cross-validation methods to obtain unbiased estimation of generalization accuracy. The optimal model is finally selected from the various algorithms tested. In this paper, the evaluation of water-flooded layers and the classification of conglomerate reservoirs in Karamay oil field are selected as case studies to analyze comprehensively two important functions in data mining, namely predictive modeling and cluster analysis. For the evaluation of water-flooded layers, six feature subset schemes and five distinct types of data mining methods (decision trees, artificial neural networks, support vector machines, Bayesian networks, and ensemble learning) are analyzed and compared. The results clearly demonstrate that decision trees are superior to the other methods in terms of predictive model accuracy and interpretability. Therefore, a decision tree-based model is selected as the final model for identifying water-flooded layers in the conglomerate reservoir. For the reservoir classification, the reservoir classification standards from four types of clustering algorithms, such as those based on division, level, model, and density, are comparatively analyzed. The results clearly indicate that the clustering derived from applying the standard K-means algorithm, which is based on division, provides the best fit to the geological characteristics of the actual reservoir and the greatest accuracy of reservoir classification. Moreover, the internal measurement parameters of this algorithm, such as compactness, efficiency, and resolution, are all better than those of the other three algorithms. Compared with traditional methods from exploration geophysics, the data mining method has obvious advantages in solving problems involving calculation of reservoir parameters and reservoir classification using different specialized field data. Hence, the effective application of data mining methods can provide better services for petroleum exploration and development.  相似文献   

7.
At various stages of petroleum reservoir development, we encounter a large degree of geological uncertainty under which a rational decision has to be made. In order to identify which parameter or group of parameters significantly affects the output of a decision model, we investigate decision-theoretic sensitivity analysis and its computational issues in this paper. In particular, we employ the so-called expected value of partial perfect information (EVPPI) as a sensitivity index and apply multilevel Monte Carlo (MLMC) methods to efficient estimation of EVPPI. In a recent paper by Giles and Goda, an antithetic MLMC estimator for EVPPI is proposed and its variance analysis is conducted under some assumptions on a decision model. In this paper, for an improvement on the performance of the MLMC estimator, we incorporate randomized quasi-Monte Carlo methods within the inner sampling, which results in an multilevel quasi-Monte Carlo (MLQMC) estimator. We apply both the antithetic MLMC and MLQMC estimators to a simple waterflooding decision problem under uncertainty on absolute permeability and relative permeability curves. Through numerical experiments, we compare the performances of the MLMC and MLQMC estimators and confirm a significant advantage of the MLQMC estimator.  相似文献   

8.
Sensitivity and uncertainty analyses methods for computer models are being applied in performance assessment modeling in the geologic high-level radioactive-waste repository program. The models used in performance assessment tend to be complex physical/chemical models with large numbers of input variables. There are two basic approaches to sensitivity and uncertainty analyses: deterministic and statistical. The deterministic approach to sensitivity analysis involves numerical calculation or employs the adjoint form of a partial differential equation to compute partial derivatives; the uncertainty analysis is based on Taylor series expansions of the input variables propagated through the model to compute means and variances of the output variable. The statistical approach to sensitivity analysis involves a response surface approximation to the model with the sensitivity coefficients calculated from the response surface parameters; the uncertainty analysis is based on simulation. The methods each have strengths and weaknesses.  相似文献   

9.
以3D地震数据体为基础,使用相干分析技术和合成声波测井对发育在渤海湾盆地南部少浅海海域中的古生界碳酸盐岩和太古界花岗片麻岩中的潜山裂缝性储层进行了横向预测,在此基础上确定了有利部位。预测结果得到了实际钻探的证实。  相似文献   

10.
For water management purposes, information about an entire aquifer system is generally more important than information about a specific spring. Since a karstic aquifer system might drain to several outlets, conclusions derived from a single spring can be misleading for characterization and modeling. In this study we apply a conceptual model to an Alpine dolomite karst system in Austria. The particular challenge was that several small springs with strongly varying hydrological behavior and diffuse flow into surrounding streams drain this system. Instead of applying the model to a single spring, it was calibrated simultaneously to several observations within the system aiming to identify the karst system’s intrinsic hydrodynamic parameters. Parameter identification is supported by modeling the transport of water isotopes (δ18O). The parameters were transferred to the whole system with a simple upscaling procedure and a sensitivity analysis was performed to unfold influence of isotopic information on parameter sensitivity and simulation uncertainty. The results show that it is possible to identify system intrinsic parameters. But the sensitivity analysis revealed that some are hardly identifiable. Only by considering uncertainty reasonable predictions can be provided for the whole system. Including isotopic information increases the sensitivity of some intrinsic parameters, but it goes along with a sensitivity decrease for others. However, a possible reduction of prediction uncertainty by isotopic information is compensated by deficiencies in the transport modeling routines.  相似文献   

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