Conditioned Simulations of Random Velocity Fields

In petroleum exploration and production, it is essential to have good estimations of the uncertainties on the reserves. Uncertainties on the velocity model used during the data processing are of major importance in this estimation. The generation of several velocity fields gives access to a quantified estimation of the uncertainties due to the velocity model inversion. The use of statistical methods helps in generating several important, equiprobable velocity fields, matching all the available velocity information. This paper presents an efficient simulation algorithm to generate instantaneous velocity fields, constrained by the distribution of values measured at the wells, and calibrated by the stacking velocities, taken as root-mean-square velocities. The simulations also match the covariance model given for the instantaneous velocity fields. The method is developed in a simple one-layer case with constant velocity, and then extended to more realistic situations. Finally, a real data application is shown, using data provided by ENI–Agip Division, and the efficiency of the proposed simulation method is discussed.     

3D modelling strategy for weather radar data analysis

Weather radar data, which have obvious spatial characteristics, represent an important and essential data source for weather identification and prediction, and the multi-dimensional visualization and analysis of such data in a three-dimensional (3D) environment are important strategies for meteorological assessments of potentially disastrous weather. The previous studies have generally used regular 3D raster grids as a basic structure to represent radar data and reconstruct convective clouds. However, conducting weather radar data analyses based on regular 3D raster grids is time-consuming and inefficient, because such analyses involve considerable amounts of tedious data interpolation, and they cannot be used to address real-time situations or provide rapid-response solutions. Therefore, a new 3D modelling strategy that can be used to efficiently represent and analyse radar data is proposed in this article. According to the mode by which the radar data are obtained, the proposed 3D modelling strategy organizes the radar data using logical objects entitled radar-point, radar-line, radar-sector, and radar-cluster objects. In these logical objects, the radar point is the basic object that carries the real radar data unit detected from the radar scan, and the radar-line, radar-sector, and radar-cluster objects organize the radar-point collection in different spatial levels that are consistent with the intrinsic spatial structure of the radar scan. Radar points can be regarded as spatial points, and their spatial structure can support logical objects; thus, the radar points can be flexibly connected to construct continuous surface data with quads and volume data with hexahedron cells without additional tedious data interpolation. This model can be used to conduct corresponding operations, such as extracting an isosurface with the marching cube method and a radar profile with a designed sectioning algorithm to represent the outer and inner structure of a convective cloud. Finally, a case study is provided to verify that the proposed 3D modelling strategy has a better performance in radar data analysis and can intuitively and effectively represent the 3D structure of convective clouds.     

A finite element formulation in Lagrangian co-ordinates for heat and fluid flow in compacting sedimentary basins

This article presents a numerical model of heat and fluid flow in compacting sedimentary basins formulated in Lagrangian co-ordinates. The Lagrangian co-ordinates are the sediment particle positions of the completely compacted basin. A finite element formulation of excess water pressure and temperature in these Lagrangian co-ordinates is presented, in addition to an equivalent formulation in the real co-ordinates. The later formulation is also Lagrangian of nature, since the elements of the grid in the real co-ordinates always frame the same sediment particles. In other words, it is the Lagrangian grid mapped to the real space. This is done in an iterative loop which solves for excess water pressure, and then updates the real co-ordinates of the sediment particles. By comparing the two finite element formulations it is concluded that the one in real space is the simplest, most efficient and most precise. The model is validated by comparison with two dimensionless one-dimensional solutions, one analytical for the linear case, and one numerical for the non-linear case. Both these one-dimensional solutions are obtained on the unit interval, where the moving top boundary caused by continuous sedimentation is incorporated.     

莺琼盆地流体包裹体对热液活动及油气运移的示踪作用

流体包裹体对地下热液活动及油气运移具有较好的示踪作用,尽管在确定最高古地温及其时间方面存在一些不确定性,为了评价均一温度的可靠性,该文首先用物质平衡法推导出了体测温的数学模型,模型表明,体积表明,体积较大的包体测温数据较准确,对莺琼盆地包体测温数据系统分析研究表明,该区包体的均一温度主要受来自深部３０００～４０００米的热液活动控制,流体包裹体发育与超压层埋深,烃源岩生排烃作用而引起的热液活和油气运     

用区间有限元计算边坡荷载组合效应

边坡工程的稳定性受多种因素的影响,其荷载具有不确定性,可以用具有上、下限的区间数来表示,提出了用区间数学和有限元结合构成的区间有限元方法来求解边坡变形。以古树包边坡的变形为例,研究了该方法的可行性,并与常规有限元计算结果进行了比较,实例计算结果表明,该方法用于计算具有不确定性参数和荷载的工程问题的变形是有效的,与常规有限元的要考虑多种工况相比,计算工作量大大减少,使用简便,而计算结果却能满足工程需要,适合计算边坡工程。     

Determining the uniqueness of best-fit trishear models

We show the application of a simulated annealing algorithm to trishear inverse modeling. The algorithm traverses the parameter space in search for best-fit models without being trapped in local minima, and thus sampling for more possible solutions globally. Simulated annealing is a robust and efficient technique to determine the uniqueness of best-fit trishear models; the spread of possible trishear models that can fit a structure. We first apply the algorithm to a decameter-size, contractional fault-propagation fold in west-central Taiwan, for which there is an exceptional exposure of pre-growth and growth strata. Simulated annealing shows that even for this complete fold dataset with low uncertainties, there is a range of models and fault slip/uplift histories that can fit the data, with the consequent implications for the assessment of seismic hazard. We then apply the algorithm to a kilometer-size, extensional fault-propagation fold, the Hadahid monocline, Gulf of Suez Rift, Egypt. In this monocline there is only surface coverage in the footwall anticline areas and the algorithm was used to delimit the range of possible models that can fit the data and their uncertainties, thus avoiding biases in the interpretation. Simulated annealing suggests that the along-strike structural variability of the monocline can result from along-strike variability in fault slip, fault propagation to fault slip ratio and depth of fault nucleation. Both examples illustrate the benefits of searching for a possible range of models rather than a precise best-fit model when modeling fault-propagation folds. In an attempt to understand which parameters control fault development, and also how the spread of possible solutions varies with fold growth, we apply the algorithm to four sequential stages of a published, analog clay model of an extensional forced fold. The inversions of the natural examples and the analog model suggest that the spread of the possible models is a manifestation of the data uncertainties, the suitability of the trishear model, fold evolution, and rock mechanical properties.     

Site selection for managed aquifer recharge using fuzzy rules: integrating geographical information system (GIS) tools and multi-criteria decision making

One of the most important water-resources management strategies for arid lands is managed aquifer recharge (MAR). In establishing a MAR scheme, site selection is the prime prerequisite that can be assisted by geographic information system (GIS) tools. One of the most important uncertainties in the site-selection process using GIS is finite ranges or intervals resulting from data classification. In order to reduce these uncertainties, a novel method has been developed involving the integration of multi-criteria decision making (MCDM), GIS, and a fuzzy inference system (FIS). The Shemil-Ashkara plain in the Hormozgan Province of Iran was selected as the case study; slope, geology, groundwater depth, potential for runoff, land use, and groundwater electrical conductivity have been considered as site-selection factors. By defining fuzzy membership functions for the input layers and the output layer, and by constructing fuzzy rules, a FIS has been developed. Comparison of the results produced by the proposed method and the traditional simple additive weighted (SAW) method shows that the proposed method yields more precise results. In conclusion, fuzzy-set theory can be an effective method to overcome associated uncertainties in classification of geographic information data.     

考虑抽样不确定性的水文设计值估计

水文频率分析计算过程中,水文极值样本系列容量一般都较小、代表性不高,使得水文设计值估计具有不确定性。利用Bootstrap方法,研究样本抽样不确定性对水文设计值的影响。与传统水文频率分析方法相比,基于Bootstrap方法不仅可提供设计值的点估计和区间估计,同时能够对设计值的不确定性进行定量评价。此外,基于Bootstrap技术,结合矩法、权函数法及线性矩法,设置3套方案,分析了该方法在不同参数估计方法间的有效性。以南通市1970-2011年共42年的年降雨量数据资料为例,对所提方法进行实例应用分析,结果表明,从期望设计值、90%置信区间及最终设计值角度而言,基于所提方法的设计成果受参数估计方法的选取影响不大,且可回避规范中B值诺莫图通用性较差及误差显著问题。     

Statistical Characterization of a Random Velocity Field Using Stacking Velocity Profiles

In petroleum exploration and production, it is important to have good estimations of the uncertainties on the reserves. Uncertainties in the velocity model used during the data processing are of major importance in this estimation. The use of geo-statistical tools can help in dealing with these uncertainties. Up to now, a strong limitation has been the inability to properly merge velocity functions measured in the wells with seismic velocity data. This was due to the different “supports” among the two, i.e. the well velocity may be regarded as a direct measurement of the instantaneous velocity field, while the seismic velocities correspond to an “average along the travelled paths” of this field. The problem is that, apart from the well positions, the instantaneous velocity field is out of reach. Luckily, for many practical applications, it is enough to know just its covariance model. However, no algorithmic method is available in the literature to yield the covariance model, and geologists are forced to use arbitrary distributions. The present paper proposes an original method to obtain a good estimate of this covariance model, using widely available information, mainly seismic stacking velocities. This method was first developed in a simple one-layer case with constant velocity, and then extended to more realistic situations. Finally, a real data application is performed, which highlights the robustness of the resulting estimation.     

有限数据条件下边坡可靠度分析的Bootstrap方法

基于Bootstrap抽样技术提出了有限数据条件下边坡可靠度分析方法。简要介绍了传统的边坡可靠度分析方法。采用Bootstrap方法模拟了抗剪强度参数概率分布函数的统计不确定性。以无限边坡为例研究了抗剪强度分布参数和分布类型不确定性对边坡可靠度的影响规律。结果表明：基于有限数据估计的样本均值、样本标准差和AIC值具有较大的变异性,这种变异性进一步导致了抗剪强度参数概率分布函数存在明显的统计不确定性。在考虑抗剪强度参数概率分布函数的统计不确定性时,边坡可靠度指标应为具有一定置信度水平的置信区间,而不是传统可靠度分析中的固定值。边坡可靠度指标的置信区间变化范围随安全系数的增加而增大,同时考虑分布参数和分布类型不确定性计算的可靠度指标具有更大的变异性和更宽的置信区间变化范围。Bootstrap方法为有限数据条件下抗剪强度参数概率分布函数统计不确定性的模拟以及边坡可靠度的评估提供了一条有效的途径。     

基于三维激光扫描的空间地物建模

利用地面三维激光扫描仪获取的空间数据,进行了三维空间地物建模研究。以建筑物建模为例,首先从原始数据中分离提取建筑物,然后对得到的建筑物数据进行去噪处理,再通过整体匹配纠正并对原始测量数据进行重新采样和拼接配准,建立了由三角网构成的三维表面模型。结果表明,所构建的三维表面模型较好地表达了建筑物的几何特征,户外实验也验证了上述过程可以实现对建筑物快速三维建模。     

压制地震资料中工业电干扰的 余弦逼近法的改进及应用

在对实际资料分析的基础上, 笔者提出对工业电干扰频率进行精细扫描、标准余弦信号超采样及深层振幅统计等方法对目前常用的余弦逼近法进行改进, 理论分析及实际资料的处理结果对比表明了改进后的方法更实用、精度更高。     

Effects of Release Conditions Uncertainty on Avalanche Hazard Mapping

Dynamical models for calculating snow avalanche motion have gained growingimportance in recent years for avalanche hazard assessment. Nevertheless, inherentuncertainties in their input-data specification, although well acknowledged, areusually not explicitly incorporated into the analysis and considered in the mappingresults. In particular, the estimate of avalanche release conditions is affected bystrong uncertainties when associated to a return period. These sources of error arenormally addressed through sensitivity analysis or conservative parameters estimate.However, each of these approaches has limitations in assessing the statistical implications of uncertainties.In the present paper the problem of release scenarios randomness is looked at following a Monte Carlo procedure. This statistical sampling-analysis method allows the evaluation of the probability distributions of relevant variables for avalanche hazard assessment – such as runout distance and impact pressure – once the release variables – essentially releasedepth and release length – are expressed in terms of probability distributions, accounting explicitly for inherent uncertainties in their definition. Both the theoretical framework of this procedure and its application to a real study case are presented. As initial step of this research in the present work the attention is mainly focused on flowing avalanches descending on open slopes. Therefore, the one-dimensional version of VARA dynamic models is usedfor avalanche simulations.     

关于大地电磁的静校正问题

本文从理论上严格地论述了大地电磁测深曲线静态位移的原理,简单介绍了目前国内外所采用的静校正方法,并着重分析了我们所用的压制表层电性不均匀干扰的办法及其效果。     

大地电磁法的1D无偏差贝叶斯反演

应用贝叶斯理论对一维(1D)大地电磁反演问题进行无偏差不确定度分析。在贝叶斯理论中,测量数据和先验信息包含在后验概率密度函数(PPD)中,它可以解释成模型的单点估计和不确定度等贝叶斯推断,这些信息的获取需要对反演问题进行优化求最优模型和在高维模型空间中对PPD进行采样积分。采样的完全、彻底和效率,对反演结果有着重要的影响。为了使采样更有效、更完全,数值积分采用主分量参数空间的Metropolis Hastings采样,并采用了不同的采样温度。在反演中,同时采用了欠参数化和超参数化方法,数据误差和正则化因子被当成随机变量。反演结果得到各参数的不确定度、参数间的相关关系和不同深度模型的不确定度分布。COPROD1数据的反演结果表明模型空间中存在双峰结构。非地电参数在反演中得到了约束,说明数据本身不仅包含地球物理模型信息(电导率等),还包含了这些非地电参数的信息。     

Optimal operation of a micro-grid containing energy resources and demand response program

In profit-based unit commitment, the objective of programming is to maximize profit and optimize generation. Practically, the gross profit depends not only on the revenue but also on the total expenditures. In this article, an efficient algorithm is suggested to assess the effect of uncertainties in determining 24-hour optimal strategy of a microgrid (MG) containing wind farms, photovoltaic, fuel cell, combined heat and power units, boiler, and energy storage devices (ESDs). The optimization problem is presented to determine the optimal points for the energy resources generation and to maximize the expected profit considering demand response (DR) programs and uncertainties. The uncertainties include wind speed, photovoltaic power generation (PVPG), market price, power, and thermal load demand. For modeling uncertainties, an effort has been made to predict uncertainties through the hybrid method of wavelet transform (WT)-artificial neural network (ANN)-imperialist competitive algorithm (ICA). In this study, three cases are assessed to confirm the performance of the proposed method. In the first case study, programing MG is isolated from the grid. In the second case study, which is grid-connected mode the WT-ANN-ICA and WT-ANN uncertainties predictions methods are compered. In the third case, which is grid-connected mode the effect of DR programs on the expected profit of energy resources is assessed.     

基于IBUNE方法的水文模型不确定性分析

在贝叶斯理论框架下,根据一种可结合多个水文模型给出模拟或预报结果的IBUNE方法探讨了水文模型的输入、参数以及结构的不确定性问题。将SCEM-UA算法和EM算法嵌入新安江和TOPMODEL水文模型用于参数优化和模型平均,进而将输入与参数的综合不确定性处理后得到的预报量后验分布进行多模型综合,据此对水文模型的不确定性及其对水文模拟结果的影响进行评价。以湖南洣水流域龙家山水文站以上集水区域为例进行了应用研究,结果表明,IBUNE方法能够有效估计水文模型的不确定性,并能给出合理的概率预报区间。     

A probabilistic model to improve reconciliation of estimated and actual grade in open-pit mining

Many of the open-pit mines suffer from the lack of reconciliation between estimated and actual grades. In a mining operation, grade reconciliation is the comparison between the values of the estimated grade calculated in exploration stage and the actual grade obtained from more reliable data such as blast holes?? samples. Many different factors affect the degree of reconciliation in a mining operation. In this paper, the factors related to estimated grade which affect the reconciliation process in the exploration stage of the orebody are investigated. These factors constitute the sources of uncertainty for the upcoming phases of the mining life. Among these parameters, the inherent variability, statistical uncertainty, and systematic uncertainty are the most important factors. In this work, these parameters are studied in further detail, and, accordingly, for each of these uncertainties, a correction factor is determined in the proposed model. The model was applied to the study of real data taken from an iron open-pit mine in Iran. The results of the case study indicated that the systematic uncertainty, inherent variability, and statistical uncertainty are, in order, the main sources of uncertainty on grade reconciliation process. Applying the correction factors to estimated grade values has increased the amount of grade reconciliation from 10%, at original condition, to 50%, at new condition, in the case study.     

An approximate dynamic programming approachto decision making in the presence of uncertainty for surfactant-polymer flooding

The least squares Monte Carlo method is a decision evaluation method that can capture the effect of uncertainty and the value of flexibility of a process. The method is a stochastic approximate dynamic programming approach to decision making. It is based on a forward simulation coupled with a recursive algorithm which produces the near-optimal policy. It relies on the Monte Carlo simulation to produce convergent results. This incurs a significant computational requirement when using this method to evaluate decisions for reservoir engineering problems because this requires running many reservoir simulations. The objective of this study was to enhance the performance of the least squares Monte Carlo method by improving the sampling method used to generate the technical uncertainties used in obtaining the production profiles. The probabilistic collocation method has been proven to be a robust and efficient uncertainty quantification method. By using the sampling methods of the probabilistic collocation method to approximate the sampling of the technical uncertainties, it is possible to significantly reduce the computational requirement of running the decision evaluation method. Thus, we introduce the least squares probabilistic collocation method. The decision evaluation considered a number of technical and economic uncertainties. Three reservoir case studies were used: a simple homogeneous model, the PUNQ-S3 model, and a modified portion of the SPE10 model. The results show that using the sampling techniques of the probabilistic collocation method produced relatively accurate responses compared with the original method. Different possible enhancements were discussed in order to practically adapt the least squares probabilistic collocation method to more realistic and complex reservoir models. Furthermore, it is desired to perform the method to evaluate high-dimensional decision scenarios for different chemical enhanced oil recovery processes using real reservoir data.     

Marquardt算法磁测三维反演方法策略

在磁法三维反演中,反演对象数目往往巨大,受限于当今的计算机技术与计算方法,在超大规模方程组的求解时遇到极大的困难。所以,在解决实际问题时能力非常有限,对于Marquardt算法磁测三维反演问题尤为突出。为此,在这里提出了两个较为有效的方法策略,即将模型组体化和将组体分类,并在理论应用中得到了较好的效果。