基于含水合物多孔介质复电导率的渗透率测试有限元仿真研究

渗透率是影响天然气水合物储层产气效率的关键参数，野外尚缺少实时监测水合物储层渗透率动态变化的技术，实验室内测试渗透率的方法存在成本高、周期长、可靠性低等问题。研究了一种基于复电导率的含水合物沉积物渗透率测试新方法。首先，针对含水合物多孔介质建立了能够计算其渗透率和复电导率的有限元数值模型，然后开展了不同水合物饱和度条件下的仿真实验，获取了0~40%水合物饱和度时多孔介质的流场和电场响应参数，分别探讨了孔隙中水合物及其饱和度变化对复电导率虚部和渗透率的影响规律和机理，最后建立并验证了基于复电导率虚部的含水合物多孔介质渗透率评价模型，为深入研究基于激发极化原理的含水合物沉积层渗透率测试新技术提供了理论和模型基础。     

融合深度置信网络与与核极限学习机算法的核磁共振测井储层渗透率预测方法

由于低孔低渗储层孔隙结构较为复杂,现有核磁共振（NMR）测井渗透率模型对于低孔低渗储层预测精度不高。为此,提出一种融合深度置信网络（DBN）算法与核极限学习机（KELM）算法的渗透率预测方法。该方法首先对DBN模型进行预训练,然后将KELM模型作为预测器放置在训练好DBN模型后,利用训练数据进行有监督的训练,最终形成深度置信-核极限学习机（DBKELMN）模型。考虑到该模型需充分利用反映孔隙结构的横向弛豫时间谱信息,将离散化后的核磁共振测井横向弛豫时间谱作为输入,渗透率作为输出,确定NMR测井横向弛豫时间谱与渗透率的函数关系,并基于该函数关系对储层渗透率进行预测。实例应用表明,融合DBN算法与KELM算法的渗透率预测方法是有效的,预测样本的平均绝对误差（MAE）较斯伦贝谢道尔研究中心（SDR）模型降低了0.34。融合DBN算法与KELM算法的渗透率预测方法可提高低孔渗储层渗透率预测精度,可应用于油气田勘探开发。     

特性关系粗糙集下属性值粗化细化时近似集增量更新方法研究

不完备信息系统是一般信息系统的推广,在现实中具有广泛的应用.信息系统动态变化时,对象的近似集会产生相应的变化.研究如何利用原有近似集信息来进行近似集的更新具有重要意义.信息系统动态变化主要可以从属性值粗化细化、属性集粗化细化、时象集粗化细化3个方面考虑.现仅讨论属性值粗化细化时近似集的增量更新方法,给出了不完备信息系统中属性值粗化细化的定义,讨论了在不完备信息系统下的特性关系粗糙集模型中属性值粗化细化时近似集的增量更新方法,并通过实例验证了方法的有效性.     

RBF神经网络在储层表征中的应用研究

研究利用RBF神经网络技术进行石油储层表征中有关储层参数的计算与岩性的识别;建立了储层参数(渗透率)预测模型与岩性识别模型,并利用该两个模型对未知样本进行预测,预测结果与实际测量结果相比具有较好的一致性,其渗透率预测精度与收敛速度较BP神经网络模型有了很大的提高;应用表明,RBF神经网络在储层表征问题中有着广阔的应用前景。     

优势关系下属性值粗化细化时近似集分析

基于优势关系粗糙集模型反映属性间的偏好情况,实际上多数数据库中的数据是动态变化的。如何利用已有的信息更新近似集对于提高知识发现效率有重要意义。提出不完备信息系统在优势关系下属性值粗化细化的定义,讨论优势关系下不完备信息系统中属性值粗化细化时近似集的变化情况,对比分析优势关系下属性值粗化细化前后的粗糙近似精度和粗糙近似质量。通过实例分析验证了该方法的有效性。     

基于权重联系度粗集理论的增量式知识发现

在实际生活中,信息系统的增量数据会不断产生,如何充分利用以前计算的结果结合新产生的数据进行新的知识发现,这是有意义的。针对这样的问题,提出了基于权得联系度的粗集模型,它着重考虑了条件属性重要性存在差异来建立粗集模型,而条件属性重要性可以通过以前数据的知识发现计算出来,于是利用基于权重联系度的粗集模型在对新产生的数据进行知识发现时,利用了以前的数据信息。建立了基于权重联系度的粗集模型及其对应的属性和属性值约简理论,最后通过一个示例来演示增量式知识发现的方法。     

捷联惯导系统方位失准角对准技术研究

研究低成本捷联惯导系统中静基座方位失准角对准问题。传统采用的MIMU精度较低,误差模型的非线性化。为改善方位失准角的对准精度,提出了一种UPF方法的方位失准角对准方法。建立了关于磁强计辅助MIMU的粗对准模型,并将磁强计辅助完成粗对准的方位角偏差引入精对准的线性和非线性误差模型之中,给出了一种简化的UPF递推算法,对比了不同误差模型下的三种滤波方法的效果。仿真结果表明,无论是线性还是非线性误差模型下,UPF都获得了比KF和UKF更优的对准精度和收敛性,具有重要理论意义和应用参考价值。     

基于图粗化的层次图池化方法研究

图神经网络(Graph Neural Networks, GNNs)已被证明能有效对图结构数据进行建模，池化机制在使用GNN模型提取图层次特征过程中至关重要，近年来已经引起了越来越多研究者们的关注.现有基于聚类的层次图池化方法要么需要增加额外的神经网络层以实现特征图的粗化；要么不能从全局角度捕获节点在图中的重要性大小.针对以上问题，本文提出一种基于图粗化的层次图池化方法(Hierarchical Graph Pooling Based on Graph Coarsening, HGP-GC),用于学习图的层次特征表示.该方法主要包括图结构粗化和图属性粗化两个部分.利用结构粗化实现特征图尺寸的缩减；利用属性粗化突显图中重要节点对图级表示的关键作用.通过将HGP-GC池化策略与现有神经网络相结合，在不同规模公共数据集上的图分类实验结果证明了HGP-GC的有效性.     

三维对流扩散方程的多重网格算法研究

研究了三维对流扩散方程基于有限差分法的多重网格算法。差分格式采用一般网格步长下的二阶中心差分格式和四阶紧致差分格式,建立了与两种格式相适应的部分半粗化的多重网格算法,构造了相应的限制算子和插值算子,并与传统的等距网格下的完全粗化的多重网格算法进行了比较。数值研究结果表明,对于各向异性问题,一般网格步长下的部分半粗化多重网格算法比等距网格下的完全粗化多重网格算法具有个更高的精度和更好的收敛效率。     

建筑物表面压力分布预测仿真研究

研究高层建筑物表面压力分布的准确预测问题。针对工程的实际应用,由于建筑物与风之间的相互作用加在建筑物上,使建立压力分布的准确预测模型较为困难。为得到准确预测建筑物表面压力分布的模型,采用风场给定的大气边界层入口条件,使用不同湍流模型和粗化网格,对立方体建筑物表面压力分布进行计算。分析发现,与测试结果相比雷诺平均和分离涡模型在立方体建筑物表面压力系数计算偏差较大,而大涡仿真计算结果吻合度较好。仿真结果表明,给定合适边界条件和计算方法,使用粗化网格的大涡模拟计算能够得到准确的压力系数计算结果,可以为更加复杂的工程实际计算提供参考和应用依据。     

Absolute Permeability Upscaling for Superelement Modeling of Petroleum Reservoir

A technique for local upscaling of absolute permeability is proposed intended for the superelement modeling of petroleum reservoir development. The upscaling is performed for every block of an unstructured superelement grid based on solving a series of stationary one-phase flow in reservoir problems on a refined grid with the initial permeability field under various boundary conditions reflecting the characteristic structural variants of the filtrational flow and taking into account the presence or absence of wells inside the block. The resulting components of the effective permeability tensor in each superelement are sought from the solution of the problem on minimizing the deviations of the normal flows through the faces of the superelement averaged on a refined computational grid from those approximated on a coarse superelement grid. The application of the method is demonstrated by examples of the reservoir of the periodic and nonperiodic structure. The method is compared with the traditional techniques for local upscaling.     

Geometric characterization,hydraulic behavior and upscaling of 3D fissured geologic media

In this article, we present numerical modeling and upscaling procedures for highly fissured and discontinuous geologic media, such as ‘karsts’. In particular, we propose a geomorphological generation model, and we address the ‘upscaling’ problem for flow in a highly fissured porous medium (‘what is the macroscale hydraulic behavior of the fissured porous medium?’). The morphological model is partly Boolean, based on statistical distributions of discrete objects (voids), combined with a (random) continuum representation for the underlying porous matrix. Various methods for constraining these two types of media are discussed (self-consistent thresholding; genetic dissolution). Hydraulic simulations are then conducted with the 3D finite volume code BIGFLOW, for the case of 3D composite media with constant matrix and high ‘fissure/matrix’ permeability contrast. The hydrodynamic equations are based on either Darcy’s linear head loss law, or on a linear/quadratic combination of Darcy and Ward–Forchheimer quadratic law (inertial effects). The numerical experiments are conducted for saturated steady flow under permeametric boundary conditions. They are used to analyze the equivalent macroscale behavior of fissured media, as well as quasi-percolation effects, in comparison with analytical results and bounds (Darcian case, low Reynolds). In addition, at moderate to large Reynolds numbers, the macroscale effects of non-Darcian (inertial) head losses are also analyzed.     

An upscaling method using coefficient splitting and its applications to elliptic PDEs

In this paper, we develop an upscaling method using coefficient splitting techniques. Green’s function is constructed using the differential operator associated with the first part of the splitting. An effective upscaling coefficient is recursively calculated by Green’s function. The computation of the upscaling process involves some independent steps. Combining the proposed upscaling method with the stochastic collocation method, we present a stochastic space reduction collocation method, where the stochastic collocation method is performed on a lower dimension stochastic space than the full-dimension stochastic space. We thoroughly analyze the convergence of the proposed upscaling method for both deterministic and stochastic elliptic PDEs. Computation complexity is also addressed for the stochastic upscaling method. A number of numerical tests are presented to confirm the convergence analysis.     

Upscaling relative phase permeability for superelement modeling of petroleum reservoir engineering

A technique for locally rescaling (upscaling) the functions of the relative phase permeability (RPP) has been developed, which minimizes the error in the approximating the phase filtration rates for the superelement modeling of waterflooding a layered heterogeneous oil reservoir. The RPP is locally upscaled for each superelement based on the solution of two-dimensional two-phase filtration problems on a refined computational grid. Modified RPP functions (MFRPPs) are represented in the parametric form; i.e., the values of the parameters are sought when solving the problem of minimizing the deviations of the averaged and approximated phase velocities at the sites corresponding to the faces of the superelement. The efficiency of applying MFRPP to superelement modeling is illustrated by an example of a model reservoir region where oil is extracted using injection and production wells and by an example of waterflooding at a real oilfield.     

Geometric characterization, hydraulic behavior and upscaling of 3D fissured geologic media

In this article, we present numerical modeling and upscaling procedures for highly fissured and discontinuous geologic media, such as ‘karsts’. In particular, we propose a geomorphological generation model, and we address the ‘upscaling’ problem for flow in a highly fissured porous medium (‘what is the macroscale hydraulic behavior of the fissured porous medium?’). The morphological model is partly Boolean, based on statistical distributions of discrete objects (voids), combined with a (random) continuum representation for the underlying porous matrix. Various methods for constraining these two types of media are discussed (self-consistent thresholding; genetic dissolution). Hydraulic simulations are then conducted with the 3D finite volume code BIGFLOW, for the case of 3D composite media with constant matrix and high ‘fissure/matrix’ permeability contrast. The hydrodynamic equations are based on either Darcy’s linear head loss law, or on a linear/quadratic combination of Darcy and Ward–Forchheimer quadratic law (inertial effects). The numerical experiments are conducted for saturated steady flow under permeametric boundary conditions. They are used to analyze the equivalent macroscale behavior of fissured media, as well as quasi-percolation effects, in comparison with analytical results and bounds (Darcian case, low Reynolds). In addition, at moderate to large Reynolds numbers, the macroscale effects of non-Darcian (inertial) head losses are also analyzed.     

A Reversible Data Hiding Scheme for Interpolated Images Based on Pixel Intensity Range

Multimedia Tools and Applications - In this paper, we propose a novel interpolation and a new reversible data hiding scheme for upscaling the original image and hiding secret data into the...     

Control co-design of 13 MW downwind two-bladed rotors to achieve 25% reduction in levelized cost of wind energy

Wind energy is recognized worldwide as cost-effective and environmentally friendly and is among the fastest-growing sources of electrical energy. To further decrease the cost of wind energy, wind turbines are being designed at ever larger scales, which is challenging due to greater structural loads and deflections. Large-scale systems such as modern wind turbines increasingly require a control co-design approach, whereby the system design and control design are performed in a more integrated fashion. We overview a two-bladed downwind morphing rotor concept that is expected to lower the cost of energy at wind turbine sizes beyond 13 megawatts (MW) compared with continued upscaling of traditional three-bladed upwind rotor designs. We describe an aero-structural-control co-design process that we have used in designing such extreme-scale wind turbines, and we discuss how we were able to achieve a 25% reduction in levelized cost of energy for our final turbine design compared to a conventional upwind three-bladed rotor design.     

基于STL的油藏数据粗化程序库设计与实现

针对油藏数据粗化的应用,研究了三维数据的数据结构,结合泛型编程与面向对象编程,并按照STL的容器、算法、速代器的模式设计了数据粗化程序库,在这个库中可以使用STL中算法和设施,具有重用性和扩展性.     

Syntax highlighting in business process models

Sense-making of process models is an important task in various phases of business process management initiatives. Despite this, there is currently hardly any support in business process modeling tools to adequately support model comprehension. In this paper we adapt the concept of syntax highlighting to workflow nets, a modeling technique that is frequently used for business process modeling. Our contribution is three-fold. First, we establish a theoretical argument to what extent highlighting could improve comprehension. Second, we formalize a concept for syntax highlighting in workflow nets and present a prototypical implementation with the WoPeD modeling tool. Third, we report on the results of an experiment that tests the hypothetical benefits of highlighting for comprehension. Our work can easily be transferred to other process modeling tools and other process modeling techniques.     

On a numerical subgrid upscaling algorithm for Stokes–Brinkman equations

This paper discusses a numerical subgrid resolution approach for solving the Stokes–Brinkman system of equations, which is describing coupled flow in plain and in highly porous media. Various scientific and industrial problems are described by this system, and often the geometry and/or the permeability vary on several scales. A particular target is the process of oil filtration. In many complicated filters, the filter medium or the filter element geometry are too fine to be resolved by a feasible computational grid. The subgrid approach presented in this paper is aimed at describing how these fine details are accounted for by solving auxiliary problems in appropriately chosen grid cells on a relatively coarse computational grid. This is done via a systematic and careful procedure of modifying and updating the coefficients of the Stokes–Brinkman system in chosen cells. This numerical subgrid approach is motivated from one side from homogenization theory, from which we borrow the formulations for the so-called cell problem, and from the other side from the numerical upscaling approaches, such as Multiscale Finite Volume, Multiscale Finite Element, etc. Results on the algorithm’s efficiency, both in terms of computational time and memory usage, are presented. Comparison of the full fine grid solution (when possible) of the Stokes–Brinkman system with the subgrid solution of the upscaled Stokes–Brinkman system (including effective permeabilities for the quasi-porous cells), are presented in order to evaluate the accuracy and the efficiency. Advantages and limitations of the considered subgrid approach are discussed.