基于同步辐射X射线CT的无烟煤样孔隙分布表征

本文利用同步辐射X射线对一沁水盆地无烟煤样在24 keV的能量下进行了成像,并重构得到其CT切片。分别采用数字地形模型（DTM）和数据约束模型（DCM）对样品的CT切片进行分析。研究结果表明,对本文所用煤样,DTM计算得到的煤样孔隙率与真密度和视相对密度实验法测得孔隙率较为接近,但利用DTM确定的阈值进行阈值分割提取到的样品孔隙率与DTM计算所得孔隙率之间偏差较大。DCM计算得到的孔隙率与DTM计算得到的孔隙率及实验测试结果均较为接近。DCM模型考虑了样品CT成像过程中的部分体积效应,得到小于CT体元的孔隙分布信息,在一定程度上拓展了CT成像技术的表征尺度。DCM计算结果显示,煤样中孔隙更多与煤基质和矿物组分以部分占据CT体元的形式存在。      

多尺度多组分数字岩心构建与弹性模拟研究（英文）

常规数字岩心模型由于尺寸较小,对于非均质性较强的复杂岩心,难以具有代表性,模拟得到的岩石物理参数也难有参考性。以三组砂岩样品为例,本文提出了一种可行的构建多尺度多组分数字岩心的方法。利用CT对柱塞岩心和毫米柱塞样品进行不同分辨率的扫描成像,并利用改进的图像配准方法进行扫描图像的精确配准。对于高分辨率扫描图像,利用常规图像分割方法,将岩心分割为孔隙和不同的矿物组分。基于配准关系,构造低分辨率图像的灰度与孔隙度、矿物组分含量的关系曲线。将构造的关系曲线应用到低分辨率扫描图像的图像分割过程。完成分割之后的数字岩心集合即构成了多尺度、多组分的数字岩心模型。基于多尺度多组分数字岩心模型,考虑了四种矿物模型,分别研究了细尺度和粗尺度下随着模型尺寸变化,三组岩心样品弹性模量的变化规律。结果表明:利用多尺度多组分数字岩心模型能够克服常规模型存在的代表性问题,实现岩心不同尺度孔隙、矿物的准确表征。在大尺度上计算的岩石弹性参数更具备代表性,同时岩石矿物组分考虑的越充分,模拟结果与实验结果越吻合。     

鄂尔多斯盆地致密砂岩气藏微观孔喉球棍模型表征方法

以鄂尔多斯盆地J地区下石盒子组致密砂岩气藏储层为研究对象，利用Avizo软件的数据处理和数值模拟功能，处理多尺度三维CT成像技术提供的图像信息.提出核磁阈值分割法，应用该方法对研究区目的层岩石样品进行多尺度三维孔喉分维数重构，建立非常规致密砂岩气藏储层纳米级三维孔喉分布和孔喉球棍模型.利用数字岩心分析模块对孔隙空间进行计算，获得喉道半径、孔隙半径、配位数、喉道长度、喉道形状因子、孔隙形状因子等定量参数，进而应用上述表征参数进行孔喉结构定量评价.研究表明，纳米尺度下致密砂岩储层孔隙呈球状，喉道呈杆状、棍状和管束状分布，孔喉分布随机性强.多尺度三维CT成像技术具有无损、高分辨率等特点，能够在多个分辨率和不同视域获得较为清晰的二维、三维图像.建立的球棍模型，能够直观、定量表征孔喉大小、几何形态、空间分布、连通性等，对微细观尺度储层孔喉研究具有重要意义.     

基于FDK算法的三维CT系统性能评估理论方法研究

随着医学应用和工业应用对X射线剂量、三维物体的成像速度的要求越来越严格,三维CT成像已经成为必然趋势,因此有必要对三维CT系统性能进行研究。本文首先建立三维CT图像噪声的理论估计方法,接着提出了基于FDK算法的三维CT系统性能评估的4种解析计算方法,使用高斯差模型作为通道函数。通过实验我们验证了本文提出的三维CT系统性...     

反演地表质量变化的附有空间约束的三维加速度点质量模型法

重力卫星可以在相同误差尺度下对全球质量变化进行连续重复观测,并在近十余年来取得了巨大成功,探索重力卫星数据精化处理方法和相关应用研究具有重要意义.本文基于三维加速度点质量模型法的基本原理,进一步发展建立了时变重力场模型球谐位系数的变化和地面点质量变化的关系,可有效考虑地表质量变化导致的负荷形变的影响;引入等权形式、线性形式、指数形式和高斯形式的空间约束方法处理南北条带噪声和向下延拓导致的病态问题,并与零阶Tikhonov正则化方法进行对比分析.采用模拟数据和一个月的实测GRACE时变重力场模型计算全球质量变化,对三维加速度点质量模型法和几种空间约束方法进行对比分析验证.计算结果表明,对于3°等面积的全球格网质量点,高斯和指数形式空间约束方法的最优相关距离约为500km,等权和线性形式空间约束方法的最优相关距离约为600km,各方法均可有效处理条带噪声的影响,四种空间约束方法的计算效果优于零阶Tikhonov正则化方法,本文的相关方法为进一步利用三维加速度点质量模型法监测全球质量变化提供了借鉴.     

双源CT心脏图像的三维显示系统

针对心内复杂结构,本文结合三维虚拟内窥镜技术和二维常规观测截面功能,开发了双源CT心脏图像的显示系统。用户可以在本系统内以自动和交互式的两种方式观测心内结构。自动方式,对造影剂增强的数据部分进行基于欧式距离的三维骨架化得到规划路径,光线投射法根据已算出的欧式跳过空白区域,减少了绘制计算量;交互方式,用户可以随时从内窥镜视角切换到当前视点所在的任意截面,便于进行二维和三维的结构和病理综合分析。而且,本系统根据规划路径自动检测标准四腔切面,改善临床检查的效率。本系统采用基于CUDA的体绘制技术有效实现了对心内解剖结构更加直观的观测,便于心脏疾病的诊断和治疗。     

基于重力卫星数据监测地表质量变化的三维点质量模型法

利用卫星重力测量手段监测全球质量变化取得了巨大成功,本文基于牛顿万有引力定律在三维空间直角坐标系中导出利用重力卫星观测数据监测全球质量变化的三维点质量模型法,该方法可直接利用重力卫星的轨道和星间观测数据或时变重力场模型计算全球质量变化,由于利用卫星观测数据计算地表质量变化的向下延拓过程以及观测数据噪声的影响,需要采用合适的空间约束方程或正则化技术对解算结果进行约束或平滑处理.利用合成全球质量变化模型模拟一个月的GRACE双星轨道和星间距离变率数据计算全球质量变化,对三维点质量模型法进行分析验证,采用零阶Tikhonov正则化技术处理病态问题.结果表明,三维点质量模型法可有效用于重力卫星观测数据监测全球质量变化,为利用重力卫星观测数据监测全球质量变化提供一种可选的途径.     

基于小波变换的低剂量CT投影数据滤波方法研究

本文根据低剂量CT投影数据的噪声特性,提出了一种基于小波变换的低剂量CT投影数据三维块匹配(BM3D)滤波方法.新方法首先对经过Anscombe变换的低剂量CT投影数据进行小波分解,然后分别对分解后尺度系数和小波系数进行BM3D滤波,接着对滤波后的系数进行逆小波变换和Anscombe逆变换,最后对处理后的投影数据采用经...     

锥束CT图像重建算法在DSP上的加速方法研究

随着CT技术的发展,重建速度已成为CT系统的重要指标之一,图像重建加速的研究也成为CT研究的热点之一。DSP由于采用哈佛结构,具有专门的硬件乘法器以及广泛采用流水线操作等特点,已开始应用于图像重建加速。本文针对近年来开始应用的三维锥束CT的图像重建算法进行了DSP加速方法研究。首先介绍了DSP应用于图像重建的研究现状,其次,通过对三维重建的典型算法——FDK的算粒分解分析,结合DSP的硬件结构的特点,提出了一种基于DSP的CT图像重建的综合加速技术。该方法通过C的优化、汇编优化和编译优化的综合使用,充分利用了硬件结构和软件流水技术,采用TMS320C6455芯片实现了CT图像重建的加速计算,实验结果表明,该方法取得了较高加速比。     

基于注意力机制和迁移学习的COVID-19深度学习诊断方法

目的:结合2019新型冠状病毒（COVID-19）肺炎患者肺CT影像学特征,提出一种多级空间注意力机制（ML-SAM）下的肺CT图像自动诊断模型,探讨该模型在COVID-19辅助诊断上的价值。方法:收集目前公开的COVID-19患者肺CT数据样本,在深度迁移学习框架下引入空间注意力多级聚焦策略,将数据样本、注意力机制与深度迁移学习卷积神经网络相结合,构建可在肺CT图像上自动诊断COVID-19肺炎的融合模型。结果:本文建立的融合模型对肺CT图像具有较好的分类性能,模型对COVID-19的正确识别率可达95%,同时实现了弱监督条件下肺CT图像关键特征的有效聚焦和提取。结论:本文建立的融合模型可被放射科医生或医疗保健专业人员作为COVID-19爆发期间快速、有效筛查COVID-19病例的智能辅助工具。      

A multiple-point statistics algorithm for 3D pore space reconstruction from 2D images

Fluid flow behavior in a porous medium is a function of the geometry and topology of its pore space. The construction of a three dimensional pore space model of a porous medium is therefore an important first step in characterizing the medium and predicting its flow properties. A stochastic technique for reconstruction of the 3D pore structure of unstructured random porous media from a 2D thin section training image is presented. The proposed technique relies on successive 2D multiple point statistics simulations coupled to a multi-scale conditioning data extraction procedure. The Single Normal Equation Simulation Algorithm (SNESIM), originally developed as a tool for reproduction of long-range, curvilinear features of geological structures, serves as the simulation engine. Various validating criteria such as marginal distributions of pore and grain, directional variograms, multiple-point connectivity curves, single phase effective permeability and two phase relative permeability calculations are used to analyze the results. The method is tested on a sample of Berea sandstone for which a 3D micro-CT scanning image is available. The results confirm that the equi-probable 3D realizations obtained preserve the typical patterns of the pore space that exist in thin sections, reproduce the long-range connectivities, capture the characteristics of anisotropy in both horizontal and vertical directions and have single and two phase flow characteristics consistent with those of the measured 3D micro-CT image.     

基于小波变换模极大值法和阈值法的CSAMT静态校正

采用小波分析方法进行CSAMT静态校正时,传统方法对视电阻率数据进行多尺度小波分解后,将所有尺度的细节系数设置为零,然后进行重构获得校正后的视电阻率.这使得在压制静态效应的同时,会损失一部分大构造异常的信息.针对传统小波分析方法在CSAMT静态校正中存在的问题,本文提出了基于小波变换模极大值法和阈值法相结合的静态效应校正方法.先对视电阻率数据进行多尺度小波变换,得到每一尺度上的模极大值,然后计算李氏指数进行静态效应的判断,通过设置合理的阈值,进行静态效应的压制.借助于正演模型和实测数据,验证了本方法的有效性.结果证明,本文提出的方法在压制静态效应的基础上,能够最大限度地保留大构造异常的信息.     

Extraction of physically realistic pore network properties from three-dimensional synchrotron X-ray microtomography images of unconsolidated porous media systems

This paper presents application of a series of algorithms used to extract pore network structure from high-resolution three-dimensional synchrotron microtomography images of unconsolidated porous media systems. These algorithms are based on the three-dimensional skeletonization that simplifies the pore space to networks in the form of nodes connected to paths. Dilation algorithms were developed to generate inscribed spheres on the nodes and paths of the medial axis to represent pore-bodies and pore-throats of the network, respectively. The end result is a physically representative pore network structure, i.e. three-dimensional spatial distribution (i.e. x-, y-, and z-coordinates) of pore-bodies and pore-throats, pore-body size distribution, pore-throat size distribution, and the connectivity. Systems analyzed in this study include different glass bead systems and natural marine sand. The media ranged in size from 0.123 to 1.0 mm, while the image volumes ranged between 7.7 and 108.9 mm³. In addition to extracting the pore network structure, the porosity, specific surface area, and representative elementary volume analysis on the porosity were calculated. Spatial correlation between pore-body sizes in the network was investigated using semivariograms and integral scale concepts. The impact of resolution on the calculated property was also investigated.

In this work, we show that microtomography is an effective tool to non-destructively extract the structure of many systems. The quality of the datasets depends on photon energy, photon flux, size of the sample, type of the sample, and size of the sample ‘features’. Results show that the developed method of extracting pore network structure is applicable to ideal and natural porous media systems. The impact of resolution on the quantification of the network structure properties varies in its significance based on feature size of the system and the properties being calculated. Therefore, a thorough resolution sensitivity analysis should be carried out to determine the degree of error associated with a system imaged at a given resolution.     

Numerical estimation of carbonate rock properties using multiscale images

Characterizing the pore space of rock samples using three‐dimensional (3D) X‐ray computed tomography images is a crucial step in digital rock physics. Indeed, the quality of the pore network extracted has a high impact on the prediction of rock properties such as porosity, permeability and elastic moduli. In carbonate rocks, it is usually very difficult to find a single image resolution which fully captures the sample pore network because of the heterogeneities existing at different scales. Hence, to overcome this limitation a multiscale analysis of the pore space may be needed. In this paper, we present a method to estimate porosity and elastic properties of clean carbonate (without clay content) samples from 3D X‐ray microtomography images at multiple resolutions. We perform a three‐phase segmentation to separate grains, pores and unresolved porous phase using 19 μm resolution images of each core plug. Then, we use images with higher resolution (between 0.3 and 2 μm) of microplugs extracted from the core plug samples. These subsets of images are assumed to be representative of the unresolved phase. We estimate the porosity and elastic properties of each sample by extrapolating the microplug properties to the whole unresolved phase. In addition, we compute the absolute permeability using the lattice Boltzmann method on the microplug images due to the low resolution of the core plug images. In order to validate the results of the numerical simulations, we compare our results with available laboratory measurements at the core plug scale. Porosity average simulations for the eight samples agree within 13%. Permeability numerical predictions provide realistic values in the range of experimental data but with a higher relative error. Finally, elastic moduli show the highest disagreements, with simulation error values exceeding 150% for three samples.     

基于有限元数值分析的木结构抗震性能分析及其在建筑中的应用

为了提高木结构抗震性能分析的精度,采用多尺度建模分析方法对木结构进行抗震分析。利用多点约束方法分别将榫卯节点和梁柱构件设定为关键区域和非关键区域。采用多尺度的建模思想,对关键区域采用实体单元进行精细尺度建模,而非关键区域则采用梁单元进行普通尺度建模,再通过不同尺度实现宏观结构模型和局部微观模型的相互协调,比较不同尺度下的实体单元和梁单元建模在抗震中的性能。实验结果表明,多尺度的有限元数值分析能够模拟木结构的整体动力响应和精确分析边界条件。通过多尺度、大范围的分级建模能够构建局部和全局的抗震性能分析的过程,精度较高,可提升抗震分析的效率。     

Efficient flow and transport simulations in reconstructed 3D pore geometries

Upscaling pore-scale processes into macroscopic quantities such as hydrodynamic dispersion is still not a straightforward matter for porous media with complex pore space geometries. Recently it has become possible to obtain very realistic 3D geometries for the pore system of real rocks using either numerical reconstruction or micro-CT measurements. In this work, we present a finite element–finite volume simulation method for modeling single-phase fluid flow and solute transport in experimentally obtained 3D pore geometries. Algebraic multigrid techniques and parallelization allow us to solve the Stokes and advection–diffusion equations on large meshes with several millions of elements. We apply this method in a proof-of-concept study of a digitized Fontainebleau sandstone sample. We use the calculated velocity to simulate pore-scale solute transport and diffusion. From this, we are able to calculate the a priori emergent macroscopic hydrodynamic dispersion coefficient of the porous medium for a given molecular diffusion D_m of the solute species. By performing this calculation at a range of flow rates, we can correctly predict all of the observed flow regimes from diffusion dominated to convection dominated.     

基于二维图像的数字岩心电导率计算方法研究

电导率是表征岩石电学性质的重要物理参数,在地质资源勘查和测井解释等领域发挥着巨大作用.快速、准确地确定岩石电导率具有重要的理论和实践意义.作为近年来发展的一种岩石物理数值模拟工具,数字岩心技术在定量计算电导率等物性参数方面应用广泛.三维微观结构的准确获取是数字岩心技术计算岩石电导率的关键,但传统获取岩石三维微观结构的方法较为复杂费时.为了方便快速地通过数字岩心技术计算岩石的电导率,本文研究了岩石二维与三维数字岩心的电导率联系.我们基于微米级X射线CT扫描得到的三个砂岩样品的微观结构信息建立了三维数字岩心,并通过有限元法计算的三维数字岩心电导率与实验数据的对比验证数值计算方法的有效性.随后我们数字地扩展了岩石的孔隙,产生了较大孔隙度的三维数字岩心样本,在此基础上,计算了三维数字岩心和相应二维数字岩心的电导率,并通过Archie公式分别拟合了电导率与孔隙度之间的关系,得到了相应的胶结系数.结果表明,三维数字岩心的胶结系数小于二维数字岩心的胶结系数,且二者的比值与岩石实测孔隙度呈线性负相关关系.以该联系为纽带,通过二维图像快速计算得到的电导率与孔隙度关系,确定了三维数字岩心的电导率与孔隙度关系,并进一步通过三维数字岩心的孔隙度计算其电导率.该方法计算得到的人工砂岩样品的电导率与其三维数字岩心电导率相关系数高于96%,验证了基于二维图像的数字岩心电导率计算方法的有效性.本文的研究结果为快速、准确地计算岩石电导率提供了新的思路,在油气勘探开发中有广阔的应用前景.     

Multiscale study for stochastic characterization of shale samples

Characterization of shale reservoirs, which are typically of low permeability, is very difficult because of the presence of multiscale structures. While three-dimensional (3D) imaging can be an ultimate solution for revealing important complexities of such reservoirs, acquiring such images is costly and time consuming. On the other hand, high-quality 2D images, which are widely available, also reveal useful information about shales’ pore connectivity and size. Most of the current modeling methods that are based on 2D images use limited and insufficient extracted information. One remedy to the shortcoming is direct use of qualitative images, a concept that we introduce in this paper. We demonstrate that higher-order statistics (as opposed to the traditional two-point statistics, such as variograms) are necessary for developing an accurate model of shales, and describe an efficient method for using 2D images that is capable of utilizing qualitative and physical information within an image and generating stochastic realizations of shales. We then further refine the model by describing and utilizing several techniques, including an iterative framework, for removing some possible artifacts and better pattern reproduction. Next, we introduce a new histogram-matching algorithm that accounts for concealed nanostructures in shale samples. We also present two new multiresolution and multiscale approaches for dealing with distinct pore structures that are common in shale reservoirs. In the multiresolution method, the original high-quality image is upscaled in a pyramid-like manner in order to achieve more accurate global and long-range structures. The multiscale approach integrates two images, each containing diverse pore networks – the nano- and microscale pores – using a high-resolution image representing small-scale pores and, at the same time, reconstructing large pores using a low-quality image. Eventually, the results are integrated to generate a 3D model. The methods are tested on two shale samples for which full 3D samples are available. The quantitative accuracy of the models is demonstrated by computing their morphological and flow properties and comparing them with those of the actual 3D images. The success of the method hinges upon the use of very different low- and high-resolution images.     

基于微结构-尺度双分解的页岩随机介质模拟和非均质特征分析

页岩储层矿物颗粒、孔/裂隙、干酪根等微观结构呈现明显的尺度化分布特征,常规的单结构单尺度随机介质模拟方法难以完整描述和重构微观尺度的页岩储层介质,本文提出了一种微结构-尺度双分解的随机介质模拟方法.基于龙马溪组页岩数字岩心,将岩心切片按照占比分解为脆性矿物、孔隙、干酪根及背景介质四种类型,对脆性矿物、孔隙和干酪根三种微结构进行尺度分解,通过优化随机介质模型参数,实现精确模拟不同尺度的微结构组分,再按占比进行微结构-尺度双合成.结果表明,微结构-尺度双分解随机介质模拟大幅度提高强非均质页岩储层介质的建模精度.