Digital rock physics benchmarks-Part I: Imaging and segmentation
Digital rock physics benchmarks-Part I: Imaging and segmentation
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DOI：
10.1016/j.cageo.2012.09.005
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发表时间：
2013-01-01
影响因子：
4.4
通讯作者：
Zhan, Xin
中科院分区：
文献类型：
--
作者：
Andrae, Heiko;Combaret, Nicolas;Zhan, Xin
数字岩石物理(DRP)“图像和计算”的核心范式是指对天然岩石的孔隙空间和矿物基质进行成像和数字化，然后对这个数字对象中的各种物理过程进行数值模拟，以获得岩石的渗透率、电导率和弹性模量等宏观性质。该过程包括图像采集、图像处理(去噪、平滑、分割)；建立数值实验(物体大小、分辨率以及边界条件)；以及数值解场方程。最后，我们需要根据所需的宏观性质来解释这样得到的解。对于这些DRP步骤中的每一个，都有不止一个方法和实现。我们的目标是探索和记录计算的有效属性作为使用不同工具和工作流程的函数的可变性。这样的基准是目前两篇配套论文的主题。在这里，在第一部分中，我们介绍了四种三维微结构，一个分段的枫丹白露砂岩样品(孔隙度0.147)，一个灰阶贝里亚样品，一个灰阶格罗斯蒙特碳酸盐样品，以及一个数值构造的固体球体包(孔隙度0.343)。三个独立团队对灰度图像的分割揭示了这一过程的不确定性：贝里亚的分割孔隙度范围在0.184到0.209之间，碳酸盐岩分割的孔隙度范围在0.195到0.271之间。第二篇论文探讨了与图像分割相关的不确定性的含义。(C)2012爱思唯尔有限公司。保留所有权利。
The key paradigm of digital rock physics (DRP) "image and compute" implies imaging and digitizing the pore space and mineral matrix of natural rock and then numerically simulating various physical processes in this digital object to obtain such macroscopic rock properties as permeability, electrical conductivity, and elastic moduli. The steps of this process include image acquisition, image processing (noise reduction, smoothing, and segmentation); setting up the numerical experiment (object size and resolution as well as the boundary conditions); and numerically solving the field equations. Finally, we need to interpret the solution thus obtained in terms of the desired macroscopic properties. For each of these DRP steps, there is more than one method and implementation. Our goal is to explore and record the variability of the computed effective properties as a function of using different tools and workflows. Such benchmarking is the topic of the two present companion papers. Here, in the first part, we introduce four 3D microstructures, a segmented Fontainebleau sandstone sample (porosity 0.147), a gray-scale Berea sample; a gray-scale Grosmont carbonate sample; and a numerically constructed pack of solid spheres (porosity 0.343). Segmentation of the gray-scale images by three independent teams reveals the uncertainty of this process: the segmented porosity range is between 0.184 and 0.209 for Berea and between 0.195 and 0.271 for the carbonate. The implications of the uncertainty associated with image segmentation are explored in a second paper. (C) 2012 Elsevier Ltd. All rights reserved.