Digital Pore Space Study of a Middle-Eastern Carbonate Rock Sample

G. Tallec
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Abstract

While Image processing is still an area of research, standard workflows have emerged and are routinely used in Oil&Gas companies. However, while hardware capabilities have increased consequently, allowing large samples to be scanned with a high fidelity, permeability simulations are still limited to small samples unless having access to HPC. Direct simulations are known to be more flexible in terms of type of rocks, but limited in terms of sample size, while Pore Network Model based allow much larger sample sizes but less rock types. In this study, we will focus on the pore space analysis of a middle-eastern carbonate sample. The rock sample is 7.5 cm tall and has a diameter of 3.8 cm. It has been acquired at 3 different resolution: a microCT scan at 16μm, a microCT scan of a 10 mm of diameter subsample at 5 μm, and a 10 mm of diameter SEM section at 2μm. This study will propose a methodology to mix the different scales in order to get an accurate pore space analysis of the largest possible sample size. As micro porous regions are visible at every scale, bringing uncertainty to the segmentation step, the first part of our analysis will consist of determining the most accurate pore space at the three different resolutions. We will rely on image registration (2D to 3D and 3D to 3D) and image based upscaling methods, further validated by simulation results. Given the large numerical size of the samples, specific workflows involving large data 3D visualization and processing will be presented. Then, different measures will be conducted: porosity and connected porosity, absolute permeability with three different methods (Lattice Boltzmann, Finite Volume, Pore Network Modeling), relative permeability curves using a Pore Network Model simulator. A new pore network model generation applicable to highly concave pore spaces such as carbonates ones will also be introduced. A scalable method using automation will be presented, so that repeating the simulations on different samples of different space origins and size is easy. We will expose the results and limits of every method and will determine which size is bringing a convergence of the results. We will especially look at the convergence of direct based simulations and pore network model based ones, such that expanding the size prior to Pore Network Model generation can be reliable. In addition to the benchmark of the different simulation methods and their associated limits, the results will help us determining the representative elementary volume at different resolutions and the associated uncertainty depending on whether sub-resolution acquisitions are available or not.
中东碳酸盐岩样品数字孔隙空间研究
虽然图像处理仍然是一个研究领域,但标准工作流程已经出现,并在油气公司中常规使用。然而,尽管硬件性能随之提高,允许以高保真度扫描大样本,但渗透率模拟仍然局限于小样本,除非能够访问HPC。众所周知,直接模拟在岩石类型方面更为灵活,但在样本量方面受到限制,而基于孔隙网络模型的模拟允许更大的样本量,但岩石类型更少。在这项研究中,我们将重点研究中东碳酸盐岩样品的孔隙空间分析。岩石样本高7.5厘米,直径3.8厘米。在3种不同的分辨率下获得:16μm的微ct扫描,5 μm直径10 mm的微ct扫描和2μm直径10 mm的SEM切片。本研究将提出一种混合不同尺度的方法,以便在尽可能大的样本量下获得准确的孔隙空间分析。由于在每个尺度上都可以看到微孔区域,这给分割步骤带来了不确定性,因此我们分析的第一部分将包括在三种不同分辨率下确定最准确的孔隙空间。我们将依靠图像配准(2D到3D和3D到3D)和基于图像的升级方法,通过仿真结果进一步验证。鉴于样本的大数值尺寸,将介绍涉及大数据3D可视化和处理的具体工作流程。然后,将进行不同的测量:孔隙度和连通孔隙度,绝对渗透率采用三种不同的方法(晶格玻尔兹曼,有限体积,孔隙网络建模),相对渗透率曲线使用孔隙网络模型模拟器。本文还将介绍一种适用于碳酸盐等高凹孔隙空间的新型孔隙网络模型生成方法。本文将介绍一种可扩展的自动化方法,以便在不同空间起源和大小的不同样本上重复模拟。我们将揭示每种方法的结果和局限性,并确定哪种大小会带来结果的收敛。我们将特别关注基于直接模拟和基于孔隙网络模型的模拟的收敛性,这样在孔隙网络模型生成之前扩大规模是可靠的。除了对不同模拟方法及其相关限制进行基准测试外,结果将帮助我们确定不同分辨率下的代表性基本体积以及相关的不确定性,这取决于是否可获得亚分辨率采集。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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