Payton Ryan L, Chiarella Domenico, Kingdon Andrew
Department of Earth Sciences, Clastic Sedimentology Investigation (CSI), Royal Holloway, University of London, Egham, Surrey, UK.
British Geological Survey, Keyworth, Nottingham, UK.
Sci Rep. 2022 May 9;12(1):7531. doi: 10.1038/s41598-022-11365-8.
An accurate and reliable description of the porosity-permeability relationship in geological materials is valuable in understanding subsurface fluid movement. This is important for reservoir characterisation, energy exploitation, geological carbon storage (GCS) and groundwater contamination and remediation. Whilst the relationship between pore characteristics and porosity and permeability are well examined, further investigation into the influence of grain characteristics on porosity and permeability would be beneficial due to the inherent relationship between grains and pores. This work aims to determine whether incorporation of grain characteristics into a porosity-permeability model is effective in constraining this relationship. Two fully digital approaches to individual 3D grain analysis based upon watershed segmentation are compared to determine the most effective, yet simple, workflow applicable to core plugs of significantly compacted grains. The identification of an effective segmentation workflow will facilitate future work on similarly complex materials, removing the need for traditional time-consuming and manual techniques. We use the most effective approach of measuring grain shape (sphericity) and size (Feret diameter) alongside an established fully digital workflow to measure porosity and permeability to investigate the impact of grain characteristics on porosity and permeability. We show that grain sphericity and porosity exhibit a positive relationship whereas no such relationship exists with grain size. Measurements of grain sphericity are applied to calculate a Kozeny-Carman (K-C) type porosity-permeability fit which was found to be unsatisfactory, compared to a simpler fit excluding any grain parameters. This is possibly due to the lower sphericity of the studied grains, deviating significantly from the K-C assumption that grains are entirely spherical. The simpler fit is most suitable for the studied materials, showing that inclusion of grain characteristics is not effective for better defining the porosity-permeability relationship in a K-C paradigm for these samples. This highlights the need for a model capable of considering a range of grain sphericities to further constrain the porosity-permeability relationship.
准确可靠地描述地质材料中的孔隙度与渗透率关系，对于理解地下流体运动具有重要价值。这对于储层表征、能源开采、地质碳储存（GCS）以及地下水污染与修复都至关重要。虽然孔隙特征与孔隙度和渗透率之间的关系已得到充分研究，但由于颗粒与孔隙之间存在内在联系，进一步研究颗粒特征对孔隙度和渗透率的影响将大有裨益。这项工作旨在确定将颗粒特征纳入孔隙度 - 渗透率模型是否能有效地约束这种关系。比较了两种基于分水岭分割的全数字三维颗粒分析方法，以确定最有效且简单的工作流程，该流程适用于颗粒显著压实的岩芯塞。确定有效的分割工作流程将有助于未来对类似复杂材料的研究，无需使用传统的耗时且手动的技术。我们使用测量颗粒形状（球形度）和尺寸（费雷特直径）的最有效方法，结合已建立的全数字工作流程来测量孔隙度和渗透率，以研究颗粒特征对孔隙度和渗透率的影响。我们发现颗粒球形度与孔隙度呈正相关，而与颗粒尺寸不存在这种关系。应用颗粒球形度测量值来计算科曾尼 - 卡曼（K - C）型孔隙度 - 渗透率拟合，结果发现与不包含任何颗粒参数的更简单拟合相比，该拟合并不理想。这可能是由于所研究颗粒的球形度较低，与K - C假设中颗粒完全球形有显著偏差。对于所研究的材料，更简单的拟合最为合适，这表明在K - C范式中，纳入颗粒特征对于更好地定义这些样品的孔隙度 - 渗透率关系并不有效。这突出了需要一个能够考虑一系列颗粒球形度的模型，以进一步约束孔隙度 - 渗透率关系。
