Scale dependence of textural alignment in shales quantified using electron microscopy. (December 2020)

• Record Type: Journal Article
• Authors: Kaduri, Maor; Dor, Maoz; Day-Stirrat, Ruarri J.; Emmanuel, Simon
• Is Part Of: Marine and petroleum geology. Volume 122(2020)
• Publication Date: 2020-12
• Subjects: Clay -- Fabric -- Anisotropy -- Image processing -- Mudrocks -- Phyllosilicates; Submarine geology -- Periodicals; Petroleum -- Geology -- Periodicals; Géologie sous-marine -- Périodiques; Pétrole -- Géologie -- Périodiques; Petroleum -- Geology; Submarine geology; Periodicals; Electronic journals; 551.468
• DOI: 10.1016/j.marpetgeo.2020.104707
• Languages: English
• ISSNs: 0264-8172

Abstract

Abstract: Textural alignment is the primary cause of anisotropy associated with the permeability and mechanical and acoustic properties of rocks. Although particle alignment in shales is known to be influenced by burial depth, mineralogical composition, and diagenetic history, understanding how these influence image-based measures of compaction at the micrometer to nanometer scale is not well understood. Here, we use a novel method, which combines scanning electron microscopy and image analysis algorithms, to quantify clay alignment in sedimentary rocks. For a given field of view, the alignment intensity in shales from the Podhale Basin in Poland is positively correlated with clay content based on image analysis. However, our analysis also shows that the intensity is strongly dependent on the spatial scale of imaging: as magnification increases and the field of view in the SEM images decreases, the alignment intensity drops. Therefore, in images with small fields of view, clay alignment is determined by the presence of localized equant silicate mineral grains, which effectively hinder the alignment process at the micrometer scale. By contrast, in images with larger fields of view, alignment intensity is determined by the overall compaction state. We also show that when the field of view is constant, alignment intensity decreases with pixel density, and we suggest a range of operating parameters required for obtaining optimum values for alignment intensity from SEM images of shales. Highlights: Novel method, combining electron microscopy and image analysis, to quantify clay alignment in sediments. In tested samples, alignment increases with clay content. Alignment intensity decreases with decreasing field of view. To determine alignment in shales, optimal ranges are suggested for imaging fields of view and resolution.