Description of chalk microporosity via automated mathematical morphology on scanning electron microphotographs

Aurelien G. Meyer, Meysam Nourani, Lars Stemmerik

Research output: Contribution to journalArticleResearchpeer-review

1 Citation (Scopus)

Abstract

The spatial geometry of microporosity influences fluid flow through chalk reservoirs and aquifers, and, hence, numerous geological processes. Analysing porosity is thus often critical in geological studies. Techniques such as mercury injection capillary pressure (MICP), nuclear magnetic resonance (NMR) and X-ray computed tomography (CT) are expensive, and hence often inapplicable to many geological studies, which often necessitate the analysis of large numbers (hundreds) of samples. However, scanning electron microscopes (SEM) have become widely available, and SEM imagery analysis, therefore, is cheaper and faster. However, extracting meaningful porosity descriptors from SEM images can be difficult, in part because of the difficulty in digitally separating pores in laterally continuous pore networks. Moreover, mathematical morphology can be automated to collect porosity parameters from hundreds of images in a short time frame. The technique also quantifies the shape complexity of porosity. Considering the influence of pore geometry on fluid flow, the capacity of image analysis to deconstruct the pore network by pore shapes is crucial when building flow models. This study concludes that mathematical morphology constitutes an alternative to other techniques in geological studies of microporosity. Lithologies dominated by micro- and nanoporosity, such as shales and tight sandstones, could also benefit from this technique.

Original languageEnglish
Pages (from-to)386-399
Number of pages14
JournalPetroleum Geoscience
Volume26
Issue number3
DOIs
Publication statusPublished - Aug 2020

Programme Area

  • Programme Area 3: Energy Resources

Fingerprint

Dive into the research topics of 'Description of chalk microporosity via automated mathematical morphology on scanning electron microphotographs'. Together they form a unique fingerprint.

Cite this