Resumo

FELIPE LOZANO, Andrei; JULIAO-LEMUS, Tatiana; PEREZ, Edgar Ricardo  e  OBANDO-YAGUAS, Ayerim Antonieta. Review of Microscopic Techniques for Digital Rock Models. Bol. geol. [online]. 2022, vol.44, n.1, pp.161-171.  Epub 25-Jan-2022. ISSN 0120-0283.  https://doi.org/10.18273/revbol.v44n1-2022008.

Unconventional deposits (source rock reservoirs) represent a new stage in the exploration and exploitation of oil and gas worldwide, and their petrophysical characterization continues to be a challenge due to low permeabilities, high levels of heterogeneity, and the difficulty of adapting conventional techniques. Digital petrophysics emerges as an alternative that takes advantage of the latest advances in electron microscopy, computed tomography, and computational processing to estimate petrophysical properties using numerical methods and voxel counting algorithms in what is called a digital rock model. This work carries out a review of digital characterization techniques and their application to unconventional reservoir samples belonging to the Vaca Muerta Formation (Argentina) and La Luna Formation (Colombia). With this technology, it is possible to visualize the porous space on a micro and nanometric scale to obtain qualitative information (types of pores and microfractures) and quantitative information (porosity, absolute permeability, pore size distribution, organic matter content, and advanced petrophysical properties). The results obtained indicate that the FIB-SEM samples are below the representative elementary volume and that digital samples with larger dimensions, although more representative, require greater computational capacity. The upscaling of petrophysical properties, the lack of connectivity of the porous medium, and the poor representativeness are the most important limitations of using this technology. However, its potential increases as artificial intelligence, simulation, and machine learning techniques gain strength in the oil and gas industry.

Palavras-chave : Source rock reservoirs; Shale; Digital petrophysics; Digital rock physics.

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