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Energies 2018, 11(7), 1798; https://doi.org/10.3390/en11071798

Critical Resolution and Sample Size of Digital Rock Analysis for Unconventional Reservoirs

1
,
2,* and 1,*
1
Department of Engineering Mechanics and CNMM, Tsinghua University, Beijing 100084, China
2
National Energy Tight Oil & Gas Research Centre, Petroleum Geology Research & Laboratory Center, Research Institute of Petroleum Exploration & Development (RIPED) PetroChina, Beijing 100083, China
*
Authors to whom correspondence should be addressed.
Received: 15 May 2018 / Revised: 11 June 2018 / Accepted: 5 July 2018 / Published: 9 July 2018
(This article belongs to the Section Energy Sources)
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Abstract

Digital rock analysis (DRA) has exhibited strong ability and significant potential to help people to image geological microstructures and understand transport mechanisms in rocks underground, especially for unconventional reservoirs like tight sandstone and shale. More and more new technologies have been developed for higher resolutions, which always come with higher expense. However, the balance between cost (money and time) and benefit has never been figured out quantitatively for these studies. As the cost and benefit are directly related to image resolution and size, this work is focusing on whether there is a critical resolution and sample size when using DRA for accurate enough predictions of rock properties. By numerically changing the digital resolutions of the reconstructed structures from high-resolution micro-computed tomography (CT) scanned tight rock samples, it is found that the permeability predictions get stable when the resolution is higher than a cut-off resolution (COR). Different from physical rocks, the representative element volume (REV) of a digital rock is influenced by the digital resolution. The results of pore-scale modeling indicate that once sample size is larger than the critical sample size and the scan resolution higher than the critical resolution for a given rock, the predicted rock properties by DRA are accurate and representative. View Full-Text
Keywords: digital rock analysis; unconventional reservoirs; scan resolution; representative element volume digital rock analysis; unconventional reservoirs; scan resolution; representative element volume
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Liu, T.; Jin, X.; Wang, M. Critical Resolution and Sample Size of Digital Rock Analysis for Unconventional Reservoirs. Energies 2018, 11, 1798.

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