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Published July 2016 | Published
Journal Article Open

Conditional reconstruction: An alternative strategy in digital rock physics

Abstract

Digital rock physics (DRP) is a newly developed method based on imaging and digitizing of 3D pore and mineral structure of actual rock and numerically computing rock physical properties, such as permeability, elastic moduli, and formation factor. Modern high-resolution microcomputed tomography scanners are used for imaging, but these devices are not widely available, and 3D imaging is also costly and it is a time-consuming procedure. However, recent improvements of 3D reconstruction algorithms such as crosscorrelation-based simulation and, on the other side, the concept of rock physical trends have provided some new avenues in DRP. We have developed a modified work flow using higher order statistical methods. First, a high-resolution 2D image is divided into smaller subimages. Then, different stochastic subsamples are generated based on the provided 2D subimages. Eventually, various rock physical parameters are calculated. Using several subsamples allows extracting rock physical trends and better capturing the heterogeneity and variability. We implemented our work flow on two DRP benchmark data (Berea sandstone and Grosmont carbonate) and a thin-section image from the Grosmont carbonate formation. Results of realization models, pore network modeling, and autocorrelation functions for the real and reconstructed subsamples reveal the validity of the reconstructed models. Furthermore, the agreement between static and dynamic methods indicates that subsamples are representative volume elements. Average values of the subsamples' properties follow the reference trends of the rock sample. Permeability trends pass the actual results of the benchmark samples; however, elastic moduli trends find higher values. The latter can be due to image resolution and voxel size, which are generated by imaging tools and reconstruction algorithms. According to the obtained results, this strategy can be introduced as a valid and accurate method where an alternative method for standard DRP is needed.

Additional Information

© 2016 Society of Exploration Geophysicists. Manuscript received by the Editor 4 May 2015; revised manuscript received 27 December 2015; published online 29 June 2016. We would like to thank M. Blunt (Imperial College) and his group for permission to use their pore network modeling codes. We also thank E. Saenger (ETH, Zurich) for his time and patience for simulating our subsamples using the dynamic method. We also wish to thank the associate editor and five anonymous reviewers of this manuscript for their constructive and valuable comments that improved the initial manuscript.

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August 20, 2023
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