Nanoscale and multiresolution models for shale samples

Nanoscale and multiresolution models for shale samples Characterization of shale systems requires imaging at different scales. One reason can be due to a diverse pore-size distribution. Low-resolution images often cover the large-scale structures and are available for a large region of the sample. On the other hand, fine-scale images usually cover a small region and they are mostly used to discover the complexity within the nano-scale pores in shale samples. Acquiring large image containing both the micro- and the nano-scale feature can be very expensive and time demanding. In this paper, a new method for integrating of such images at different scales is proposed. The aim is to include the nano-scale information within the coarse images. The input of this method is a set of coarse- and fine-scale images. The corresponding regions of each fine-scale image within the coarser image are determined using a similarity map. Then, the coarse image is refined iteratively to include the fine-scale information. The final image contains both the micro and nano-meter images and can readily be used for various purposes. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Fuel Elsevier

Nanoscale and multiresolution models for shale samples

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Publisher
Elsevier
Copyright
Copyright © 2017 Elsevier Ltd
ISSN
0016-2361
D.O.I.
10.1016/j.fuel.2017.12.107
Publisher site
See Article on Publisher Site

Abstract

Characterization of shale systems requires imaging at different scales. One reason can be due to a diverse pore-size distribution. Low-resolution images often cover the large-scale structures and are available for a large region of the sample. On the other hand, fine-scale images usually cover a small region and they are mostly used to discover the complexity within the nano-scale pores in shale samples. Acquiring large image containing both the micro- and the nano-scale feature can be very expensive and time demanding. In this paper, a new method for integrating of such images at different scales is proposed. The aim is to include the nano-scale information within the coarse images. The input of this method is a set of coarse- and fine-scale images. The corresponding regions of each fine-scale image within the coarser image are determined using a similarity map. Then, the coarse image is refined iteratively to include the fine-scale information. The final image contains both the micro and nano-meter images and can readily be used for various purposes.

Journal

FuelElsevier

Published: Apr 1, 2018

References

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