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Generation of CT images from medical CT scans of carbonate rocks using a diffusion-based model

Carbonate rocks are known for their high heterogeneity and textural and compositional complexity. Evaluating their petrophysical properties is thus challenging, especially with limited information. One way to obtain an internal image of such rocks is to scan them with X-ray computed tomography scanners, revealing their internal structures. The problem with this approach is the trade-off between cheap bigger volumes scanned with medical CT, but with lower spatial resolution, and higher spatial resolution with
CT, but higher financial and time costs involved, as well as smaller samples (normally centimeter scales). This work proposes a way to have the volume and cost advantages of the medical CT with the spatial resolution of the
CT using a diffusion probabilistic model to convert medical CT into a
CT. The model was trained with a sample of the Brazilian pre-salt composed by Shrub boundstones and tested with one sample of the same facies and another composed of packstone–grainstones. The results show that the model could replicate both samples well, but worked better when the input sample has the same facies as the training set.

Availability
148551.136Perpustakaan BIG (Eksternal Harddisk)Available
Detail Information
Series Title
Applied Computing and Geoscience - Open Access
Call Number
551.136
Publisher
Amsterdam : Elsevier.,
Collation
11 hlm PDF, 4.920 KB
Language
Inggris
ISBN/ISSN
2590-1974
Classification
551.136
Content Type
text
Media Type
-
Carrier Type
-
Edition
Vol.18 June 2023
Subject(s)
Petrography
Carbonate rocks
Digital image processing
Generative models
Diffusion probabilistic models
Specific Detail Info
-
Statement of Responsibility
Other version/related

No other version available

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  • Generation of CT images from medical CT scans of carbonate rocks using a diffusion-based model
    Carbonate rocks are known for their high heterogeneity and textural and compositional complexity. Evaluating their petrophysical properties is thus challenging, especially with limited information. One way to obtain an internal image of such rocks is to scan them with X-ray computed tomography scanners, revealing their internal structures. The problem with this approach is the trade-off between cheap bigger volumes scanned with medical CT, but with lower spatial resolution, and higher spatial resolution with CT, but higher financial and time costs involved, as well as smaller samples (normally centimeter scales). This work proposes a way to have the volume and cost advantages of the medical CT with the spatial resolution of the CT using a diffusion probabilistic model to convert medical CT into a CT. The model was trained with a sample of the Brazilian pre-salt composed by Shrub boundstones and tested with one sample of the same facies and another composed of packstone–grainstones. The results show that the model could replicate both samples well, but worked better when the input sample has the same facies as the training set.
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