Computer-implemented systems and methods for intelligent image analysis using spatio-temporal information
US-2024020835-A1 · Jan 18, 2024 · US
US11694338B2 · US · B2
| Field | Value |
|---|---|
| Publication number | US-11694338-B2 |
| Application number | US-202017415621-A |
| Country | US |
| Kind code | B2 |
| Filing date | Jul 23, 2020 |
| Priority date | Jul 3, 2020 |
| Publication date | Jul 4, 2023 |
| Grant date | Jul 4, 2023 |
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The present invention belongs to the technical field of petroleum exploitation engineering, and discloses a 3D modeling method for cementing hydrate sediment based on a CT image. Indoor remolding rock cores or in situ site rock cores without hydrate can be scanned by CT; a sediment matrix image stack and a pore image stack are obtained by gray threshold segmentation; then, a series of cementing hydrate image stacks with different saturations are constructed through image morphological processing of the sediment matrix image stack such as dilation, erosion and image subtraction operation; and a series of digital rock core image stacks of the cementing hydrate sediment with different saturations are formed through image subtraction operation and splicing operation to provide a relatively real 3D model for the numerical simulation work of the basic physical properties of a reservoir of natural gas hydrate.
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The invention claimed is: 1. A 3D modeling method for cementing hydrate sediment based on CT image, comprising steps of: step 1, scanning remolding or in situ rock cores without natural gas hydrate by CT to obtain digital rock core image stacks; step 2, adjusting the gray threshold of the digital rock core image stacks, conducting binarization segmentation to obtain a sediment matrix and a pore, and respectively saving as the image stacks; step 3, firstly dilating a sediment matrix image stack obtained in step 2 at x pixel and then eroding at x pixel; step 4, performing image subtraction; and subtracting the sediment matrix image stack obtained in step 2 from the sediment matrix image stack obtained in step 3 to obtain a cementing hydrate image stack; step 5, performing image subtraction again; and subtracting the cementing hydrate image stack obtained in step 4 from the pore image stack obtained in step 2 to obtain a new pore image stack corresponding to the cementing hydrate image stack obtained in step 4; step 6, splicing and combining the sediment matrix image stack obtained in step 2, the cementing hydrate image stack obtained in step 4 and the new pore image stack obtained in step 5 to form a digital rock core image stack with the sediment matrix, the cementing hydrate and the pore, which is the digital rock core image stack of the cementing hydrate sediment; step 7, repeatedly executing step 3 to step 6, and adjusting x value to obtain the digital rock core image stacks of the cementing hydrate sediment with different hydrate saturations.
Encoded features or binary features, e.g. local binary patterns [LBP] · CPC title
Morphological image processing · CPC title
involving morphological operators · CPC title
Constructive solid geometry [CSG] using solid primitives, e.g. cylinders, cubes · CPC title
Computed x-ray tomography [CT] · CPC title
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