Machine learning model for measuring perforations in a tubular
View Patent ↗A method and instruction memory for processing acoustic images of a downhole casing to determine perforations of the tubular. The images may be acquired by an acoustic logging tool deployed into cased well. A Machine Learning model is trained to recognize regions of the acoustic images that are perforations or not, in order to calculate geometric properties of the perforation and overall casing. Renderings of the imaged casing may be overlaid with contours and properties of perforations to improve perforation, fracturing and producing operations.
1 . A method of identifying perforations in a downhole casing from ultrasound images, the method comprising:
receiving an ultrasound image of the casing;
determining sub-regions of the ultrasound image that each include one perforation;
convolving corresponding pixels of each sub-region with a Perforation Segmentation Model to create a perforation mask that corresponds to the pixels and their probability of being a perforation within that sub-region expressed as a pixel perforation probability value being a range between a first value indicating a background pixel and a second value indicating a perforation pixel;
calculating one or more geometric properties of each perforation from each perforation mask;
storing the one or more geometric properties in a datastore; and
rendering a visualization of the casing to a user from the received ultrasound image overlaid with at least one of: the perforation mask or calculated geometric properties from several perforations.
2 . The method of claim 1 , further comprising thresholding the perforation mask to use pixels in the perforation mask above a threshold probability for calculating the one or more geometric properties.
3 . The method of claim 1 , wherein one of the geometric properties is a contour that encapsulates the perforation, the contour being a 2D contour in coordinates of azimuth and axial position along the casing.
4 . The method of claim 1 , further comprising imaging the casing using a ring-shaped phased-array of ultrasound transducers moved axially through the casing while capturing transverse image frames of the casing.
5 . The method of claim 1 , wherein determining the sub-regions is performed manually via a User Interface displaying a 2D image of a portion of the ultrasound image and receiving locations of perforations or boundaries of sub-regions around perforations.
6 . The method of claim 1 , wherein the geometric properties calculated is a diameter or volume of the perforation.
7 . The method of claim 1 , wherein the ultrasound image comprises three-dimensional data provided in polar coordinates.
8 . The method of claim 1 , wherein the Perforation Segmentation Model is a Semantic model corresponding to at least one of a UNet, UNet++, or Deeplab.
9 . The method of claim 1 , further comprising assembling a geometric model of the casing from the geometric properties of hundreds of perforations.
10 . A system for processing ultrasound images of a downhole casing to identify perforations comprising:
a memory storing a Perforation Segmentation Model;
one or more datastores storing an ultrasound image of the casing; and
a non-transitory computer readable medium having instructions executable by a processor to perform operations comprising:
receiving the ultrasound image of the casing;
determining sub-regions of the ultrasound image that each include one perforation;
convolving corresponding pixels of each sub-region with the Perforation Segmentation Model to create a perforation mask that corresponds to the pixels and their probability of being a perforation within the selected sub-region expressed as a pixel perforation probability value being a range between a first value indicating a background pixel and a second value indicating a perforation pixel;
calculating one or more geometric properties of each perforation from each perforation mask;
storing the one or more geometric properties in the one or more datastores; and
rendering a visualization of the casing to a user from the received ultrasound image overlaid with at least one of: the perforation mask or calculated geometric properties from several perforations.
11 . The system of claim 10 , further comprising a User Interface providing i) a 2D display of a portion of the ultrasound image and ii) input means for tagging locations of perforations or bounding sub-regions around perforations.
12 . The system of claim 10 , the instructions further performing thresholding the perforation mask to apply pixels in the mask above a threshold probability to calculate the one or more geometric properties.
13 . The system of claim 10 , wherein one of the geometric properties is a contour that encapsulates the perforation.
14 . The system of claim 10 , further comprising a ring-shaped phased-array of ultrasound transducers for capturing transverse image frames of the casing.
15 . The system of claim 10 , wherein the geometric properties calculated is a diameter or volume of the perforation.
16 . The system of claim 10 , wherein the ultrasound image comprises three-dimensional data.
17 . The system of claim 10 , wherein the Perforation Segmentation Model is a Semantic model.
18 . The system of claim 10 , the instructions further performing assembling a geometric model of the casing from the stored geometric properties of hundreds of perforations.
19 . The system of claim 10 , wherein the visualization corresponds to the received ultrasound image being overlaid by a plurality of contours that each encapsulate a respective perforation of a plurality of perforations, each contour being a 2D contour in coordinates of azimuth and axial position along the casing.
20 . The method of claim 1 , wherein the visualization corresponds to the received ultrasound image being overlaid by a plurality of contours that each encapsulate a respective perforation of a plurality of perforations, each contour being a 2D contour in coordinates of azimuth and axial position along the casing.