Method and system for characterizing perforations in a tubular
AssigneeDarkVision Technologies Inc.
InventorsGaurav Handa, Sindhu Hari, Mengliu Zhao
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Abstract
Methods and system of characterizing perforations in a tubular. An imaging tool having an acoustic imaging probe transmits waves and receives acoustic reflections from the tubular. Image segments are processed from the acoustic data. A first trained neural network operates on the image segments to identify processed image segments containing a perforation. A second trained neural network operates on processed image segments containing a perforation to output the location of perforations along the tubular. Another trained neural network can calculate a geometric size of the perforations, such as their size or points along their contour.
Claims23
A method of characterizing perforations in a tubular, comprising:
- generating processed image segments, based on a received acoustic data for acoustic reflections from the tubular;
- convolving a first trained neural network with the processed image segments to identify processed image segments containing a perforation;
- and
- convolving a second trained neural network on those processed image segments containing a perforation to output bounding boxes that locate the perforations along the tubular.
A method of characterizing a perforation in a tubular, comprising:
- generating, based on a received acoustic data, an image segment containing a perforation and a corresponding bounding box around the perforation;
- identifying key points of the perforation in the image segment using a trained neural network model;
- and
- determining, based on the key points, geometric characteristics of the perforation.
A system for characterizing a perforation in a tubular, comprising:
- an acoustic probe comprising a plurality of ultrasonic sensors, each sensor capable of transmitting and receiving ultrasonic waves, wherein the acoustic probe is configured to generate acoustic data;
- at least one processor;
- and
- at least one memory storing a first and a second trained neural network;
- the at least one memory communicatively coupled with the at least one processor and storing machine-readable instructions that, when executed by the processor, cause the processor to:
- generate processed image segments, based on the acoustic data;
- convolve the first trained neural network with the processed image segments to identify processed image segments containing a perforation;
- and
- convolve the second trained neural network on those processed image segments containing a perforation to output a bounding box that locates the perforation along the tubular.
A system for characterizing a perforation in a tubular, comprising:
- an acoustic probe comprising a plurality of ultrasonic sensors, each sensor capable of transmitting and receiving ultrasonic waves, wherein the acoustic probe is configured to generate acoustic data;
- at least one processor;
- and
- at least one memory storing a trained neural network;
- the at least one memory communicatively coupled with the at least one processor and storing machine-readable instructions that, when executed by the processor, cause the processor to:
- generate, based on a received acoustic data, an image segment containing a perforation;
- identify key points of the perforation in the image segment using a trained neural network model;
- and
- determine, based on the key points, geometric characteristics of the perforation.
Dependencies are inferred from the claim text.