High-contrast ultraviolet fluorescence imaging systems and methods for pixel-level detection of crude oil in drill cuttings

Patent metadata

Field	Value
Publication number	US-2025278825-A1
Application number	US-202519212144-A
Country	US
Kind code	A1
Filing date	May 19, 2025
Priority date	May 27, 2022
Publication date	Sep 4, 2025
Grant date	—

Abstract

Systems and methods are provided for imaging drill cuttings, which employ a UV source including a UV LED, which is configured to illuminate a sample volume with UV radiation that interacts with oil-bearing cuttings to cause fluorescence emission. A camera system is configured to capture at least one image of the cuttings based on fluorescence emission. In another aspect, methods are provided for characterizing oil content in drill cuttings that involve capturing at least one WL image of the cuttings illuminated by white light, capturing at least one UV image of the cuttings based on fluorescence emission from UV radiation, processing the at least one WL image to determine a first pixel count for all cuttings, processing the at least one UV image to determine a second pixel count for oil-bearing cuttings, and determining a parameter representing oil content of the cuttings based on the first and second pixel counts.

First claim

What is claimed is:

1 . An imaging system for use with drill cuttings, the imaging system comprising:
an ultraviolet (UV) source including a UV light-emitting diode, wherein the UV source is configured to illuminate a sample volume with UV radiation that interacts with crude oil bound to drill cuttings located in the sample volume to cause fluorescence emission of photons in the visible region of the electromagnetic spectrum; and a white light source configured to illuminate the sample volume with white light; a camera system including an image sensor, wherein the camera system is configured to capture at least one image of drill cuttings located in the sample volume based on fluorescence emission from the drill cuttings; and a data processing system to quantitively characterize oil content of the drill cuttings.

2 . The imaging system of claim 1 , wherein:
the UV source is configured to illuminate the sample volume with at least one predefined UV wavelength band, wherein the at least one predefined UV wavelength band interacts with crude oil bound to drill cuttings located in the sample volume to cause fluorescence emission of photons in the visible region of the electromagnetic spectrum.

3 . The imaging system of claim 1 , wherein:
the UV light-emitting diode is configured to emit UV radiation in a UV wavelength band centered around 365 nm with peak intensity at the wavelength of 365 nm.

4 . The imaging system of claim 1 , wherein:
the UV source further includes an optical bandpass filter configured to transmit UV radiation within at least one predefined UV wavelength band and block other UV wavelength bands, wherein the at least one predefined UV wavelength band interacts with crude oil bound to drill cuttings located in the sample volume to cause fluorescence emission of photons in the visible region of the electromagnetic spectrum.

5 . The imaging system of claim 4 , wherein:
the optical bandpass filter is configured to transmit UV radiation in a wavelength band centered around 365 nm and substantially block transmission of UV radiation for wavelengths outside the wavelength band for transmission; and/or the wavelength band for transmission of the optical bandpass filter extends over a narrow UV wavelength range of 100 nm or less; and/or the optical bandpass filter is configured to block visible light in the wavelength band between 400 nm and 700 nm.

6 . The imaging system of claim 1 , further comprising:
an optical filter in the optical path between the sample volume and the camera system.

7 . The imaging system of claim 1 , wherein the camera system is further configured to capture at least one image of drill cuttings located within the sample volume and illuminated by white light.

8 . A system for use in a mud-logging workflow, the system comprising:
a camera system configured to capture at least one image of drill cuttings located within a sample volume illuminated by white light; and a data processing system, operably coupled to the imaging system, wherein the data processing system is configured to process the at least one image of drill cuttings located within the sample volume and illuminated by white light as captured by the imaging system and process the at least one image arising from fluorescence emission from drill cuttings located in the sample volume as captured by the imaging system in order to quantitively characterize oil content of the drill cuttings based on a ratio of pixel count from the white light source and pixel count from the UV source.

9 . The system of claim 8 , wherein the data processing system is configured to:
i) process the at least one image of drill cuttings located within the sample volume and illuminated by white light as captured by the imaging system to determine a first pixel count for all drill cuttings; ii) process the at least one image arising from fluorescence emission from drill cuttings located in the sample volume as captured by the imaging system to determine a second pixel count for oil-bearing drill cuttings; and iii) determine a parameter representing oil content of the drill cuttings based on the first pixel count and the second pixel count.

10 . The system of claim 9 , wherein:
the data processing system is configured to determine the parameter representing oil content of the drill cuttings based on the ratio of the second pixel count over the first pixel count.

11 . The system of claim 9 , wherein:
the data processing system employs a first machine learning model to determine the first pixel count for all drill cuttings; and the data processing system employs a second machine learning model to determine the second pixel count for oil-bearing drill cuttings.

12 . The system of claim 11 , wherein:
the first machine learning is trained to determine the first pixel count for all drill cuttings from images of drill cuttings of different textures, colors, and oils of different API and associated label data; and the second machine learning is trained to determine the second pixel count for oil-bearing drill cuttings from images of drill cuttings of different textures, colors, and oils of different API and associated label data.

13 . The system of claim 11 , wherein:
the first machine learning model is trained to determine the first pixel count for all drill cuttings with label data derived from binarization of images of drill cuttings illuminated by white light.

14 . The system of claim 13 , wherein:
the binarization of images employs i) clustering of hue, saturation or value image data obtained by transforming color space of the images, or ii) edge-based segmentation of the images.

15 . The system of claim 11 , wherein:
the second machine learning model is trained to determine the second pixel count for oil-bearing drill cuttings with label data derived from binarization of images illuminated by UV radiation that causes fluorescence emission from oil-bearing drill cuttings.

16 . The system of claim 15 , wherein:
the binarization of images employs i) clustering of hue, saturation or value image data obtained by transforming color space of the images, or ii) edge-based segmentation of the images, or iii) thresholding of the images.

17 . The system of claim 11 , wherein:
the first machine learning comprises a convolutional encoder-decoder neural network trained to determine the first pixel count for all drill cuttings given an image of drill cuttings illuminated by white light; and/or the second machine learning model comprises a convolutional encoder-decoder neural network trained to determine the second pixel count for oil-bearing drill cuttings given an image of drill cuttings illuminated by UV radiation.

18 . A system for use in a mud-logging workflow, the system comprising:
a white light source configured to illuminate the sample volume with white light; an ultraviolet (UV) source including a UV light-emitting diode, wherein the UV source is configured to illuminate a sample volume with UV radiation that interacts with crude oil bound to drill cuttings located in the sample volume to cause fluorescence emission of photons in the visible region of the electromagnetic spectrum; and a camera system including an image sensor, wherein the camera system is configured to capture at least one image of drill cuttings located in the sample volume based on fluorescence emission from the drill cuttings; a data processing system to determine an oil content of the drill cuttings based on a ratio of pixel count from the white light so

Assignees

• Schlumberger Technology Corp

Inventors

• Sharma Richa
• Bondabou Karim
• Francois Matthias

Classifications

• G06T2207/20084

  Artificial neural networks [ANN] · CPC title

• G06T2207/20081

  Training; Learning · CPC title

• G06T2207/10064

  Fluorescence image · CPC title

• G06T2207/10056

  Microscopic image · CPC title

• G06T2207/10024

  Color image · CPC title