UV Fluorescence Imaging for Pixel-Level Oil Detection in Drill Cuttings
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current mud-logging technologies face challenges with low robustness and safety risks in UV fluorescence imaging for crude oil detection, leading to weak contrast images unsuitable for automated workflows and health hazards from mercury-based bulbs.
Innovation Solution
An imaging system using a UV light-emitting diode and optical bandpass filter to illuminate drill cuttings, capturing visible fluorescence emissions with a camera system, combined with white light imaging and machine learning models for pixel-level oil detection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Illumination intensity
If mercury-based UV bulbs are used for fluorescence imaging, then UV radiation can be generated to excite crude oil fluorescence, but health and safety risks are increased and the apparatus becomes bulky
Solution Approach 1:
The patent replaces the traditional mercury-based UV bulb system with a UV LED (light-emitting diode) system. This substitution eliminates the harmful mercury content while maintaining UV radiation generation capability. The UV LED module includes a printed circuit board with LED elements that emit UV light to excite fluorescence in crude oil samples, thereby reducing health and safety risks associated with mercury handling and exposure.
Solution Approach 2:
The patent changes the physical state and composition parameters of the UV light source by transitioning from gas-discharge-based mercury bulbs to solid-state LED technology. This parameter change involves modifying the emission mechanism, reducing power consumption, and eliminating toxic materials while maintaining the essential UV radiation output for fluorescence excitation.
2Measurement precision
If high-power UV radiation is used to improve fluorescence signal strength, then detection sensitivity increases, but the apparatus becomes more bulky and robustness decreases
Solution Approach 1:
The patent replaces high-power UV bulb systems with UV LED modules that provide sufficient UV radiation for fluorescence detection without requiring bulky high-power infrastructure. The LED-based system achieves the necessary detection sensitivity through efficient UV emission and optimized optical path design, while maintaining a compact, robust form factor suitable for automated mud-logging workflows.
3Difficulty of detecting and measuring
If legacy Fluoroscope system is used for UV fluorescence imaging, then crude oil detection can be performed, but image contrast is weak and automation capability is limited
Solution Approach 1:
The patent replaces the optical eyepiece viewing system of the legacy Fluoroscope with a digital camera-based imaging system. The camera captures UV-excited fluorescence images with high contrast, enabling automated image processing and machine learning algorithms to detect and characterize crude oil in drill cuttings. This digital imaging approach facilitates full automation of the mud-logging workflow.
Solution Approach 2:
The patent enhances image contrast by utilizing the characteristic fluorescence emission spectrum of crude oil when excited by UV radiation. The optical filter system isolates the fluorescence wavelength range, creating high-contrast images where oil-bearing cuttings stand out distinctly from non-oil-bearing materials. This spectral separation enables reliable automated detection and characterization.
4Productivity
If UV fluorescence imaging is used for crude oil detection, then detection speed can be improved, but image quality and contrast remain insufficient for reliable machine learning
Solution Approach 1:
The patent optimizes the UV excitation parameters by using UV LEDs with specific wavelength emissions (e.g., 365 nm) that match the absorption spectrum of crude oil components. This parameter optimization maximizes fluorescence yield and image contrast while maintaining rapid acquisition speeds. The optimized optical parameters enable both high-speed detection and high-quality images suitable for machine learning analysis.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables high-contrast, automated, and safe detection of crude oil in drill cuttings, facilitating rapid and accurate characterization of oil content for improved wellsite decision-making.
Implementation Method 1
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
Data Source
AI summary
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.