Drill Cuttings Imaging Chamber With Controlled Lighting Calibration
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Solution Overview
Problem
The challenge in subterranean drilling operations is the inconsistent and low-quality imaging of drill cuttings, which hampers the effectiveness of automated machine learning algorithms in accurately segmenting and labeling rock types, particularly due to varying lighting conditions and overlapping particles.
Innovation Solution
An automated image acquisition device with a housing, tray, lights, and a digital camera, controlled by an electronic controller, which captures high-resolution images under controlled lighting conditions and performs automated calibration, including ultraviolet and white light imaging, and utilizes machine learning algorithms for segmentation and lithology labeling.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If automated image acquisition is implemented without controlled lighting, then device complexity is reduced, but image quality and consistency deteriorate due to varying lighting conditions
Solution Approach 1:
The patent applies parameter changes by controlling lighting conditions through multiple light sources with specific intensities and spectral characteristics. The system uses adjustable lighting parameters to ensure consistent illumination across different drilling environments, directly addressing the image quality consistency issue while maintaining automated operation.
Solution Approach 2:
The patent introduces lighting control systems as intermediaries between the environment and image capture. These controlled light sources act as mediators to eliminate the direct influence of varying ambient lighting conditions, ensuring consistent image quality without requiring complex manual intervention.
2Manufacturing precision
If multiple light sources are used for illumination, then image quality improves, but device complexity and energy consumption increase
Solution Approach 1:
The patent implements multi-functionality by designing light sources that serve multiple purposes: primary illumination, shadow reduction, and color consistency maintenance. The lighting system is integrated into the housing structure, allowing the same components to fulfill both structural and illumination functions, thereby improving image quality without proportionally increasing device complexity.
3Measurement precision
If automated calibration is implemented, then measurement precision improves, but device complexity and processing time increase
Solution Approach 1:
The patent applies self-service through automated calibration routines that perform self-diagnosis and self-adjustment. The system includes self-calibrating light sources and automated focus adjustment mechanisms that maintain optimal imaging conditions without requiring external intervention or complex manual calibration procedures, thereby improving measurement precision while keeping the calibration system manageable.
Solution Approach 2:
The patent implements preliminary action by performing calibration operations automatically during system initialization and at scheduled intervals before actual imaging. This proactive calibration approach ensures measurement precision is maintained without requiring complex real-time adjustment mechanisms during active drilling operations.
4Measurement precision
If high-resolution imaging is used, then segmentation accuracy improves, but data processing time and computational requirements increase
Solution Approach 1:
The patent applies preliminary action by performing image preprocessing operations such as noise reduction, contrast enhancement, and feature extraction immediately after image capture but before main analysis. This preliminary processing of high-resolution images reduces the computational burden on subsequent segmentation algorithms, maintaining accuracy while reducing overall processing time.
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
Improves image quality and consistency, enabling effective automated analysis of drill cuttings, enhancing the accuracy of machine learning algorithms in identifying and labeling rock types.
Implementation Method 1
At least one light is also deployed in the image acquisition chamber and is disposed to illuminate the tray
Implementation Method 2
A digital camera is deployed in the image acquisition chamber and is configured to acquire a digital image of the cuttings sample
Data Source
AI summary
An automated image acquisition device includes a housing including an image acquisition chamber. A tray is deployed in the image acquisition chamber and is configured to receive a drill cuttings sample. At least one light is also deployed in the image acquisition chamber and is disposed to illuminate the tray. A digital camera is deployed in the image acquisition chamber and is configured to acquire a digital image (e.g., a digital color image) of the cuttings sample. The device further includes an electronic controller configured to instruct the digital camera to record a digital image of the drill cuttings and save the image to digital memory or transfer the image to an external computing device.