Hyperspectral Imaging Drilling Fluid Analysis
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Solution Overview
Problem
Current methods for analyzing drilling fluid cuttings and cavings, such as hyperspectral imaging and camera systems, face challenges in accurately distinguishing between cuttings and background, tracking particle movement, and correlating mineralogy and morphology data, leading to incomplete characterization of drilling fluid contents.
Innovation Solution
Combining hyperspectral imaging with high-speed cameras and computer vision techniques to generate corrected hyperspectral imaging data, differentiate between cuttings and background, track particle movement, and synchronize data to provide accurate mineralogy and morphology analysis of drilling fluid cuttings.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If hyperspectral imaging is used to analyze drilling fluid cuttings, then mineralogy characterization is improved, but difficulty in distinguishing cuttings from background increases
Solution Approach 1:
The patent combines hyperspectral imaging data with computer vision-based optical flow tracking to create a integrated analysis system. The optical flow algorithm provides motion-based segmentation that helps distinguish cuttings from background, while hyperspectral imaging provides mineralogical composition data, resolving the contradiction between improved characterization and difficulty in distinction.
Solution Approach 2:
The patent introduces optical flow tracking as an intermediary technique that bridges the gap between hyperspectral imaging and cuttings identification. By using motion information from optical flow as an intermediate layer, the system can effectively segment cuttings from background before applying hyperspectral analysis, thus resolving the detection difficulty.
2Measurement precision
If multiple imaging systems are combined for comprehensive analysis, then data quality is improved, but system complexity increases
Solution Approach 1:
The patent makes the imaging system multi-functional by combining hyperspectral imaging and optical flow tracking in a single integrated framework. The system simultaneously performs mineralogy analysis, motion tracking, and segmentation functions, improving data quality while managing complexity through unified processing rather than separate dedicated systems.
Solution Approach 2:
The patent merges hyperspectral imaging and optical flow tracking into a single integrated analysis pipeline. By combining these multiple imaging approaches and processing them together through unified algorithms, the system achieves comprehensive data quality improvement while avoiding the complexity of fully separate systems through integrated processing architecture.
3Measurement precision
If real-time tracking of particle movement is implemented, then particle characterization is improved, but processing time increases
Solution Approach 1:
The patent applies preliminary action by performing optical flow tracking and motion segmentation before full hyperspectral analysis. This preliminary processing step prepares the data by identifying and segmenting particles based on motion, so that subsequent mineralogy characterization can be performed more efficiently on already-identified regions, reducing overall processing time while maintaining characterization quality.
4Productivity
If hyperspectral imaging is performed on moving cuttings, then continuous monitoring is improved, but alignment and correlation of successive frames becomes difficult
Solution Approach 1:
The patent uses feedback from optical flow tracking to improve frame alignment in hyperspectral imaging. The optical flow algorithm provides motion vectors that indicate how cuttings move between successive frames, and this feedback information is used to correct and align the hyperspectral data, maintaining measurement precision while enabling continuous monitoring of moving particles.
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
This approach enables more accurate characterization of drilling fluid cuttings and cavings by improving mineralogy and morphology identification, linking cuttings to geological formations, and enhancing data quality by distinguishing between cuttings and background, thus improving drilling efficiency and safety.
Implementation Method 1
generating a hyperspectral imaging data set comprising a plurality of lines of hyperspectral data derived from line images taken by the hyperspectral imaging device
Implementation Method 2
obtaining tracking information in respect of particles of interest from the output of the at least one optical camera
Data Source
AI summary
A system and method of analysing drilling cuttings using image data output from a hyperspectral imaging device and at least one optical camera, includes generating a hyperspectral imaging data set including a plurality of lines of hyperspectral data derived from line images taken by the hyperspectral imaging device positioned along a drilling fluid cuttings path, obtaining tracking information in respect of particles of interest from the output of the at least one optical camera, correcting the position of pixels associated with particles of interest in the plurality of lines of hyperspectral imaging data based on the obtained tracking information to generate corrected hyperspectral imaging data, and analysing the corrected hyperspectral imaging data to characterise the cuttings.