Automated Cuttings Analysis via HSB Spectral Classification
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Solution Overview
Problem
The analysis of rock cuttings from wellbores is time-consuming and typically performed in a laboratory, requiring manual classification by geologists, which delays the acquisition of essential geological formation data.
Innovation Solution
A method and system that utilize an imaging device to capture images of cuttings on a background surface, processing them in the (hue, saturation, brightness) coordinate space to classify pixels into groups representing cuttings and background, enabling automated identification and classification of cuttings zones.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual analysis by geologists is used, then measurement precision is improved, but loss of time increases
Solution Approach 1:
The patent replaces the manual mechanical analysis process with an automated image processing system using color space transformation and spectral analysis. The calculator automatically processes cutting images through (hue, saturation, brightness) coordinate space to classify cuttings, eliminating the need for manual geologist inspection while maintaining classification accuracy.
Solution Approach 2:
The patent creates a digital spectral copy of the cutting samples through image capture and coordinate space transformation. Instead of directly examining physical samples, the system analyzes spectral representations in (hue, saturation, brightness) space, enabling automated classification that preserves measurement precision while dramatically reducing analysis time.
2Productivity
If automated image processing is used, then productivity is improved, but measurement precision may worsen
Solution Approach 1:
The patent transforms the analysis from direct spatial image examination to spectral parameter analysis in (hue, saturation, brightness) coordinate space. By changing the parameter domain from raw pixel values to spectral distributions, the system enables automated processing that maintains classification precision while improving productivity through algorithmic analysis.
Solution Approach 2:
The patent adds a spectral dimension to the analysis by transforming images into (hue, saturation, brightness) coordinate space and generating spectra for each coordinate. This dimensional transformation enables automated classification algorithms to operate on spectral profiles, achieving both high productivity and maintained measurement precision.
Data Source
AI summary
The disclosure relates to a method for analysing cuttings exiting a borehole. The method comprises taking at least an image of a sample of cuttings on a background surface, obtaining spectra representative of the image in the (hue, saturation, brightness) coordinate space, wherein each spectrum is associated to a coordinate and is representative of the distribution of the values of the pixels for the coordinate. Based on the spectrum and the values of each pixel for the associated coordinate, classifying the pixel in one of a plurality of groups, wherein each group is representative of a type of objects within the image, i.e. cuttings and background surface. The method also comprises determining at least a cuttings zone in the image based on the classification of the pixels.