Hyperspectral Imaging for Hydrocarbon Emission Quantification
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Solution Overview
Problem
Current subterranean operations lack effective methods for monitoring and quantifying hydrocarbon emissions, posing safety and operational challenges in identifying and managing gaseous hydrocarbons during oil field processes.
Innovation Solution
Hyperspectral imaging technology is employed using a Hyperspectral Image Capture Mechanism (HICM) to capture and process images across the electromagnetic spectrum, allowing for continuous monitoring and characterization of materials, including gaseous hydrocarbons, by aligning and stacking frames, removing background noise, and cross-correlating hyperspectral components to estimate flow rates and volumes of emissions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional monitoring methods are used for hydrocarbon emissions, then the system is simple and easy to operate, but the detection precision and measurement accuracy are insufficient
Solution Approach 1:
The patent replaces traditional mechanical or simple electronic monitoring systems with hyperspectral imaging technology that uses electromagnetic spectrum analysis. The HICM captures images across multiple spectral bands and uses cross-correlation algorithms to detect hydrocarbon emissions, substituting physical measurement methods with optical-spectral analysis to achieve higher detection precision.
Solution Approach 2:
The patent changes the measurement parameters from traditional single-band detection to multi-spectral parameter analysis. By capturing and analyzing images across multiple spectral bands (different wavelengths of electromagnetic radiation), the system transforms the detection approach to use spectral signature variations for identifying and quantifying hydrocarbon emissions, thereby improving measurement accuracy.
2Reliability
If hyperspectral imaging is implemented for continuous monitoring, then the measurement precision and detection capability improve, but the device complexity and data processing requirements increase
Solution Approach 1:
The patent segments the complex hyperspectral data processing into distinct functional modules: image capture across multiple spectral bands, background noise removal, cross-correlation analysis of spectral signatures, and flow rate estimation. This segmentation allows each processing stage to be optimized independently and simplifies the overall system architecture while maintaining high detection reliability.
Solution Approach 2:
The patent introduces cross-correlation algorithms as an intermediary processing step between raw hyperspectral image capture and final emission quantification. This intermediary technique compares spectral signatures across multiple images to reliably identify hydrocarbon emissions while filtering out background variations, thereby enhancing detection reliability without requiring direct complex processing of all raw data.
3Measurement precision
If multiple image frames are captured and processed for accurate quantification, then the measurement precision improves, but the processing time and loss of time increase
Solution Approach 1:
The patent performs preliminary processing of captured image frames by removing background noise and pre-aligning spectral signatures before conducting cross-correlation analysis. This preliminary action prepares the data in advance, reducing the computational burden during final quantification and minimizing the overall processing time while maintaining measurement precision.
Solution Approach 2:
The patent implements continuous capture and processing of image frames in a sequential workflow, where each frame is processed immediately upon capture. This continuous action allows for real-time or near-real-time emission monitoring, reducing the total time loss by eliminating idle periods between capture and processing operations.
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 accurate detection and quantification of hydrocarbon emissions, improving safety and operational efficiency by providing real-time data on gas volumes and flow rates, thereby enhancing flare off heat analysis and mineral identification in subterranean operations.
Implementation Method 1
A hyperspectral image capture mechanism (HICM) is employed to capture and process images across the electromagnetic spectrum
Implementation Method 2
cross-correlating hyperspectral components to estimate flow rates and volumes of emissions
Data Source
AI summary
Apparatus and methods for imaging and characterizing materials when performing subterranean operations are disclosed. A method for analyzing gaseous emissions from a subterranean formation comprises positioning a hyperspectral image capturing mechanism to monitor an area of interest and detecting presence of one or more materials of interest in the area of interest using the hyperspectral image. The amount of the one or more materials of interest in the area of interest is then quantified.