Flare Stack Imaging for Real-Time Drilling Parameter Adjustment
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing flare stack monitoring in drilling operations is prone to human error, slow processing times, and inefficient use of information, posing safety risks and environmental pollution due to incomplete data processing.
Innovation Solution
Implementing image detection technology using a computer-implemented method to analyze flare stack images, determine wellbore features, and adjust drilling parameters based on image data, including the use of deep neural networks for analysis and real-time data processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If visual inspection is performed by an engineer, then operational safety can be monitored, but human error and slow processing times occur
Solution Approach 1:
The patent replaces the mechanical system of human visual inspection with an automated image processing system using cameras and computer algorithms. The system captures images of the flare stack and uses image processing techniques to automatically analyze flame characteristics, eliminate human error, and provide real-time monitoring without manual intervention.
Solution Approach 2:
The system enables self-service monitoring where the flare stack monitoring performs itself through automated image capture and analysis. The computer-implemented method automatically processes images, extracts relevant parameters, and generates alerts without requiring engineer intervention, making the monitoring system autonomous and eliminating human error.
2Loss of information
If cameras with thermal imaging capabilities are used, then remote viewing and temperature readings are obtained, but data processing becomes more complex and time-consuming
Solution Approach 1:
The patent extracts only the essential information from the captured images that is relevant to flare stack monitoring. Instead of processing all thermal imaging data, the system selectively extracts flame presence, temperature ranges, and abnormal conditions using targeted image processing algorithms, reducing complexity while maintaining information completeness.
Solution Approach 2:
The image processing system is designed to handle multiple types of imaging data (visible light and thermal) through a unified processing framework. The same computer-implemented method processes both image types to extract relevant parameters, simplifying the system architecture while maintaining comprehensive monitoring capabilities.
3Measurement precision
If extensive image data is collected from the flare stack, then comprehensive monitoring information is obtained, but the information becomes difficult to process quickly
Solution Approach 1:
The patent segments the image processing task into distinct stages: image acquisition, pre-processing, feature extraction, and analysis. By dividing the comprehensive image data processing into manageable segments with specific functions, the system maintains high detection accuracy while improving processing efficiency through specialized algorithms for each stage.
Solution Approach 2:
The system performs preliminary processing of image data immediately upon capture, including noise reduction, enhancement, and initial feature detection. This preliminary action prepares the data for faster subsequent analysis, maintaining measurement precision while reducing the time required for comprehensive processing.
Data Source
AI summary
Detection technology to monitor a flare stack during drilling operations and determine information based on the imaging. Various actions may be taken based on the determined information. For example, subterranean geology may be mapped. This may include mapping formation properties, fractures, faults or reservoir zones. Additionally, drilling operational parameters may be adjusted. This may include adjusting rate of direction, penetration, weight on bit, rotary speed, mud flow rate, mud weight, actuating a valve, or changing the pump speed.