Automatic Slips Detection System for Drilling Operations
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Solution Overview
Problem
Current drilling operations face challenges in accurately monitoring and optimizing slips-to-weight and slips-to-slips operations, leading to inefficiencies and increased risks of differential sticking due to long connection times.
Innovation Solution
A system utilizing camera devices, sensor parameters, and machine learning models to automatically and real-time identify slips status, enabling accurate computation of elapsed times and optimizing drilling operations by integrating smart camera or vision sensor networks, image processing techniques, artificial intelligence, and deep learning models.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual monitoring of slips operations is used, then operational flexibility is maintained, but measurement precision and time management deteriorate
Solution Approach 1:
The patent replaces manual mechanical monitoring of slips operations with an automated vision-based detection system. Camera devices capture images of the slips mechanism, and image processing algorithms automatically analyze the slips status, eliminating the need for manual observation and measurement while significantly improving detection precision and time management.
2Productivity
If real-time automatic slips detection is implemented, then productivity and time management improve, but device complexity increases
Solution Approach 1:
The patent integrates multiple functions into a unified automated detection system. The same vision system performs slips status detection, elapsed time computation, and operational optimization simultaneously. This multi-functional approach improves productivity while managing complexity by consolidating rather than multiplying separate systems.
Solution Approach 2:
The detection system is designed to operate autonomously without continuous human intervention. The image processing algorithms automatically analyze captured images, determine slips status, compute elapsed times, and provide optimization recommendations, enabling the system to serve itself and reduce operational complexity despite the advanced technology involved.
3Loss of time
If traditional monitoring methods are used, then system complexity remains low, but loss of time and operational optimization deteriorate
Solution Approach 1:
The patent implements continuous real-time monitoring of slips operations through automated image capture and analysis. Unlike traditional intermittent manual checks, the vision system continuously tracks the slips mechanism, eliminating dead time and ensuring no loss of critical operational moments, thereby reducing overall connection time while managing complexity through automation.
Solution Approach 2:
The system incorporates real-time feedback mechanisms where detection results and elapsed time measurements are immediately fed back to operators and control systems. This continuous feedback loop enables timely decision-making and operational adjustments, minimizing loss of time despite the increased complexity of the monitoring infrastructure.
Data Source
AI summary
A method for determining a slips status during a drilling operation of a subterranean formation. The method includes capturing, using one or multiple camera devices mounted on a drilling rig of the drilling operation, a plurality of images, each of the plurality of images comprising a portion that corresponds to a slips device of the drilling rig, generating, using a sensor device of the drilling rig, a plurality of parameters of the drilling rig, wherein the plurality of parameters are synchronized with the plurality of images, providing, by a computer processor, the plurality of parameters as input to a machine learning model of the drilling rig, and analyzing, by the computer processor and based on the machine learning model, the plurality of images to generate the slips status.