Computer Vision Wellhead Monitoring for Displacement Detection

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Solution Overview

Problem

Existing wellhead monitoring systems lack efficient methods for detecting and quantifying displacement and growth due to thermal and pressure-induced loads, which can lead to well integrity failures and safety risks.

Innovation Solution

An automated wellhead monitoring system using computer vision and artificial intelligence, employing image dimension and perspective calibration, constructs computer vision models from a wellhead database to extract shape and geometric information, and estimate displacement and growth based on labeled images and video analysis.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If automated computer vision monitoring is implemented, then detection precision and productivity are improved, but device complexity increases

Engineering Contradiction:

Improvedisplacement detection precisionVSAvoidsystem complexity

Core Design Contradiction:

Measurement precisionVSDevice complexity

Solution Approach 1:

The patent replaces manual measurement methods with automated computer vision systems. Image processing algorithms and machine learning models automatically extract wellhead displacement data from images, eliminating the need for physical measurement devices and manual data collection, thereby improving precision while managing system complexity through software-based solutions

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The system creates digital copies of wellhead structures through image capture and 3D reconstruction. By working with digital representations rather than physical measurements, the system achieves high precision displacement monitoring without requiring complex physical measurement infrastructure at the wellsite

Inventive Principle:

Principle #26Copying

2Reliability

If real-time monitoring is implemented, then safety and reliability are improved, but energy consumption and device complexity increase

Engineering Contradiction:

Improvewellhead integrity reliabilityVSAvoidenergy consumption

Core Design Contradiction:

ReliabilityVSUse of energy by moving object

Solution Approach 1:

The system implements periodic monitoring at strategically selected time intervals rather than continuous real-time monitoring. Image capture and analysis are performed at intervals sufficient to detect displacement trends while allowing the system to enter low-power states between measurements, reducing overall energy consumption while maintaining wellhead integrity reliability

Inventive Principle:

Principle #19Periodic action

Solution Approach 2:

The monitoring system is designed to operate autonomously at remote wellsites, capturing images and analyzing displacement data without requiring constant external power or intervention. The system uses onboard processing and storage capabilities to self-manage monitoring operations, reducing the need for high-power continuous connectivity and external energy sources

Inventive Principle:

Principle #25Self-service

Data Source

PatentUS12430795B2Automated wellhead monitoring using imaging and computer vision

Publication Date: 2025.09.30 SAUDI ARABIAN OIL CO

AI summary

A computer-implemented method for automated wellhead monitoring using imaging and computer vision is described. The method includes establishing a baseline for a wellhead using image dimension and perspective calibration. The method also includes constructing at least one computer vision model using images or video from a wellhead database and inputting unseen wellhead images to the trained at least one computer vision model. Additionally, the method includes extracting a wellhead shape and geometric information of the wellhead in the unseen wellhead images and estimating wellhead displacement and growth based on the extracted images.