Wireline Cable Spooling With Vision-Based Fleet Angle Control

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Solution Overview

Problem

Conventional wireline cable spooling equipment faces difficulties in spooling the cable onto a rotating drum without leaving gaps, requiring expensive equipment modifications and affecting workflow efficiency.

Innovation Solution

An automated system using a trained artificial neural network to estimate the position of the wireline cable on a rotatable drum, adjusting the spooling arm to control the fleet angle and prevent anomalies, utilizing a vision-based model with convolutional neural networks for precise cable positioning.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Manufacturing precision

If conventional wireline cable spooling equipment is used, then the equipment structure is simple, but the cable spooling precision is poor and gaps are left between successive passes

Engineering Contradiction:
Improvecable spooling precisionVSAvoidequipment complexity
Core Design Contradiction:
Manufacturing precisionVSDevice complexity

Solution Approach 1:

The patent replaces conventional mechanical positioning systems with a vision-based neural network system. A video camera captures images of the cable position, and a trained neural network processes these images to determine precise cable location and fleet angle, eliminating the need for complex mechanical sensors and adjustment mechanisms while achieving superior spooling precision.

Inventive Principle:
Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The patent introduces a video camera and neural network as intermediary elements between the operator and the spooling process. Instead of direct mechanical feedback, the system uses visual information processed by AI to infer cable position and control spooling operations, enabling precise control without direct mechanical intervention.

Inventive Principle:
Principle #24Intermediary (Mediator)

2Productivity

If conventional cable spooling methods are used, then the equipment cost is low, but cable pileups and gaps occur affecting workflow efficiency

Engineering Contradiction:
Improveworkflow efficiencyVSAvoidcable spooling reliability
Core Design Contradiction:
ProductivityVSReliability

Solution Approach 1:

The patent implements a real-time feedback system where the video camera continuously monitors cable position on the drum, the neural network processes this visual data to determine current cable location and fleet angle, and the system adjusts spooling operations accordingly. This closed-loop feedback mechanism prevents cable pileups and gaps by continuously adapting to actual cable positioning conditions.

Inventive Principle:
Principle #23Feedback

Solution Approach 2:

The system performs preliminary assessment of cable position and fleet angle before each spooling operation. By predicting the optimal spooling parameters based on current cable configuration, the system prevents anomalies from occurring in the first place rather than reacting to problems after they arise, thereby improving both reliability and productivity.

Inventive Principle:
Principle #10Preliminary action

3Measurement precision

If expensive equipment modifications are made to improve spooling precision, then cable positioning accuracy improves, but the equipment cost increases significantly

Engineering Contradiction:
Improvecable position measurement accuracyVSAvoidequipment modification cost
Core Design Contradiction:
Measurement precisionVSEase of manufacture

Solution Approach 1:

The patent uses a video camera to create a visual copy or representation of the cable position on the drum. Instead of using expensive mechanical sensors or measurement devices, the system captures optical images and processes these copies through neural networks to extract precise position and fleet angle information, achieving high measurement precision at minimal cost.

Inventive Principle:
Principle #26Copying

Solution Approach 2:

The patent substitutes expensive mechanical measurement and positioning systems with a low-cost video-based optical system. The neural network algorithms replace complex mechanical sensors, providing precise cable position measurement without requiring expensive hardware modifications to the spooling equipment.

Inventive Principle:
Principle #28Mechanics substitution (Replace mechanical system)

Data Source

PatentUS12412381B2Methods and systems for controlling operation of wireline cable spooling equipment
Publication Date: 2025.09.09 SCHLUMBERGER TECH CORP
  • US12412381B2 patent drawing
  • US12412381B2 patent drawing
  • US12412381B2 patent drawing

AI summary

A method of controlling operation of equipment that spools cable on and off a rotatable drum, in one or more embodiments, includes obtaining video data of a position of the cable on the rotatable drum. The method can also include feeding data into a trained artificial neural network and processing the data fed into the trained artificial neural network to determine at least one of a calculated position of the cable on the rotatable drum, a calculated fleet angle, or both. The method can also include actuating the rotatable drum to one of spool cable on and off the rotatable drum.