Intelligent Completion Valve Position Sensing With Acoustic Machine Learning
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Solution Overview
Problem
Hydrocarbon well operators face challenges in accurately determining the position of downhole control valves due to changes in hydraulic fluid characteristics and lack of real-time monitoring, leading to unintended valve adjustments and inefficiencies in well operations.
Innovation Solution
A machine-learning-based system that utilizes acoustic sensing and distributed acoustic sensing (DAS) to record acoustic signals from intelligent completion valves (ICVs), correlating them with fluid flow rates to train a model that accurately determines ICV position changes and adjusts valve positions accordingly.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If hydraulic control lines are used to adjust downhole control valves from the surface, then valve position control is enabled, but the operator cannot accurately determine if the valve has reached the intended setting position due to changes in hydraulic fluid characteristics and lack of real-time monitoring
Solution Approach 1:
The patent implements a feedback system using acoustic sensors downhole to detect valve position changes and provide real-time information to the surface. The acoustic sensing system monitors the actual valve position and feeds this information back to the control system, enabling the operator to accurately determine when the valve has reached the intended setting position despite hydraulic fluid characteristic changes.
Solution Approach 2:
The patent replaces the traditional mechanical/hydraulic position indication system with an acoustic sensing system. Instead of relying on hydraulic fluid characteristics to indicate valve position, the system uses acoustic signals generated by the valve mechanism itself to detect and report position changes, providing more reliable measurement.
2Adaptability or versatility
If traditional hydraulic control systems are used without real-time monitoring, then valve adjustment capability is provided, but the operator is unaware of previous control valve setting changes leading to unintended valve adjustments
Solution Approach 1:
The acoustic sensing system provides continuous feedback on valve position changes, informing the operator of any setting adjustments that occur. This feedback loop eliminates information loss by ensuring the operator is always aware of the current valve state and any changes from previously intended settings.
Solution Approach 2:
The downhole acoustic sensing system automatically detects and reports valve position changes without requiring active operator intervention or monitoring. The system serves itself by continuously monitoring and communicating valve state, eliminating the need for the operator to actively track valve settings.
3Adaptability or versatility
If hydraulic fluid characteristics change based on temperature and other factors, then hydraulic control functionality is maintained, but the reliability of valve position indication deteriorates
Solution Approach 1:
The patent substitutes the hydraulic fluid-based position indication mechanism with an acoustic sensing mechanism. The acoustic sensors detect valve position through sound waves generated by the valve mechanism, which are not affected by hydraulic fluid characteristic changes due to temperature or other factors, thereby maintaining reliable position indication.
Solution Approach 2:
The acoustic sensing system acts as an intermediary between the valve mechanism and the operator. Instead of directly relying on hydraulic fluid characteristics to indicate position, the acoustic sensors serve as intermediaries that detect valve position through a different physical phenomenon (acoustic waves) that is not influenced by hydraulic fluid changes.
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
Enhances wellbore operation efficiency by maintaining target flow rates, preventing issues like water breakthrough and caprock integrity loss, and improving production and sweep efficiency through precise ICV control.
Implementation Method 1
an acoustic sensing system to record the acoustic signals produced by the ICVs
Data Source
AI summary
A system for operating intelligent completion valves (ICVs) used in a hydrocarbon well operation is disclosed. The ICVs can be positionable downhole in a wellbore. A trained machine-learning model can be generated by training a machine-learning model on training data comprising acoustic signal data generated by a pressurized injection fluid flowing through the ICVs at various flow rates and different ICV positions. When new acoustic sensing system sensor data associated with an ICV of multiple ICVs in the wellbore is applied to the trained machine-learning model, the trained machine-learning model can generate a result determining that the amplitude spike is attributable to a change in the position of the intelligent completion valve. The system may also determine a magnitude of the change in the position of the intelligent completion valve. The result may be output and used to control the ICV.