Event Driven Control for Artificial Lift Equipment
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Solution Overview
Problem
Existing technologies for oil and gas production lack efficient automatic event detection and correction systems, leading to potential equipment failures and production disruptions.
Innovation Solution
A system and method for automatic event detection and correction in oil and gas production equipment, utilizing sensors to receive data on equipment parameters, determining event conditions, generating potential corrective actions, calculating reward values, and selecting the most effective corrective action to control the equipment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual monitoring and control methods are used for oil and gas production equipment, then system complexity is reduced, but productivity and response time to equipment events deteriorate
Solution Approach 1:
The control system automatically detects equipment events, evaluates corrective actions, and implements control decisions without requiring continuous manual intervention. The system serves itself by autonomously monitoring equipment parameters, identifying events, selecting optimal corrective actions based on reward values, and executing control commands to maintain production efficiency.
Solution Approach 2:
The patent replaces manual mechanical monitoring and control processes with an automated computational system that uses sensors, data processing algorithms, and electronic control mechanisms. This substitution of manual operations with automated systems increases productivity while managing complexity through structured computational approaches.
2Reliability
If comprehensive event detection and correction systems are implemented, then reliability of equipment operation is improved, but device complexity increases
Solution Approach 1:
The system continuously monitors equipment parameters through sensors, compares actual values against expected ranges, detects deviations indicating events, evaluates corrective actions based on their potential impact, and implements control decisions. This closed-loop feedback mechanism ensures reliable equipment operation by automatically responding to events while maintaining a structured approach to managing system complexity.
Solution Approach 2:
The system proactively detects equipment events before they lead to failures by continuously monitoring parameters and identifying anomalies. Corrective actions are evaluated and prepared in advance, with the system selecting optimal actions based on reward values that predict their effectiveness. This preliminary detection and preparation of corrective measures enhances reliability while keeping the control system organized and manageable.
3Loss of time
If real-time data monitoring and automatic corrective action implementation are used, then loss of time in responding to equipment events is reduced, but device complexity increases
Solution Approach 1:
The control system autonomously performs real-time monitoring of equipment parameters, automatically detects events as they occur, evaluates multiple corrective actions using reward value calculations, and immediately implements the optimal control decision without human intervention. This self-service capability eliminates time losses associated with manual detection and response while managing complexity through automated algorithms.
Solution Approach 2:
The system maintains continuous monitoring of equipment parameters, ensuring uninterrupted detection of events. The evaluation and implementation of corrective actions occur continuously without interruption, allowing the system to respond immediately to events as they occur. This continuous operation minimizes response time while the structured automated process manages the complexity of real-time decision-making.
Data Source
AI summary
A system for oil and gas production includes a drilling, pipeline, or power quality equipment, a sensor, and a storage device having instructions stored thereon that, when executed by one or more processors, cause the one or more processors to perform operations. The operations include receiving first data from the sensor, determining whether the drilling, pipeline, or power quality equipment is experiencing an event condition based on the first data, generating one or more potential corrective actions, identifying a first corrective action of the one or more potential corrective actions, and controlling a fluid transfer device to implement the first corrective action. The first corrective action includes at least one of increasing a drive frequency of the fluid transfer device, adjusting a choke position of the fluid transfer device, or reversing a rotational direction of an impeller of the fluid transfer device.