Drishya AI Labs Enhances Oil Plant Alarm Intelligence with Machine Learning

Drishya AI Labs: Enhancing Alarm Intelligence Through Machine Learning

This case study details how Drishya AI Labs partnered with OSUM, a Canadian oil and gas company, to address the challenge of alarm management in their operations. OSUM, a significant producer in Western Canada, utilizes Steam-Assisted Gravity Drainage (SAGD) technology for heavy crude oil extraction, a process heavily reliant on water and complex interconnected systems with established controls and interlocks.

The Challenge: Alarm Overload and Nuisance Alarms

Plant operators at OSUM are tasked with ensuring smooth operations, preventing malfunctions, and minimizing downtime. To achieve this, various alarms and sensors are integrated into the plant systems to signal potential disruptions and prompt timely intervention. However, a common issue faced is the simultaneous triggering of multiple alarms, creating a "conundrum" for operators who must prioritize which alarm to address first. Furthermore, nuisance alarms, such as "chattering" alarms, can serve as significant distractions, negatively impacting operational efficiency and potentially leading to costly plant downtime.

The Solution: Leveraging Machine Learning with Drishya AI Labs

Concerned by the increasing frequency of alarm spikes and the resulting operational disruptions, OSUM collaborated with Drishya AI Labs. The objective was to leverage machine learning algorithms to reduce these distractions and improve alarm management. Drishya AI Labs aimed to develop a system that could intelligently analyze alarm data, identify patterns, and provide operators with a more streamlined and effective way to manage alerts.

OSUM's Operations and the Role of Technology

OSUM operates within the oil and gas sector, with its headquarters in Calgary, Alberta. Canada's significant role in the US oil market, supplying over 35% of imported oil in 2023, underscores the importance of efficient and reliable operations in this industry. The SAGD technology employed by OSUM involves injecting steam to extract heavy crude oil, a process where water management is critical. The plant's intricate network of systems requires constant monitoring and control to maintain optimal performance.

The Impact of Effective Alarm Management

Effective alarm management is crucial for several reasons:

Operational Efficiency: By reducing nuisance alarms and helping operators prioritize critical alerts, the plant can run more smoothly.
Downtime Reduction: Proactive identification and resolution of issues signaled by alarms can prevent major breakdowns and minimize unplanned downtime.
Cost Savings: Plant downtime in the oil and gas sector can result in substantial financial losses. Improving alarm management directly contributes to cost reduction.
Operator Focus: Reducing distractions allows operators to concentrate on essential tasks, improving overall safety and productivity.

Drishya AI Labs' Approach

While the specifics of Drishya AI Labs' machine learning models are not detailed in this summary, their approach likely involved:

Data Collection: Gathering historical alarm data, sensor readings, and operational logs from the OSUM plant.
Feature Engineering: Identifying relevant features from the data that indicate alarm severity, root cause, or potential for nuisance.
Model Training: Developing and training machine learning models (e.g., classification, anomaly detection, or predictive models) to classify alarms, predict failures, or identify patterns of nuisance alarms.
Integration and Deployment: Integrating the developed AI solution into the existing plant control systems to provide real-time insights and recommendations to operators.

Key Takeaways

This case study highlights the critical role of advanced technologies like machine learning in optimizing industrial operations. By addressing the complex challenge of alarm management, Drishya AI Labs provided OSUM with a solution that promises to enhance efficiency, reduce costs, and improve the overall operational environment for plant operators. The focus on intelligent alarm prioritization and the mitigation of nuisance alarms demonstrates a practical application of AI in a demanding industrial setting.

Product Details:

Product #: IM007B
Pages: 5
Publication Date: June 01, 2024
Source: Indian Institute of Management-Bangalore
Related Topics: Analytics and data science, AI and machine learning

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