Case Study Transforming Oil & Gas Pipeline Safety with IoT-Based Leak Detection

1. CASE STUDY Enhancing Oil & Gas Pipeline Safety Through IoT-Based Leak Detection CLIENT BACKGROUND The client is a leading multinational oil and gas company specializing in the extraction, transportation, and distribution of petroleum products, with a vast network of pipelines and a strong commitment to safety, environmental protection, and regulatory compliance. Technology Behind IoT-Based Leak Detection Rejig Digital’s IoT-based leak detection uses advanced sensors, real-time analytics, and automated responses for continuous pipeline monitoring and rapid leak detection. Sensor data is securely transmitted in real time through an IoT network, ensuring fast and reliable leak detection. AI and analytics detect anomalies and predict maintenance, helping prevent issues before they disrupt operations. Sensors monitor pressure, flow, temperature, and sound along the pipeline to quickly detect and locate leaks with high accuracy. A live dashboard shows real-time alerts and leak locations with map integration, enabling fast and informed response.

2. IOT SOLUTIONS IMPLEMENTED To address the client’s operational challenges, Rejig Digital implemented a comprehensive IoT-based solution, integrating advanced acoustic sensors, real-time data transmission, and predictive analytics. Key components of the solution included: Acoustic Leak Detection Sensors: Acoustic sensors continuously monitor pipeline sound waves, detecting early leaks and malfunctions, ensuring timely issue detection. Real-Time Data Transmission: Sensors are integrated into a secure IoT network, enabling fast, low-latency data transmission for continuous pipeline visibility, even in remote areas. Predictive Maintenance and Analytics: Machine learning analyzes real-time sensor data to identify anomalies, predict failures, and optimize maintenance schedules proactively. Centralized Monitoring Dashboard: A user-friendly dashboard consolidates live sensor data and visual alerts, providing operators with actionable insights for quick decision-making. Problem Statement Ineffective Monitoring Remote Pipeline Challenges Safety & Delayed Responses Environmental Risks Sensor data is securely transmitted in real time through an IoT network, ensuring fast and reliable leak detection. AI and analytics detect anomalies and predict maintenance, helping prevent issues before they disrupt operations. Sensors monitor pressure, flow, temperature, and sound along the pipeline to quickly detect and locate leaks with high accuracy. A live dashboard shows real-time alerts and leak locations with map integration, enabling fast and informed response. CASE STUDY 3

3. IMPLEMENTATION TIMELINE Phase Duration Activities Site survey, risk assessment, feasibility study, and solution design Assessment 2 weeks Installation of IoT-based acoustic sensors, network configuration, and platform setup 6 weeks Deployment Integration with existing SCADA systems and real-time data sync with monitoring platforms 3 weeks Integration Continuous refinement of machine learning models for enhanced anomaly detection and predictive maintenance Optimization Ongoing With IoT acoustic sensors in place, we now have full visibility into our pipeline’s health, allowing proactive issue resolution. Rejig Digital's solution paid for itself in under a year. PIPELINE OPERATIONS MANAGER, LEADING OIL & GAS OPERATOR info@rejigdigital.com rejigdigital.com +1 (510) 956 6572