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PROBLEM STATEMENT
CLIENT BACKGROUND
CASE STUDY
Transforming Oil Field Operations
with IoT Acoustic Sensors
The client is a leading oil and gas company with operations across
upstream, midstream, and downstream sectors. Focused on innovation and
safety, they aim to enhance operational efficiency through advanced
technologies. Their digital transformation strategy includes IoT, smart
sensors, and predictive maintenance solutions.
Pipeline
leaks often
went
undetected,
risking
safety and
violations.
Unexpected
equipment
failures led to
costly
unplanned
downtime.
Manual
inspections in
remote areas
exposed
personnel to
risks.
No real-time
asset visibility
made
proactive
issue
resolution
hard.
Rising
maintenance
costs due to
reactive repairs
and
replacements.
Despite advanced equipment, the client faced operational challenges that
impacted efficiency and increased costs
IOT SOLUTIONS IMPLEMENTED
TECHNOLOGY BEHIND IOT ACOUSTIC SENSORS
+1 (510) 956 6572 rejigdigital.com info@rejigdigital.com
To address these challenges, PetroCore deployed a network of IoT-enabled smart
acoustic sensors across its field operations. Key implementation highlights:
Installed on pipelines, compressors, and drilling equipment
Integrated with a centralized cloud-based monitoring system
Leveraged AI-powered analytics to detect abnormal acoustic patterns
Enabled automated alerts and predictive maintenance workflows
IoT acoustic sensors detect sound and vibrations to monitor equipment and
pipelines for early signs of issues like leaks and wear.
Real-Time Data: IoT sensors transmit continuous data, enabling
immediate feedback for quick monitoring and faster decision-making.
Cloud Connectivity: Data from sensors is stored on the cloud, providing
remote access for centralized monitoring and analysis.
Remote Monitoring: IoT sensors reduce manual inspections in hazardous
areas, improving safety and operational efficiency.
AI/ML Role:
Predictive Maintenance:
AI and ML analyze
sensor data to predict
equipment failures,
enabling proactive
maintenance and
minimizing unplanned
downtime.
Anomaly Detection:
AI algorithms detect
small deviations in
sensor data, identifying
potential issues before
they escalate.
Optimization:
AI-driven insights
optimize asset
performance, improve
resource allocation, and
reduce operational
costs.
Phase Duration Activities
Assessment
2 weeks
Field survey, risk analysis, and pilot
planning
Deployment 6 weeks
Sensor installation, IoT platform
configuration
Integration 3 weeks
Data sync with existing SCADA and
maintenance systems
Optimization Ongoing
ML model training for enhanced anomaly
detection
+1 (510) 956 6572 rejigdigital.com info@rejigdigital.com
With IoT acoustic sensors integrated, we now have complete visibility into the health of
our field assets, allowing us to address potential issues before they impact operations.
Rejig’s solution paid for itself in under 12 months.
PLANT MANAGER, A MID-SIZED GRINDING MACHINE COMPANY
IMPLEMENTATION TIMELINE

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Optimizing Oil Field Operations with IoT-Driven Acoustic Sensor Technology A Case Study.pdf

  • 1. PROBLEM STATEMENT CLIENT BACKGROUND CASE STUDY Transforming Oil Field Operations with IoT Acoustic Sensors The client is a leading oil and gas company with operations across upstream, midstream, and downstream sectors. Focused on innovation and safety, they aim to enhance operational efficiency through advanced technologies. Their digital transformation strategy includes IoT, smart sensors, and predictive maintenance solutions. Pipeline leaks often went undetected, risking safety and violations. Unexpected equipment failures led to costly unplanned downtime. Manual inspections in remote areas exposed personnel to risks. No real-time asset visibility made proactive issue resolution hard. Rising maintenance costs due to reactive repairs and replacements. Despite advanced equipment, the client faced operational challenges that impacted efficiency and increased costs
  • 2. IOT SOLUTIONS IMPLEMENTED TECHNOLOGY BEHIND IOT ACOUSTIC SENSORS +1 (510) 956 6572 rejigdigital.com info@rejigdigital.com To address these challenges, PetroCore deployed a network of IoT-enabled smart acoustic sensors across its field operations. Key implementation highlights: Installed on pipelines, compressors, and drilling equipment Integrated with a centralized cloud-based monitoring system Leveraged AI-powered analytics to detect abnormal acoustic patterns Enabled automated alerts and predictive maintenance workflows IoT acoustic sensors detect sound and vibrations to monitor equipment and pipelines for early signs of issues like leaks and wear. Real-Time Data: IoT sensors transmit continuous data, enabling immediate feedback for quick monitoring and faster decision-making. Cloud Connectivity: Data from sensors is stored on the cloud, providing remote access for centralized monitoring and analysis. Remote Monitoring: IoT sensors reduce manual inspections in hazardous areas, improving safety and operational efficiency. AI/ML Role: Predictive Maintenance: AI and ML analyze sensor data to predict equipment failures, enabling proactive maintenance and minimizing unplanned downtime. Anomaly Detection: AI algorithms detect small deviations in sensor data, identifying potential issues before they escalate. Optimization: AI-driven insights optimize asset performance, improve resource allocation, and reduce operational costs.
  • 3. Phase Duration Activities Assessment 2 weeks Field survey, risk analysis, and pilot planning Deployment 6 weeks Sensor installation, IoT platform configuration Integration 3 weeks Data sync with existing SCADA and maintenance systems Optimization Ongoing ML model training for enhanced anomaly detection +1 (510) 956 6572 rejigdigital.com info@rejigdigital.com With IoT acoustic sensors integrated, we now have complete visibility into the health of our field assets, allowing us to address potential issues before they impact operations. Rejig’s solution paid for itself in under 12 months. PLANT MANAGER, A MID-SIZED GRINDING MACHINE COMPANY IMPLEMENTATION TIMELINE