BHC3 Hydrocarbon Loss Analytics
Reducing transportation and processing loss of crude oil
BHC3 Hydrocarbon Loss Analytics
Reducing transportation and processing loss of natural gas
BHC3 Hydrocarbon Loss Analytics
Reducing transportation and processing loss of refined oil
Identify Theft, Reduce Leakage and Verify Material Movement
BHC3™ Hydrocarbon Loss Analytics pinpoints patterns in data streams that highlight mass balance issues across hydrocarbon transportation networks so operations teams can respond in a timely manner to ensure physical safety and safeguard revenues.
Hydrocarbon transportation is among the most critical elements in the oil and gas supply chain, involving vast pipeline networks and spanning highly variable geographies. Complete and in-full delivery of supply requires coordination and verification. Any discrepancies found in mass balances between supply and delivery will not only impact revenue capture, but also generate considerable safety risk in the areas surrounding pipeline networks. Among the challenges in identifying those discrepancies include theft, leakage and sensor fidelity.
By ingesting data from numerous sources in the BHC3™ AI Suite and applying an ensemble of advanced AI algorithms, BHC3 Hydrocarbon Loss Analytics highlights areas of concern, quantifies the potential loss amount, and categorizes the risk for effective operator intervention and analysis. Issues are tracked and managed through the life cycle of analysis, review, confirmation and intervention, enabling maintenance engineers and production planners to identify trends and develop long-term investment plans.
Features
Prioritization of hydrocarbon loss risks
Comprehensive risk analysis that enables operators to address issues with appropriate resources.
Visual reconstruction of surface network
Assess deviations between as-designed and as-operated configurations, including categorizing discrepancies as true deviations or faulty sensors.
Advanced AI algorithms
Use AI models to distinguish between fraud and safety risks, equipment or pipeline leakage and faulty sensors.
Ad-hoc mass balance analysis capabilities
Enable maintenance and reliability engineers to conduct historical review of trouble areas and plan for asset and network upgrades.
Accurate and near real time assessment of material movement
Support invoicing and internal value accounting by verifying actual supplied and delivered quantities.
Configurable user interface and application logic
Integrate with existing operational business processes and enable fine-tuned access controls.
Comprehensive closed-loop workflow support
Enable operators to construct maintenance packages based on risk categorization. Create work orders directly from the application by leveraging bidirectional integration with work order management and dispatch systems.
Alerts and notification functionality
Facilitate effective coordination through configurable alerts and thresholds. Alerts are summarized and presented within the application and can be configured for delivery to designated contacts via SMS and/or email.
Benefits
Reduce
Reduce hydrocarbon losses through timely identification of pipeline and associated network risks.
Lower
Lower unplanned operational expense due to high precision in loss-issue isolation within geographic and network infrastructure, leading crews directly to high-risk area.
Enhance
Enhance safety risk by quickly highlighting and isolating emergent theft and leakage issues.
Improve
Improve assurance of delivered product through identification and replacement of faulty sensors, enabling more accurate invoicing.
Increase
Increase uptime through early identification and resolution of equipment at high risk of failure.
Optimize
Optimize planned maintenance costs through streamlined workflow that enables maintenance planners to effectively bundle and schedule high-priority work across the network.
Reduce
Reduce capital expenditures by driving sensor replacement decisions using sensor fidelity risk scores.
Proven results in weeks, not years
Get insights into BHC3 capabilities, enterprise AI best practices and highest-value use cases.
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