AI for Oil & Gas
Use the power of enterprise-scale AI to improve uptime and reliability, increase production output, mitigate risk, and optimize processes.
Oil & gas companies are embracing AI and IoT to address a dynamic market of unprecedented challenges and opportunities
The ability to flexibly and rapidly respond to these market dynamics has been constrained by data segregated in disparate, rigid IT systems built over many years. Until now, efforts to integrate this data, build analytics, or generate actionable insights across the organization have proven expensive and difficult to maintain.
The C3 AI Suite rapidly delivers oil & gas AI applications that seamlessly integrate with existing systems
The C3 AI Suite provides comprehensive services to build enterprise-scale AI applications 25x to 100x faster than alternative approaches. The C3 AI Suite enables use of all relevant data sources that underpin machine learning models to rapidly generate predictive insights, enhance asset monitoring, improve operations, and optimize production, reliability, yield, and safety. A recent study of the value chain at a global oil & gas producer demonstrated that the economic value of enterprise-wide C3 AI Suite use could exceed $100 million annually.
C3.ai Applications for Oil & Gas
C3 Predictive Maintenance for Asset Health
Identify high-risk assets and recommend prescriptive actions before failures occur. C3 Predictive Maintenance enables operators to prioritize maintenance expenditures and directly operationalize maintenance through seamless integration with existing work order management and business systems.Learn More
Oil & Gas Use Cases Addressed by the C3 AI Suite
Generate operational recommendations for drilling new wells and for optimizing production from existing wells. Integrate operational data and reservoir geophysical models for comprehensive AI-enabled recommendations, leveraging near real-time analytics on drilling data signals (e.g., WOB, ROP, RPM, mud volume, cuttings, etc.) to determine operational parameters.
Identify corrosion risks, recommend inspection targets, and predict wall-loss events with recommended interventions for assets at risk. AI-enabled predictions seamlessly integrate with ionic modeling and engineering simulations to support oil & gas companies' efforts to remain compliant with American Petroleum Institute requirements to maximize safety and prevent loss of containment incidents.
Reduce waste, maximize value-added products, and identify process degradation such as fouling and coking. Integrated near real-time data, AI and machine learning algorithms, and engineering models provide unit-based and plant-wide performance optimization and continual feedback based on actual operational parameters. Users can leverage actionable recommendations that prioritize safety, production, runtime, and track yield risk issues over long time horizons spanning multiple unit shutdowns, revamps, and configuration changes.
Network and Flow Monitoring
Automate back-allocation and material-balance calculations using sensor data in an end-to-end process application. Identify operational deviations from predicted flows, generate alerts, and reduce bottlenecks. Aggregated results at the well, field, and network level enables users to automate production-loss analysis and investigate operational time-series data and events.
Machine Vision for Safety
Detect and alert safety hazards in near real-time using machine vision to analyze video and image-based data sources. Throughout upstream, midstream, and downstream operations, customers can remotely validate well-site operations security, detect asset integrity, and monitor retail safety hazards like consumer smoking behavior. Advanced object detection capabilities can be deployed on edge devices for in-field rapid processing and response time.