Murphy Oil Corporation is an independent exploration and production company with a balanced portfolio of global offshore and onshore assets. Murphy produces oil and natural gas in the United States and Canada while conducting exploration activities worldwide.
Murphy Oil Corporation is extracting business value with various digital initiatives, impacting its key LOBs. In 2019, with SAP CP, Murphy Oil Corporation has implemented complex solutions including visualization for high-velocity frac data, built remote assistant to bridge knowledge gaps in workforce and used iRPA to improve forecasting by identifying data anomalies and creating tasks in ROC workbench using AI based business rules. Through the use of real-time data in Completion process, Murphy is becoming an intelligent enterprise. Murphy is using advanced technologies such as AI, ML and Augmented Analytics to execute unique projects cost-effectively, deploy existing technologies in new ways and reduce downtime, improve its efficiency and maximize oil production.
Touchless Mobile for operators using voice commands to complete the tasks on the field, powered by the Alan Conversational Voice AI Platform
Murphy Oil Corporation was looking to reduce the non-productive time during well operations. Non-productive time caused by mechanical failures, weather, and logistical problems add substantial overhead to operations. Reductions in these overheads can result in lower costs and improved health, safety, and environmental performance.
- Advanced visualization to generate a more comprehensive view from field data to well completion
- Remote Assistant to bridge knowledge gaps in workforce between operators and field staff
- Robotic Process Automaton to mitigate operational risks and discrepancies for project cost tracking
- Touchless Mobile for operators using voice commands to complete the tasks on the field
Rapid decision making with real-time visualization of Completion data, driving down operational cost and expenses with remote assistant, improving forecasting by identifying data anomalies and creating tasks in workbench using AI based business rules, reducing operational risks and discrepancies in system by leveraging automation while improving communication across functions, ensuring consistency and repeatability in the Completion process.