View source for 18469324. INTEGRATED AUTONOMOUS OPERATIONS FOR INJECTION-PRODUCTION ANALYSIS AND PARAMETER SELECTION simplified abstract (Schlumberger Technology Corporation)

=INTEGRATED AUTONOMOUS OPERATIONS FOR INJECTION-PRODUCTION ANALYSIS AND PARAMETER SELECTION=


==Organization Name==

[[:Category:Schlumberger Technology Corporation|Schlumberger Technology Corporation]]


[[Category:Schlumberger Technology Corporation]]

==Inventor(s)==

[[:Category:Shripad Biniwale of Churchlands (AU)|Shripad Biniwale of Churchlands (AU)]][[Category:Shripad Biniwale of Churchlands (AU)]]

[[:Category:Sanjoy Kumar Khataniar of Abingdon (GB)|Sanjoy Kumar Khataniar of Abingdon (GB)]][[Category:Sanjoy Kumar Khataniar of Abingdon (GB)]]

[[:Category:Mohamed Osman Mahgoub Ahmed of Abingdon (GB)|Mohamed Osman Mahgoub Ahmed of Abingdon (GB)]][[Category:Mohamed Osman Mahgoub Ahmed of Abingdon (GB)]]

==INTEGRATED AUTONOMOUS OPERATIONS FOR INJECTION-PRODUCTION ANALYSIS AND PARAMETER SELECTION - A simplified explanation of the abstract==


This abstract first appeared for US patent application 18469324 titled 'INTEGRATED AUTONOMOUS OPERATIONS FOR INJECTION-PRODUCTION ANALYSIS AND PARAMETER SELECTION

==Simplified Explanation==

The patent application describes an integrated autonomous operation system that digitizes operations at multiple scales, connecting subsurface to production and utilizing AI for optimal water injection setpoints.

* The system provides end-to-end digital twin technology.
* Subsurface models monitor water-producing zones for strategic decisions.
* AI is used to determine optimum water injection setpoints.
* Automated systems control chokes and valves to meet setpoints.
* Achieves fully integrated, autonomous operations.

== Potential Applications ==
The technology could be applied in the oil and gas industry for enhanced reservoir management, improved production efficiency, and reduced operational costs.

== Problems Solved ==
This technology addresses the challenges of manual operation control, inefficient water injection practices, and lack of real-time monitoring in oil and gas production.

== Benefits ==
The benefits of this technology include increased production rates, optimized water injection processes, reduced downtime, and improved decision-making based on real-time data.

== Potential Commercial Applications ==
"Enhancing Oil and Gas Production Efficiency with Integrated Autonomous Operation System"

== Possible Prior Art ==
Prior art may include traditional reservoir management systems, manual operation control methods, and basic water injection optimization techniques.

=== Unanswered Questions ===

== How does the system handle unexpected changes in reservoir conditions? ==
The patent application does not provide specific details on how the system adapts to unforeseen changes in reservoir conditions, such as sudden water breakthroughs or pressure fluctuations.

== What cybersecurity measures are in place to protect the digital twin and operational data? ==
The patent application does not mention the cybersecurity protocols or encryption methods used to safeguard the digital twin and sensitive operational data from potential cyber threats.


==Original Abstract Submitted==

An integrated autonomous operation system that holistically renders the operation in digital form at multiple scales, including reservoir, surface infrastructure, workflows, processes, and the real asset. The system provides an end-to-end digital twin connecting subsurface to production. A subsurface model identifies and monitors water-producing zones for strategic decisions. The models use intelligent AI to provide optimum water injection setpoints. The models provide data to systems that automatically control the chokes and valves to meet the setpoints, thus achieving fully integrated, autonomous operations.



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