17934090. DYNAMIC REAL TIME GROSS RATE MONITORING THROUGH SUBSURFACE AND SURFACE DATA simplified abstract (Saudi Arabian Oil Company)
Contents
- 1 DYNAMIC REAL TIME GROSS RATE MONITORING THROUGH SUBSURFACE AND SURFACE DATA
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 DYNAMIC REAL TIME GROSS RATE MONITORING THROUGH SUBSURFACE AND SURFACE DATA - A simplified explanation of the abstract
- 1.4 Simplified Explanation
- 1.5 Potential Applications
- 1.6 Problems Solved
- 1.7 Benefits
- 1.8 Potential Commercial Applications
- 1.9 Possible Prior Art
- 1.10 Original Abstract Submitted
DYNAMIC REAL TIME GROSS RATE MONITORING THROUGH SUBSURFACE AND SURFACE DATA
Organization Name
Inventor(s)
Mohammed S. Kanfar of Dammam (SA)
Ali Saleh Alshehri of Dammam (SA)
Kalid Saad Dosary of Khobar (SA)
Abdulaziz A. Alsaleh of Dammam (SA)
Hussain M. Al-zahrani of Dammam (SA)
Ahmed K. Bubshait of Dhahran (SA)
Osama M. Kheshaifaty of Khobar (SA)
DYNAMIC REAL TIME GROSS RATE MONITORING THROUGH SUBSURFACE AND SURFACE DATA - A simplified explanation of the abstract
This abstract first appeared for US patent application 17934090 titled 'DYNAMIC REAL TIME GROSS RATE MONITORING THROUGH SUBSURFACE AND SURFACE DATA
Simplified Explanation
The patent application describes a method for estimating the continuous gross rate of multiple wells using information from sensors on electrical submersible pumps and a physics-based pipeline simulation.
- Sensors on electrical submersible pumps provide data on well performance.
- Information on the model of each pump is accessed.
- Artificial intelligence or machine learning processes the sensor data and pump model information to estimate a first gross rate for each well.
- A pipeline simulation using a physics-based model is used to estimate a second gross rate for each well.
- The continuous gross rate for each well is then estimated based on the first and second gross rates.
Potential Applications
The technology can be applied in the oil and gas industry for optimizing production rates and monitoring well performance.
Problems Solved
This technology helps in accurately estimating the gross rate of multiple wells, allowing for better decision-making in production operations.
Benefits
The method provides continuous and accurate estimates of well performance, leading to improved efficiency and productivity in oil and gas production.
Potential Commercial Applications
The technology can be used by oil and gas companies to optimize production, reduce downtime, and maximize output from multiple wells.
Possible Prior Art
Prior art may include methods for estimating well production rates using sensor data and simulation models in the oil and gas industry.
Unanswered Questions
How does this technology compare to traditional methods of estimating well production rates?
This article does not provide a direct comparison between this technology and traditional methods of estimating well production rates.
What are the potential limitations or challenges of implementing this technology in real-world oil and gas operations?
The article does not address the potential limitations or challenges of implementing this technology in real-world oil and gas operations.
Original Abstract Submitted
Continuous gross rate of each of a plurality of wells is estimated. Information provided by sensors configured with each of a plurality of electrical submersible pumps is received. Information associated with a respective model of each of the plurality of electrical submersible pumps is accessed. Utilizing at least one of artificial intelligence and machine learning, the information provided by sensors and the information associated with the respective model of each of the plurality of electrical submersible pumps is processed to estimate a first gross rate of each of the plurality of wells. A second gross rate of each of the plurality of wells is estimated via a pipeline simulation that applies a physics-based model. A continuous gross rate for each of the plurality of wells is estimated as a function the first gross rate and the second gross rate.
