Automated Well Productivity Estimation via Neural Network
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Solution Overview
Problem
Manual pressure buildup surveys for well productivity estimation are time-consuming, costly, and provide limited, intermittent data, relying on engineering judgment and faulty assumptions, necessitating a more efficient and cost-effective alternative for reservoir pressure measurement and well productivity index determination.
Innovation Solution
An intelligent estimation system comprising at least two pressure sensors and a neural network model, which generates real-time pressure data from surface and downhole points of a well bore, estimates productivity index and reservoir pressure values in real-time, and displays graphical representations for continuous monitoring and analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual pressure buildup surveys are used to measure reservoir pressure and determine productivity index, then measurement accuracy is improved, but time consumption and cost increase significantly
Solution Approach 1:
The patent replaces manual mechanical survey methods with an automated electronic system that uses pressure sensors, temperature sensors, and a data processor to automatically collect and analyze pressure buildup data, eliminating the need for manual intervention and significantly reducing time consumption while maintaining measurement accuracy
Solution Approach 2:
The system performs self-service by automatically conducting pressure buildup surveys without requiring external manual operation. The data processor automatically processes sensor data, calculates reservoir pressure and productivity index, and generates results, making the system autonomous and eliminating dependency on manual survey teams
2Measurement precision
If manual pressure buildup surveys are conducted, then reservoir pressure data is obtained, but production interruptions occur due to well shut-in conditions
Solution Approach 1:
The system enables continuous pressure monitoring and productivity assessment without interrupting well production. By using automated sensors and real-time data processing, the system continuously collects pressure buildup data during normal production operations, eliminating the need for well shut-in and maintaining continuous productive action
Solution Approach 2:
The patent introduces pressure sensors and temperature sensors as intermediaries that can measure pressure buildup conditions without requiring actual well shut-in. These sensors act as mediators that capture the necessary data for reservoir pressure calculation while the well remains in production mode, avoiding direct disruption to production
3Quantity of substance
If manual pressure surveys are performed intermittently on a quarterly basis, then some productivity data is collected, but data completeness and reliability deteriorate due to sparse sampling
Solution Approach 1:
The system transitions from intermittent quarterly data collection to continuous real-time monitoring. Pressure sensors and temperature sensors continuously collect data throughout production operations, providing a complete and uninterrupted data stream that significantly improves data completeness and reliability compared to sparse periodic sampling
Solution Approach 2:
The system implements continuous feedback by constantly monitoring pressure and temperature parameters and immediately processing this data to update productivity index and reservoir pressure estimates. This real-time feedback loop ensures data reliability through continuous validation and adjustment, rather than relying on infrequent snapshots that may miss critical trends
4Productivity
If automated real-time pressure monitoring system is implemented, then productivity estimation speed and data completeness are improved, but system complexity and initial cost increase
Solution Approach 1:
The system achieves multi-functionality by using a single integrated platform that simultaneously performs pressure monitoring, temperature monitoring, productivity index calculation, and reservoir pressure estimation. This universal system handles multiple functions through one coordinated setup, reducing the need for separate specialized equipment and thereby limiting the increase in overall system complexity
Solution Approach 2:
The patent uses a data processor as an intermediary that simplifies the complexity of real-time data analysis. The data processor acts as a mediator between the sensors and the user, automatically performing complex calculations for productivity index and reservoir pressure while presenting simplified results, thereby managing system complexity through intelligent automation rather than requiring complex manual systems
Data Source
AI summary
Systems and methods for intelligent estimation of productivity index and reservoir pressure values using pressure sensors, a neural network model comprising historical flow rate data of at least a well bore, and a data processor. The pressure sensors generate pressure data associated with a well bore's surface point and a downhole point. The data processor, communicatively coupled to the two pressure sensors and the neural network model, is operable to receive the pressure data from the sensors respectively indicative of pressure at each of the two points, estimate a real-time productivity index value in real-time based on the pressure data from the pressure sensors and the historical flowrate data of the neural network model, and estimate a reservoir pressure value of the well bore at a flowing condition, a reservoir pressure value of the well bore at a shut-in condition, or both, based on the real-time productivity index.