Surface Data Monitoring for Gas Production Deviations
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Solution Overview
Problem
Current gas production monitoring and management systems rely on downhole data, which can be costly and inefficient, and struggle to predict and mitigate performance deviations in hydrocarbon wells without real-time surface data analysis.
Innovation Solution
A computer-implemented method using surface production data to generate predictions about gas production system conditions, compute performance deviations, and trigger automated responses, such as warnings or interventions, based on machine-learning algorithms and surface network simulations, without requiring downhole data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If downhole data is used for monitoring and managing gas production, then measurement precision is improved, but device complexity and cost increase
Solution Approach 1:
The patent introduces surface-based sensors and a computer system as intermediaries to monitor gas production parameters (flow rate, pressure, temperature) without requiring downhole measurement devices. The surface sensors capture production data that is then processed by the computer system to detect performance deviations, eliminating the need for complex downhole instrumentation while maintaining monitoring capability.
Solution Approach 2:
The patent replaces mechanical downhole sensing systems with a computational approach using surface sensors and machine learning algorithms. The computer system analyzes surface measurement data to infer subsurface conditions and detect performance deviations, substituting physical downhole devices with an information-processing system that achieves similar monitoring objectives with reduced complexity.
2Productivity
If real-time surface data analysis is implemented, then productivity is improved, but use of energy increases
Solution Approach 1:
The patent implements preliminary action by continuously collecting and analyzing surface production data in real-time to detect performance deviations before they lead to significant production losses. The system proactively identifies trends and triggers automated responses, enabling early intervention that prevents larger problems while maintaining efficient energy use through continuous monitoring rather than periodic intensive analysis.
Solution Approach 2:
The system performs self-service by automatically detecting performance deviations and triggering appropriate responses without requiring constant human intervention. The computer system autonomously analyzes surface data, compares it against expected performance, and initiates corrective actions, reducing the need for energy-intensive manual monitoring and decision-making processes.
3Reliability
If automated responses are triggered based on performance deviation, then reliability is improved, but device complexity increases
Solution Approach 1:
The patent implements feedback by continuously comparing actual surface production data against expected performance parameters and automatically triggering responses when deviations exceed predetermined thresholds. This closed-loop control system maintains reliable and consistent performance by providing real-time feedback and corrective action, while the rule-based threshold approach keeps the control logic relatively simple and manageable.
Data Source
AI summary
Disclosed are methods, systems, and computer-readable medium to perform operations including: obtaining surface production data of wells in the gas production system; generating, using a well simulation module and a surface network module, predictions about a plurality of conditions in the gas production system; computing a difference between measured conditions obtained from the production data and predicted conditions obtained from the predictions about the plurality of conditions; determining, based on the computed difference, a performance deviation in the gas production system; comparing the performance deviation to a predetermined threshold value that represents an acceptable tolerance for variance in performance of the gas production system; and triggering, when the performance deviation exceeds the predetermined threshold value, a particular type of automated response comprising an action that addresses the variance in performance of the gas production system.