Intelligent production adjustment early warning for shale gas wells based on fuzzy logic control
Against the backdrop of continuously advancing big data technology, digitization and intelligent production management of oil and gas fields have become an inevitable trend. Shale gas wells face challenges such as liquid accumulation, sand production, and high stress sensitivity, necessitating the c...
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| Format: | Article |
| Language: | zho |
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Editorial Department of Petroleum Reservoir Evaluation and Development
2025-02-01
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| Series: | Youqicang pingjia yu kaifa |
| Subjects: | |
| Online Access: | https://red.magtech.org.cn/fileup/2095-1426/PDF/1737903101512-1817198654.pdf |
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| Summary: | Against the backdrop of continuously advancing big data technology, digitization and intelligent production management of oil and gas fields have become an inevitable trend. Shale gas wells face challenges such as liquid accumulation, sand production, and high stress sensitivity, necessitating the consideration of numerous factors during production adjustment. Traditional methods, which require extensive manual labor and exhibit low efficiency in production adjustment warnings, fail to consider multiple factors for optimal adjustment. To address this issue, considering the typical lifecycle characteristics of shale gas wells, the study divided the lifecycle into three stages: liquid unloading and gas transportation, stable production and pressure reduction, and fixed pressure and production reduction. Specific production adjustment rules tailored to different lifecycle stages were defined and six types of production adjustment indicators were proposed, including pressure drop method in stable production period, gas production per unit pressure drop method, critical sand-carrying flow rate method, critical liquid-carrying flow rate method, empirical chart method, and intermittent well-switching method. Based on these production adjustment rules and indicators, combined with field experience, an intelligent production adjustment early warning model for shale gas wells using fuzzy logic control was established. Implemented in Python, this model allows for real-time calculation of all production adjustment indicators and the fuzzy logic control algorithm as the well production dynamics change. This method has been applied in over a hundred wells in the Weirong shale gas field, reducing early warning times for production adjustments to just 30 seconds, compared to the traditional methods that require at least 5 days. The timely early warning of production adjustment needs has achieved good application results. In the future, combining remote control of oil nozzles or choke valves to adjust the production regime can provide technical support for intelligent oil and gas fields. |
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| ISSN: | 2095-1426 |