The intelligent well system integrates IoT and edge computing technologies to establish a dynamic monitoring platform covering the entire lifecycle of oil wells. It constructs deep learning-based models for fault diagnosis, energy consumption optimization, and production forecasting, enabling intelligent speed regulation of pumping units, smart lubrication, and self-optimizing production strategies. The system accurately identifies insufficient fluid supply, adjusts stroke frequency and stroke length in real time, and adapts the lubrication system to operating conditions, with production forecast error controlled within ±10%. Following deployment, per-well energy consumption has been reduced by 30%, and fault handling efficiency has increased by 90%.

With a modular design philosophy and following the design standards of unification, standardization, refinement, and typification, the system achieves optimized layout, module partitioning, process flow, and equipment selection. This greatly improves the efficiency and quality of engineering construction while reducing construction and operation costs as well as safety risks.

Targeting the urgent demand for cost-effective shale oil (gas) development, this project integrates multi-source data—including geology, reservoirs, engineering, production, and expert insights—with AI and big data technologies to establish an intelligent technology system centered on the "Oil & Gas Drilling and Production Big Data Model." The system features modules for intelligent evaluation of production testing capacity, full-process optimization of shale oil (gas) production testing, high-precision EUR prediction, full-lifecycle intelligent diagnosis, and dynamic production forecasting, enabling closed-loop management from capacity assessment and parameter optimization to production early warning. By combining mechanistic models with data-driven approaches, the "Shale Oil Intelligent Production Diagnosis System" has been developed, significantly enhancing the precision and efficiency of development decisions and supporting the economically efficient development of shale oil.