Directional drilling intelligent drilling system and control method based on digital twinning and multi-source information fusion

By constructing a digital twin and multi-source information fusion intelligent directional drilling system, the problems of heterogeneous data silos, delayed parameter inversion solutions, and passive risk assessment have been solved. The system achieves spatiotemporal synchronization of multi-source data and improves inversion accuracy, forming a closed-loop control across the entire chain, thereby enhancing the safety and efficiency of directional drilling.

CN122148277BActive Publication Date: 2026-07-21CHINA HYDROELECTRIC ENGINEERING CONSULTING GROUP CHENGDU RESEARCH HYDROELECTRIC INVESTIGATION DESIGN AND INSTITUTE
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
CHINA HYDROELECTRIC ENGINEERING CONSULTING GROUP CHENGDU RESEARCH HYDROELECTRIC INVESTIGATION DESIGN AND INSTITUTE
Filing Date
2026-05-09
Publication Date
2026-07-21

AI Technical Summary

Technical Problem

Existing directional drilling technologies suffer from problems such as heterogeneous isolated multi-source data, delayed multiple solutions for parameter inversion, passive risk assessment, and lack of intelligent closed-loop control between virtual and real data. These issues make it difficult to achieve spatiotemporal assimilation of multi-source information of surrounding rock, accurate inversion of physical parameters, and forward-looking risk control based on digital twins under complex geological conditions.

Method used

A directional drilling intelligent drilling system based on digital twin and multi-source information fusion is constructed, including a downhole sensing and execution unit, a data transmission network, and a surface intelligent decision-making platform. Multi-dimensional data is acquired through a multi-functional measurement-while-drilling module and a borehole wall panoramic imaging component. Spatiotemporal alignment is achieved using a data assimilation module, geological inversion and working condition extrapolation are performed by a digital twin model module, and the intelligent decision and control module generates the optimal drilling control strategy, forming a complete closed-loop control of sensing-inversion-decision-execution.

Benefits of technology

It achieves spatiotemporal synchronization of multi-source heterogeneous data, reduces the ambiguity of rock mass parameter inversion, improves the real-time performance and accuracy of inversion, realizes advanced extrapolation and forward-looking control driven by digital twins, and forms a closed-loop control chain of downhole sensing, data transmission, surface assimilation, twin inversion, strategy generation, and downhole execution, thereby improving the safety and efficiency of directional drilling.

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Abstract

The present application belongs to the field of deep exploration technology, and discloses a directional drilling intelligent drilling system and control method based on digital twinning and multi-source information fusion, which solves the problems of multi-source data heterogeneous island, parameter inversion multi-solution lag, passive risk evaluation and non-virtual real closed-loop intelligent control in the existing directional drilling technology. The present application collects multi-source heterogeneous data through a downhole sensing and executing unit and uploads them to a ground intelligent decision-making platform; the platform pre-processes the data, updates the digital twinning model based on extended Kalman filtering and inverts the rock mass mechanical parameters and the geological state in front of the drill bit, uses the twinning model for multi-working-condition advanced deduction, so as to obtain the optimal drilling control strategy and issue it to the downhole executing mechanism. The present application can improve the safety, trajectory accuracy and drilling efficiency of directional drilling construction and is suitable for deep exploration.
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