论文信息 - Design of Intelligent Drilling System Software Framework and Data Architecture Based on MVC Pattern

Design of Intelligent Drilling System Software Framework and Data Architecture Based on MVC Pattern

Drilling system software is crucial for the complex geological drilling process due to its vital role in improving the drilling efficiency and safety. In this paper, a Model-View-Controller (MVC) pattern-based software framework and data architecture of an intelligent drilling system are proposed. First, four main functional requirements, namely, data fusion and visualization, safety assessment and efficiency calculation, efficiency and safety optimization, and coordination control have been analyzed. After that, a four-layers is established based on the above analysis and MVC pattern. Finally, a new online data architecture has been presented at the end of this paper. The proposed software framework and data architecture form a basis for the monitoring of the drilling process.

Min Wu | Weihua Cao | Chao Gan | Peilun Ouyang | Fawen Wang

[1] Geir Hareland,et al. Development of an Intelligent System for the Analysis of both Static and Real-time Oil and Gas Well Drilling Data , 2010 .

[2] Costin Cepisca,et al. Intelligent control system for monitoring drilling process , 2008 .

[3] Ole Morten Aamo,et al. Control of heave-induced pressure fluctuations in managed pressure drilling , 2012, 2012 American Control Conference (ACC).

[4] Mogens Blanke,et al. Fault diagnosis of downhole drilling incidents using adaptive observers and statistical change detection , 2015 .

[5] Manoj Khandelwal,et al. An intelligent approach to evaluate drilling performance , 2010, Neural Computing and Applications.

[6] Naren Reddy Dhansri,et al. An Intelligent Control Approach for Oil Drilling Processes , 2011, Complex Adaptive Systems.

[7] Xu Yingzhuo,et al. Research of Visualization Intelligent Decision Support System for Drilling Risk Control , 2010, 2010 Chinese Control and Decision Conference.

[8] Ole Morten Aamo,et al. Control of heave-induced pressure fluctuations in managed pressure drilling , 2012 .

[9] Lars Imsland,et al. Fault diagnosis in managed pressure drilling using nonlinear adaptive observers , 2013, 2013 European Control Conference (ECC).