The paper provides a technical overview of an operator's Real-Time Drilling(RTD)ecosystem currentlydeveloped and deployed to all US Onshore and Deepwater Gulf of Mexico rigs.It also shares best practiceswith the industry through the journey of building the RTD solution:first designing and building theinitial analytics system,then addressing significant challenges the system faces(these challenges should becommon in drilling industry,especially for operators),next enhancing the system from lessons learned,andlastly,finalizing a fully integrated and functional ecosystem to provide a one-stop solution to end users.The RTD ecosystem consists of four subsystems as shown in architecture Figure 1.(I)The StreamBaseRTD streaming system,which is the backbone of the ecosystem.It takes the real-time streaming logdata as well as other contextual well data(for example,OpenWells),processes it through analyticalmodels,generates results,and delivers them to the web-based user interface;(II)The analytics models,which include the Machine Learning(ML)/Deep Learning(DL)models,the physics-based models andthe stream analytical/statistical models;(III)The digital transformation solution,which wasdesigned toaddress contextual well data digitization issues to enable real-time physics-based modeling.Contextual welldata like bottom hole assemblies(BHAs)and casing programs are challenging to aggregate and deliver tomodels,as this data is often stored in locations across multiple systems and in various formats.The digitaltransformation applications are designed to fit into the drilling teams'workflows and collect this informationduring the course of normal engineering processes,enhancing both the engineering workflow and the datacollection process;(IV)the cloud based ML pipeline,which streamlines the original ML workflows,aswell as establishes an anomaly detection and re-training mechanism for ML models in production.All of these subsystems are fully integrated and interact with each other to function as one system,providing a one-stop solution for real-time drilling optimization and monitoring.This RTD ecosystemhas become a powerful decision support tool for the drilling operations team.While it was a significanteffort,the long term operational and engineering benefits to operators designing such a real-time drillinganalytics ecosystem far outweighs the cost and provides a solid foundation to continue pushing the historicallimitations of drilling workflow and operational efficiency during this period of rapid digital transformationin the industry.
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