The paper presents a solution to the problem of qualitative determination of actual downhole loads and drilling parameters optimization performed employing a dynamic digital well model. The problem of the surface and downhole sensor’s data quality is disclosed, and a solution for an aggregated data QAQC. Described the practical approach of the methodology used to timely and systematically improve operational excellence across organizations and well construction time improvement.
The dynamic digital twin in real-time delivers data quality assurance, efficiency analysis, and the ability to define optimal parameters. The selection of drilling parameters and an increase in ROP are carried out in real-time, based on the analysis of MSE. Quality control of sensors plays a key role in the process of evaluating effective downhole loads, and in identifying the current FFs. This paper describes process automation routines and real-time dynamic digital twin benefits to evaluate downhole state, and potential hazards, and look ahead. Presented the optimized pipe connection method which yields into 40 % weight-to-weight time reduction, best applicable in intermediate and production well sections drilling and overall substantial improvement in well delivery quality and timing.
Implementation of the ecosystem with live digital twin allowed us to perform optimized connection practices and obtain great results of connection time reduction. This resulted in drill time savings while drilling 11-⅝″ section (8h) and while drilling 8-½″ section (13.5h). Out of total savings of 21h, 15h goes to savings related to connection practice optimization measures. Applied measures in drilling practice were supported by monitoring the well condition via T&D and hydraulics real-time calculations, friction factors automated determination, and selection of drilling parameters to increase in ROP are carried out based on the analysis of MSE and data quality assurance tools. Thus, the contractor was provided with reliable clues about wellbore condition and hole cleaning issues, while the smart alarm system was alerting RTOC engineers timely, therefore planned optimization was successfully put in place while non-productive time has not been induced.
This paper presents a novel approach to real-time monitoring of the well construction process using a digital ecosystem with a live dynamic digital twin. Described detailed optimized connection method for 11-⅝» and 8-½″ hole sections, was successfully implemented on contractor facilities. This method also can be modified for slim wells drilling.
geologist, wellbore design, united states government, geology, europe government, artificial intelligence, drillstring design, data quality, drilling fluids and materials, drilling fluid management & disposal