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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 sensors data quality is disclosed, a solution for an aggregated data QAQC and achieved results are presented. The implementation of the digital platform and the functionality of the dynamic digital twin allowed us to improve the compliance with desired regimes, enabled ensuring the safety of technological operations, allowed us to speed up decision-making while drilling and well completion and commissioning into production. The digital ecosystem allows to timely respond and control operational parameters, to improve and accurately control ROP while minimizing drilling hazards risks and premature drill bit bits wear. The incorporated dynamic digital twin in real-time allows assuring data quality, analyzing activities efficiency, and defining the optimal drilling parameters. The selection of optimal drilling parameters and an increase in ROP are carried out in real-time, based on the analysis of specific mechanical energy. Quality control of sensors plays a key role in the process of evaluating effective weight to bit and associated loads, and in identifying the current friction factor values exhibited downhole. Further on performed trend analysis of the friction factors and respective changes in key drilling parameters allows to track and prevent critical overloads of the drill string, permits to determine the risks of downhole hazards, enables evaluation of well circulation and conditioning activities efficiency in a given interval – allows reducing invisible NPT and the risks of downhole complications. The introduction of a digital ecosystem and a dynamic digital twin allowed us to bring the well construction management process to the next level. Operational response and the decision-making process has been drastically accelerated and improved. Uncertainties associated with an expert's interpretation of drilling states, and subjectivity in the opinions on the effectiveness of processes were eliminated. The negative effect of the human factor and the resulting invisible nonproductive time was minimized. In a short period, the drilling contractor was able to integrate a single digital platform, improve key performance indicators, and involve the field personnel in the full cycle of the technological process of well construction. Field and office personnel, including the driller, can work in a single digital platform, and regardless of the current operation, do always know the true downhole loads, do see the allowable operating envelope and optimal values of the hook load, surface torque, SPP, flow rate, RPM, weight, and torque on the bit, ROP and tripping speeds. The presented method of assessing the quality of the readings of measuring devices and determining the true WOB allows us to optimize the technological parameters during actual drilling. The calculation of the specific mechanical energy is performed based on effective downhole loads transferred to the drill bit. An abnormal increase in the specific mechanical energy notifies the driller to promptly correct the parameters and restore the efficient drilling process. The friction factors are automatically determined during rotation off bottom and tripping operations. Safe corridors and the operational roadmap are re-evaluated every second and are dynamically updated according to the current state of the wellbore and depths.
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 sensors data quality is disclosed, a solution for an aggregated data QAQC and achieved results are presented. The implementation of the digital platform and the functionality of the dynamic digital twin allowed us to improve the compliance with desired regimes, enabled ensuring the safety of technological operations, allowed us to speed up decision-making while drilling and well completion and commissioning into production. The digital ecosystem allows to timely respond and control operational parameters, to improve and accurately control ROP while minimizing drilling hazards risks and premature drill bit bits wear. The incorporated dynamic digital twin in real-time allows assuring data quality, analyzing activities efficiency, and defining the optimal drilling parameters. The selection of optimal drilling parameters and an increase in ROP are carried out in real-time, based on the analysis of specific mechanical energy. Quality control of sensors plays a key role in the process of evaluating effective weight to bit and associated loads, and in identifying the current friction factor values exhibited downhole. Further on performed trend analysis of the friction factors and respective changes in key drilling parameters allows to track and prevent critical overloads of the drill string, permits to determine the risks of downhole hazards, enables evaluation of well circulation and conditioning activities efficiency in a given interval – allows reducing invisible NPT and the risks of downhole complications. The introduction of a digital ecosystem and a dynamic digital twin allowed us to bring the well construction management process to the next level. Operational response and the decision-making process has been drastically accelerated and improved. Uncertainties associated with an expert's interpretation of drilling states, and subjectivity in the opinions on the effectiveness of processes were eliminated. The negative effect of the human factor and the resulting invisible nonproductive time was minimized. In a short period, the drilling contractor was able to integrate a single digital platform, improve key performance indicators, and involve the field personnel in the full cycle of the technological process of well construction. Field and office personnel, including the driller, can work in a single digital platform, and regardless of the current operation, do always know the true downhole loads, do see the allowable operating envelope and optimal values of the hook load, surface torque, SPP, flow rate, RPM, weight, and torque on the bit, ROP and tripping speeds. The presented method of assessing the quality of the readings of measuring devices and determining the true WOB allows us to optimize the technological parameters during actual drilling. The calculation of the specific mechanical energy is performed based on effective downhole loads transferred to the drill bit. An abnormal increase in the specific mechanical energy notifies the driller to promptly correct the parameters and restore the efficient drilling process. The friction factors are automatically determined during rotation off bottom and tripping operations. Safe corridors and the operational roadmap are re-evaluated every second and are dynamically updated according to the current state of the wellbore and depths.
Beginning in the early 2000s, the industry has applied a lot of attention, effort and protocol toward drilling automation routines in the interest of advancing efficiency and consistency, and most of all, safety. The routines that have grown in maturity and gone mainstream blend data interpretation from advanced algorithms and apply actions to downhole and/or surface machines to achieve the desired outcome. Directional drilling stands our as one field that has proven successful. Well control has been pursued with less enthusiasm in the automation space. Some effort has gone into automating a segmented well control workflow. A fully closed loop automated workflow that detects and controls has not reached commercial maturity yet. A key challenge for the pursuit of a fully closed loop influx management routine is detection. The data signatures that present themselves remain difficult to interpret consistently. This may be due to the wide range of variables that influence the interpretation. The drilling fluid, reservoir fluid and pressure, and the drilling state when the influx initiates are only a few. This paper will describe and demonstrate new technology that improves upon a process used since 2014, targeting the most important step of advancing early kick detection. This new generation of algorithms and workflows reduce gain and loss detection thresholds, can enable kick tolerance reduction, and will also minimizes false alarms. As dynamic pressure management and primary well control techniques become more complex, so to, do the challenges associated with the prompt and accurate detection of gains and losses. The new algorithms and workflows have been developed to ensure compatibility with surface backpressure Managed Pressure Drilling (MPD) systems, as well other techniques such as riser annulus height control. With increasingly stringent environment regulations being implemented worldwide, it is becoming essential for drilling operations to not only detect gains and losses, but to also monitor subsea equipment to avoid unplanned releases of drilling fluid. A side benefit of accurate gain and loss detection also enables detection of such leaks from subsea equipment. The case studies presented here will focus on the results obtained while running this technology in both conventional mode, and MPD mode. Additionally, a case study will describe how the detection application is then coupled with applied backpressure MPD and previously developed work automating circulation of the influx in SPE-194089-MS, attempting to fully close the automated influx management loop. Beyond the technology, human factors remain a barrier. To break these barriers, validation under robust conditions is essential.
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.
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