Operators' Group, Rig Contractors, and OEM/Service Company Work to Solve Rig Data Quality Issues
Abstract: In the current economic climate Operators must reduce drilling costs, so they are turning to well data analytics, real-time advisory, and automation systems to make sustainable improvements (Behounek et al. 2017). Rig surface sensor data is critical to improvement; however, documented issues with consistent, reliable, quality data complicates and delays the value from these systems. The Operators Group for Data Quality (OGDQ) seeks to accelerate the adoption of standardized key measurement specifications, data… Show more
Search citation statements
Paper Sections
Citation Types
Year Published
Publication Types
Relationship
Authors
Journals
Cited by 10 publications
References 11 publications
Good directional drilling practices have a huge impact not only on drilling costs, but on improved reserves recovery, as well as on production costs such as submersible pump failures and pump rod wear. These are all helped by improving wellbore quality, lowering tortuosity, and more accurate well placement with increased percentage of the wellbore in the target zone. The very high rates of penetration being achieved today in build and hold sections require the processing and action speed of automation to supplement the directional driller’s ability to achieve these goals. In addition, there are widespread industry drives to reduce personnel at the rig site, and to automate drilling systems. A Levels of Automation Taxonomy (LOAT) was introduced by the Drilling Systems Automation (DSA) Roadmap initiative (SPE 178841). The DSA LOAT is based on incremental automation of the four cognitive functions of interaction, which are Information Acquisition, Information Analysis, Decision Making and Action Selection, and Action Implementation. Levels of human to systems interaction are described on a nine-point scale ranging from fully manual, through levels of system support for the human, through levels of automation overseen by the human, to full automation. Directional Drilling Automation systems are being progressively accepted by the drilling industry. This paper describes those systems’ progress along the cognitive functions and levels of automation defined by the LOAT. It highlights the usefulness of the LOAT to help users understand their current levels, provide a path forward, and manage expectations of potential users. Successful automation is neither an all or nothing proposition, but rather a progression to increasing levels of each cognitive function that balance desired goals for automation against the risks and uncertainties requiring human consideration. Best practices in wellbore placement are being adopted as automation is advanced; the value being demonstrated by automated directional drilling requires suppliers to implement and manage all necessary data flows on a consistent and reliable basis.Appropriate automation systems can improve cross-functional communications, increase organizational efficiency, and enhance geosteering involvement for timely target revisions and improved reservoir exposure.Automated Decision Making can improve consistency between individual directional drillers, wells, and of delivery of best practices developed by individual companies.Higher levels of automation require the involvement of Rig Control System builders, and increased acceptance and implementation of the automated decisions. Automation should not be seen as an end goal in itself, but a means to add value through appropriate application. In the case of automating directional drilling, value is being added through reduced HSE impact and overall cost efficiencies such as reduced dollars per foot and reduced dollars per barrel.
Good directional drilling practices have a huge impact not only on drilling costs, but on improved reserves recovery, as well as on production costs such as submersible pump failures and pump rod wear. These are all helped by improving wellbore quality, lowering tortuosity, and more accurate well placement with increased percentage of the wellbore in the target zone. The very high rates of penetration being achieved today in build and hold sections require the processing and action speed of automation to supplement the directional driller’s ability to achieve these goals. In addition, there are widespread industry drives to reduce personnel at the rig site, and to automate drilling systems. A Levels of Automation Taxonomy (LOAT) was introduced by the Drilling Systems Automation (DSA) Roadmap initiative (SPE 178841). The DSA LOAT is based on incremental automation of the four cognitive functions of interaction, which are Information Acquisition, Information Analysis, Decision Making and Action Selection, and Action Implementation. Levels of human to systems interaction are described on a nine-point scale ranging from fully manual, through levels of system support for the human, through levels of automation overseen by the human, to full automation. Directional Drilling Automation systems are being progressively accepted by the drilling industry. This paper describes those systems’ progress along the cognitive functions and levels of automation defined by the LOAT. It highlights the usefulness of the LOAT to help users understand their current levels, provide a path forward, and manage expectations of potential users. Successful automation is neither an all or nothing proposition, but rather a progression to increasing levels of each cognitive function that balance desired goals for automation against the risks and uncertainties requiring human consideration. Best practices in wellbore placement are being adopted as automation is advanced; the value being demonstrated by automated directional drilling requires suppliers to implement and manage all necessary data flows on a consistent and reliable basis.Appropriate automation systems can improve cross-functional communications, increase organizational efficiency, and enhance geosteering involvement for timely target revisions and improved reservoir exposure.Automated Decision Making can improve consistency between individual directional drillers, wells, and of delivery of best practices developed by individual companies.Higher levels of automation require the involvement of Rig Control System builders, and increased acceptance and implementation of the automated decisions. Automation should not be seen as an end goal in itself, but a means to add value through appropriate application. In the case of automating directional drilling, value is being added through reduced HSE impact and overall cost efficiencies such as reduced dollars per foot and reduced dollars per barrel.
For many years the aerospace and automotive industries have realized significant improvements in efficiency, performance and cost savings by simulating multiple prototype vehicle designs and control systems under various operating conditions. These same simulation techniques have now been introduced to the oilfield drilling industry and are delivering insights for more effective drilling tool designs, bottom hole assembly optimization, drilling severity minimization, dysfunction recognition and for drilling performance improvement with fewer downhole failures. Drilling is a non-linear, coupled and dynamic hydro-geomechanical process, the physics for all aspects of which must be captured to enable a robust automated drilling control process. Drill string, drilling tool and drill bit failures are frequently incorrectly blamed upon the invisible geology through which they drill. Field engineers frequently report more severe downhole vibrations at rotation speeds other than those predicted by linear frequency-based finite element critical speeds analyses. The same multi-body dynamics simulation techniques used by the automotive and aerospace industries, however, are now being applied to capture the non-linear aspects of the drilling process and provide more realistic predictions of drilling performance. Simulation validation is achieved by comparing virtual data to physical data with an implicit understanding of the uncertainties of each. Recommendations are presented for improving the usefulness and the quality of physical drilling data which simulation can then also help assure. The ultimate objective is to deliver better quality boreholes which are less costly with fewer drilling tool failures. These novel simulation techniques are enabling manufacturers to benefit from lower development costs and shorter times to market with more reliable proprietary drilling tool designs. Drilling contractors are using simulations to optimize top-drive controls and drill more effectively. Product developers are able to configure higher performing and more optimal bottom hole assemblies. Operators are able to reduce overall drilling costs with the potential benefits of higher performing drilling automation systems and greater production from better quality boreholes.
Using Simulation to Prevent Non-Productive Time
Advanced simulation techniques which have been applied successfully for some decades by the aerospace and automotive industries, are now being used to design more robust drilling tools, improve data quality, optimize bottom hole assemblies, minimize drilling severity, construct better quality boreholes, simulate the effects of drilling dysfunction and prevent non-productive time. Extensive combinations of various bottom hole assembly designs, wellbore trajectories and drilling controls are now being simulated without the risk or costs associated with the physical experimentation that is traditionally required to enable design and performance improvements. Simulation has the potential to help drill more productive wellbores with less tortuosity and reduced workover costs. Simulation also provides a virtual reality with helpful visualizations of failure mechanisms that result from drilling inefficiency. Drilling engineers often find that vibration frequencies observed using physical downhole sensors are different to frequencies predicted by finite element structural mode shape and critical speeds analyses that hypothetically permit a drill string to extend beyond its borehole diameter when in resonance and ignore non-linear damping and frequency shifts associated with wall contacts. Non-linear finite element and multi-body dynamics simulation techniques more realistically constrain the drill string to remain within the borehole and can predict actual physical amplitude and frequency responses with higher fidelity. Another significant benefit of simulation is how virtual sensors enable the measurement of dynamic forces and motions anywhere between bit and top-drive - in particular within vulnerable drill string components where physical sensors are impractical. Whenever unpredicted dynamic forces associated with drilling dysfunction are detected by physical sensors, simulation can propagate those dynamics along the drill string and provide useful insights at critical locations where physical sensors cannot be located. This paper presents various simulation use cases together with a field example of how downhole physical measurements combined with a calibrated simulation running in a timely manner could have anticipated and potentially prevented the fishing of a drilling motor that twisted off. The timeliness of drilling decisions and how the characteristics of surface and downhole physical measurements affect simulation calibration and the influence of physical data on simulation fidelity are also discussed. Definitions There is some confusion about the meaning of various terms related to drilling automation stemming from a diversity of published definitions. Sometimes the term automation itself is used to embrace only the process of parametric analysis while excluding any simulation validation and control processes. The terms digitization and digitalization are also sometimes interchanged and incorrectly used synonymously. The value derived from drilling simulation is predicated upon the assumption that the entire coupled, non-linear and dynamic hydro-thermo-geomechanical process can be modeled and that drilling severity in response to various combinations of drilling controls can be predicted with adequate fidelity. This implies that benign as well as severe dynamic drilling behaviors should each be able to be simulated in a predictable and well-behaved manner. It should be noted, however, that when a drill string component fails to operate in a normal manner, it requires a comparison of a physical measurement to its digital twin to discern that there is a drilling dysfunction which could not be predicted alone by either the physical data or by simulation. The difference between the simulated digital twin and its physical counterpart can further be exploited with the dynamic virtual characteristics of a dysfunction propagated along the drill string and assessed for their significance at critical drill string locations even where physical sensors cannot be placed. In order to assure a more consistent understanding from the terminology used in this manuscript, the following definitions (Google, Collins et al., Theys, 1999 & Theys, 2011) are adopted:
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
Contact Info
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Product
Resources
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with đź’™ for researchers
Part of the Research Solutions Family.
