Abstract
Abstract It is widely known that data associated with oil well drilling is often noisy and otherwise of bad quality. It is also known that solutions need to draw on both people, processes and technology to make traction. However, both the severity of the matter and the complex causes of bad data are still not completely understood. In this paper we offer a new vantage point, by presenting the data quality issues as they appear in drilling operations which utilize a real-time wellbore model for supervision and decision support. We summarize experience from several pilot studies carried out by SINTEF and the Center for Integrated Operations in the Petroleum Industry, together with industry partners. We find that bad data quality is not only a cost driver, but a serious drilling hazard in its own right.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
