Availability and Quality of Drilling Data in the Volve Dataset

Abstract

The importance of data sharing cannot be overexaggerated today, when the recent trend toward automation fundamentally reshapes the way of how operations are done in the oil industry. The emergence of real-time trend analysis softwares and digital twins led to the increase need of reliable data sources to build, test and verify the physical and data-driven models, which represent the core of these softwares. The OpenLab project at NORCE – by integrating physical and virtual drilling and well operations – is a prime example of these novel solutions. The purpose of this thesis is to provide actual field data for the OpenLab drilling simulator, so that students, researchers and industry experts can train and run simulations on virtual wellbores which are based on real well configurations.

The Volve dataset – disclosed by Equinor – provided the database for this work. Various data sources have been investigated in the drilling-related features, and both manual and automated data mining methods were developed in order to extract the required data. When the processed data were available, a web application has been developed and integrated into OpenLab. The end result enables the user to get an overview of the Volve wells with interactive visualization, and create configurations in the OpenLab drilling simulator based on actual well data. As a side-project, a browser-based application for well data management and visualization has also been created.

This thesis serves as an example of how publicly available field data combined with free educational softwares help new ideas to emerge. Hopefully the future holds similar initiatives both by the industry and by the research community. This way innovators from the academia could easily contribute to improved operational efficiency with creative and fresh ideas.