Drilling systems automation depends on timely flow of accurate and relevant data from multiple sources to control equipment, machines and processes. The fragmented nature of the drilling operations business means that data must usually be shared among companies contracted to perform services, and the operator, and all companies must trust that data. This paper describes the issue of data ownership in terms of the application of drilling systems automation, and proposes solutions.

Various parties in a drilling operation measure, collect, analyze and report data gathered during the drilling operation. They take actions to control the drilling process, avoid problems and improve performance, using information derived from the data. Data is used in pre-job planning, in real-time by those operating the drilling rig and various drilling tools, as well as periodically to advise the onsite drilling team. Data flow ranges from high-frequency, low-latency response loops at the wellsite to low-frequency, high-latency response loops in remote centers.

The SPE Drilling Systems Automation Technical Section (DSATS) has identified OPC UA as the most suited communications protocol for multidirectional fast-loop control systems. In these environments, there is high likelihood that a controller from one supplier will access and use data created by another supplier.

Drilling systems automation requires structured and organized data sharing between parties. This data sharing adds value to the drilling process. A conceptual data model describes at least three classes of data generated while drilling, and all lie within the confidentiality envelope of the operator or government agency. There is data that is the property of the data generator (such as equipment condition monitoring data), data that is restricted (such as formation evaluation data), and data that is shared in an "open data pool" for the purposes of drilling systems automation. Because ownership or control means responsibility for data quality, it is important that each data generator own its contribution to the shared data pool. The data aggregator – the party managing the shared data pool – is therefore not necessarily the owner of all data in the pool, but a caretaker of that data.

This paper describes the history of data measurement, data flow and data ownership in the drilling industry. It will address data ownership issues pertaining to drilling systems automation and drilling performance improvement. A brief review of examples of data from academia and from within our own industry will assist in understanding the relationship between data ownership and intellectual property. The paper presents a data ownership and data sharing solution that provides an environment for drilling systems automation.

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