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The authors have been contacted by many people in the industry lately that are incorrectly utilizing big data to produce correlations that attempt to identify operational "sweet spots". This paper will show examples and address the need to add several steps to big data before any meaningful correlation results can be obtained, mainly understanding (and this is not a comprehensive list): The sensors involved and their limitations;The errors in the placement of these sensors (e.g. hook load sensor on the deadline);The frequency of the data and how this impacts the analysis (some companies provide 10-second data);The quality of the data itself;The appropriate filtering of data to ensure apples-to-apples comparisons;The rig state must be knownUnderstanding of the physics involved.

Technological advancements continuously change in the oil and gas industry and shape drilling performance. Trends point toward increased automation at the rig but there will likely always maintain an element of human touch. By incorporating an automated drilling state detection monitoring service, best-safe-practices were identified and standardized, allowing for a significant increase in rig efficiency. A best-safe-practices initiative was implemented that included the following process: Rigorous measurement of rig activities: A third-party service carefully quality-controlled the data feed and automatically determined the rig state.Rigorous measurement of human activity: The rigs' activities were transformed into meaningful performance information on individual crews following a data classification process and aggregation of rig operations.Recognition of safe working rates: The performance data provided by the monitoring service identified the most consistent and efficient crews to help observe their methods and share with the other crews.A teamwork environment: Involvement of stakeholders to help produce actionable plans with clear accountabilitiesTransparency: Sharing of the measurements with all stakeholders, including the drilling contractor, to further improve the processSafety first: Through transparency and a no-blame culture, it was possible to identify actionable items, such as new processes and additional personnel training. The following case study focuses on the Weight to Weight (W2W) connection time during drilling operations and dissects these activities to reveal identified improvement opportunities. Efforts resulted in a savings of more than 11.75 days on a single pad of nine wells drilled by the same rig and a 45-percent improvement in overall non-drilling time.

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