In order to remain competitive, digital solution in upstream oil and gas industry "is not one of the option, it's the only option". Nowadays, many companies have embarked on the digital transformation journey, and striving to become a data-driven organization. Service providers and consultancy companies constantly propose their latest technology such as Advanced Analytics, Big Data and digital oil field (DOF), however, the success of these digital solution relies heavily on data quality, where companies have always struggled to ensure a high level of data quality and make their readiness towards digital transformation questionable. Real time data has become an essential tool in production surveillance, monitoring and asset optimization, it provides the engineers a breadth of view on the operational behavior of their wells and facilities. However, multiple issues arise that hinders the right data before flowing into the system such as instrument failure, bad data, wrong mapping, duplication, misleading descriptions and inconsistence in naming convention. These discrepancies will lead to low quality data being fed into the system and ultimately affect the efficiency of any deployed digital solution. Therefore, for any organization to leverage the value of their data and to unlock new opportunities the real time data needs to be well managed, governed and provided in high quality. In this paper, the approach of real time data cleansing and standardization will be addressed in detail from end to end based on an initiative conducted in one of the signature field in Peninsular Malaysia. A thorough cleansing was done from the verification of instruments onsite, P&ID to all sub systems (servers) and end up with reporting all the finding (Completeness, Validity, Uniqueness, Consistency, Timeliness, Accuracy…). Therefore, provide a real time master data management, this helped in a good understanding of the real time data flow and identifying the responsible parties. This has resulted in the development of a robust workflow accompanied by a clear RACI that can be used during the replication in other fields as well as future developments. Author believes that other operators may benefit from the proposed cleaning strategy and standardization logics to prepare for digital transformation.
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