Big Data And Digital Transformationsummary⋯Three (3) Years Of Panel Discussions

Abstract

Abstract Digital data collected by the oil and gas industry supports many, if not, most of its activities. Data integrity, security, mining, analysis, and transfer are critical to the industry. Related topics such as the use and management of massive data sets ("big data"), data value and ownership, cybersecurity, cloud computing, machine learning, and virtual twin modeling and simulation represent only a small subset of the derivative uses of digital data being contemplated by the industry. Why are they important for the O&G Industry? These are imperative discussion topics for the oil and gas industry because of the potential for significant improvements in safety, asset security and environmental stewardship. The opportunity for improvements in performance, availability, efficiency and profitability demonstrated in other industries holds promise for the oil and gas industry, as well. OTC is the world forum for revealing innovations, solutions, ideas, and emerging technologies. To continue this mission, an OTC program subcommittee was formed to organize panels over a three (3) year span to discuss these topics and their relevance to the oil and gas industry. A cohesive and coordinated approach sets the path to similar efforts that tackles other critical topics to increase the knowledge base and benefit from the experience accumulated in other industries, thus avoiding mishaps. The "Big Data" panels were populated by high level executives and technologists from all sectors such as: Operators, Service Companies, Equipment Manufacturers, EPC, and Academia. Each panel was built in three sequence stages: the first to raise awareness, the second to discuss challenges and successes, and thirdly to have an overview of success case studies and the future. The 17 panelists were requested to ponder and present their view of challenging topics: What is the current level of maturity for data collection enablers (i.e., sensing, transmission, storage, transformation, and processing) in the industry? Who "owns" data? How is ownership determined, protected, and transferred? Once data has been collected and its ownership established, what we do with it? How do we extract knowledge and value from collected data to benefit the operations, gain efficiencies, and improve safety and security? What are the business propositions that sensed data collection, storage, and analysis bring to the table? How much data is gathered? How much is repeatedly stored? How much collected data is transformed into actionable knowledge (data "yield")? At what level does a data set become "big data"? What makes big data useful and unique? How important is data security? How securely data is handled now? How securely should it be handled? How effectively data is analyzed? What data analysis methods and tools should the industry be adopting that aren't now being used? This paper will summarize the development of the topics and the answers to these questions providing valuable insights to the future of Big Data and Data Analytics for the Energy Industry, strategies being implemented by major energy players, and the role and actions needed to be taken by professional societies.