The guideline explains the current use and application of data analytics and data science in the oil and gas industry. It is designed to provide guidance on how to utilize data analytics and machine learning/artificial intelligence (ML/AI) to address a given business need, resulting in value-creation.
This guideline provides descriptions of various data analytics techniques and the recommended tools for the respective techniques and a framework for understanding and a workflow for utilizing data analytical techniques to solve business problems, without requiring the reader to be a full-time statistician or data scientist professional.
It is universal in its application to Big Data challenges in the oil and gas industry and is written not only for oil and gas professionals who are beginners to Big Data techniques, but also for data professionals looking to contribute to unique oil and gas applications. Specific users could include:
- Citizen Data Scientist: a subject matter expert in engineering, operations, supply chain, planning, project management or operations that requires data insights.
- Early Career Engineer: a young professional that is looking to improve his or her career by adding a data dimension to their problem solving.
- Data Scientist Professional: a data science professional that is looking to apply his or her deep experience in data analytics by learning the unique sets of data and operational challenges of the oil and gas industry.
This document is the culmination of the efforts of ASME industry professionals in the oil and gas industry to define Big Data and its useful applications to upstream, midstream and downstream businesses.
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- 1 file , 6.2 MB