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Artificial Intelligence in Exploration. Examples from Wintershall DeaNormal access

Author: T. Helbig
Event name: ProGREss'19
Session: Digital Transformation in O&G Exploration / Цифровая трансформация в ГРР
Publication date: 05 August 2019
DOI: 10.3997/2214-4609.201953110
Language: Russian
Info: Extended abstract, PDF ( 408.9Kb )
Price: € 20

Summary:
Being at the beginning of E&P value chain, exploration is a prime target for numerous digital applications. Unlike in operations or development, exploration work is usually focusing on unstructured data (reports, studies etc.), especially at the early stage. At this stage, ideation and interpretation are prevalent whereas in the other two domains modeling and engineering play a much larger role. Here, systems acting as digital advisors or cognitive search engines can be employed to reduce the time needed to come to conclusions. At later stages, big data applications and machine learning can be used to enhance the interpretation of seismic or petrophysical data. All of these technologies are commonly referenced as “Artificial Intelligence”.


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