Course Description

Most difficult issues regarding the upstream oil industry are data management, quantifying uncertainty in the subsurface, and risk assessment of strategies for field engineering and development. Oil and Gas industry is now in the sea of data, where the big data is collected from virtually every sensor imaginable, and this data can provide us with the ways and means to go above and beyond old school of traditional deterministic and interpretive studies. In the Big Data era, the clustering techniques, neural networks, fuzzy-logics, genetic algorithms and other heuristics are becoming the new norm for data driven modeling of all the elements of the upstream oil and gas industry. Participants to this course will receive a thorough training on the subjects covered by the seminar outline with the instructor utilizing a variety of proven adult learning teaching and facilitation techniques. 
 

Course Objectives

Upon successful completion of this course, participant will be able to:

• Perform the data mining and the fusion of data.
• Understand how to implement the Big Data Analytics to improve drilling processes.
• Appreciate Artificial neural network and its geoscience applications.
• Implement data management and data analytics for intelligent reservoir characterization.
• Effectively perform data analysis for production forecasting.
• Implement Block-chain models for Risk Management and production optimization.
• Appreciate the environmental effects of drilling activities.
• Implement techniques to control non-productive time.
• Effectively identify and monitor key performance Indicators (KPI).
• Implement real time management of well construction and optimization for Risk Management and production optimization.

Who Can Benefit

Drilling engineer, Drilling supervisor, Risk managers, and Drilling managers