The SPE has split the former "Management & Information" technical discipline into two new technical discplines:
- Management
- Data Science & Engineering Analytics
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- Artificial Intelligence (1)
- artificial lift solution (1)
- artificial lift system (1)
- asia government (1)
- cloud computing (1)
- data analysis technique (1)
- data mining (1)
- different data analysis technique (1)
- India government (1)
- operation artificial lift (1)
- operation full field optimization (1)
- participant (1)
- production optimization concept (1)
- rajan chokshi (1)
- significant interdependence (1)
- surface installation (1)
- technology awareness (1)
- Upstream Oil & Gas (1)
- Use case (1)
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In this hands-on course, the participants will learn some of the techniques and workflows applied to artificial lift and production while reviewing code and practicing. The focus will be on the development of data-driven models while reviewing the underlying artificial lift principles. After introducing data science and analytics techniques, the course will discuss some business use cases that are amenable to data-driven workflows. Two or three problems will be presented during the training. For each case there will be a demonstration of the solution of such a problem using a data analysis technique with Python code deployed in the Google-cloud.
Artificial Intelligence, artificial lift solution, artificial lift system, asia government, cloud computing, data analysis technique, data mining, different data analysis technique, India government, operation artificial lift, operation full field optimization, participant, production optimization concept, rajan chokshi, significant interdependence, surface installation, technology awareness, Upstream Oil & Gas, Use case
SPE Disciplines:
- Production and Well Operations > Artificial Lift Systems (1.00)
- Data Science & Engineering Analytics > Information Management and Systems > Data mining (0.41)
- Data Science & Engineering Analytics > Information Management and Systems > Artificial intelligence (0.32)
Technology:
- Information Technology > Data Science (1.00)
- Information Technology > Artificial Intelligence (1.00)
- Information Technology > Cloud Computing (0.71)
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