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Intelligent Hydrocarbon Fields
KFUPM Main Campus, Dhahran, Saudi Arabia
# 5QS Subject Rankings
24 monthsProgram duration
YesScholarships
Engineering - PetroleumMain Subject Area
Program overview
Main Subject
Engineering - Petroleum
Degree
MSci
Study Level
Masters
Study Mode
On Campus
The continued digitalization of the hydrocarbon industry requires engineers to integrate new technologies and emerging tools from various disciplines and applications. This program aims at addressing this need by equipping field and reservoir engineers with...
Read more
The continued digitalization of the hydrocarbon industry requires engineers to integrate new technologies and emerging tools from various disciplines and applications. This program aims at addressing this need by equipping field and reservoir engineers with the necessary knowledge to adopt and use such advanced technologies and solutions for improved hydrocarbon monitoring, management, and production. In addition, many of skills acquired in this program are highly versatile and can be easily transferable to other industry applications such as advanced process control.
The program combines a carefully selected set of skills from different disciplines to equip the student with a solid foundation in Industry 4.0 topics and their applications in intelligent oil and gas field (i-field) management. Topics include the application of artificial intelligence for petroleum engineers and scientists (neural networks, fuzzy logic, clustering, etc.), digital communication (signal detection and enhancement, modulation, etc.), data science (handling, visualization, sampling, modeling, etc.), Cybersecurity of industrial control systems, advanced reservoir management (e.g. production optimization, project economics, from primary depletion to abandonment), smart well completion, and integrated downhole/surface reservoir monitoring and control (with computational reservoir models for optimized production control systems). The program also covers instrumentation and control network (e.g. SCADA, cluster tree and mesh networks, communication protocols, etc.), and big data analytics (smart clouds, machine learning and visualization of big data, privacy, etc.).
Read lessProgram overview
Main Subject
Engineering - Petroleum
Degree
MSci
Study Level
Masters
Study Mode
On Campus
The continued digitalization of the hydrocarbon industry requires engineers to integrate new technologies and emerging tools from various disciplines and applications. This program aims at addressing this need by equipping field and reservoir engineers with...
Read more
The continued digitalization of the hydrocarbon industry requires engineers to integrate new technologies and emerging tools from various disciplines and applications. This program aims at addressing this need by equipping field and reservoir engineers with the necessary knowledge to adopt and use such advanced technologies and solutions for improved hydrocarbon monitoring, management, and production. In addition, many of skills acquired in this program are highly versatile and can be easily transferable to other industry applications such as advanced process control.
The program combines a carefully selected set of skills from different disciplines to equip the student with a solid foundation in Industry 4.0 topics and their applications in intelligent oil and gas field (i-field) management. Topics include the application of artificial intelligence for petroleum engineers and scientists (neural networks, fuzzy logic, clustering, etc.), digital communication (signal detection and enhancement, modulation, etc.), data science (handling, visualization, sampling, modeling, etc.), Cybersecurity of industrial control systems, advanced reservoir management (e.g. production optimization, project economics, from primary depletion to abandonment), smart well completion, and integrated downhole/surface reservoir monitoring and control (with computational reservoir models for optimized production control systems). The program also covers instrumentation and control network (e.g. SCADA, cluster tree and mesh networks, communication protocols, etc.), and big data analytics (smart clouds, machine learning and visualization of big data, privacy, etc.).
Read lessAdmission Requirements
Tuition Fee
Scholarships
QS subject rankings
Subject: Engineering - Petroleum
Ranking criteria
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