The purpose of the paper is to present the implementation of FSO2 life extension program by using big data and the Industrial Internet of Things (lloT). We will explain why it was decided to implement the program and how to use big data and the…
Demand forecasting in the energy sector is essential for both countries and companies to plan their supply and demand. Agents in the highly volatile oil markets have to act fast and data-driven. In the literature, studies on oil or gasoline demand…
To simulate and predict the appropriate indices for algal blooms and petroleum pollution, this study combined remote sensing data and models of Machine Learning ML for the Aqaba Gulf’s condition. For algal blooms indication
Big data plays a major role in the learning, manipulation, and forecasting of information intelligence. Due to the imbalance of data delivery, the learning and retrieval of information from such large datasets can result in limited classification…
Multiphase flows are of paramount importance in the oil and gas industry, considering that most petroleum industries produce and transport oil and gas simultaneously. However, systematic research on pipeline leakage conveying more than one phase at a…
Multiphase flows are of paramount importance in the oil and gas industry, considering that most petroleum industries produce and transport oil and gas simultaneously. However, systematic research on pipeline leakage conveying more than one phase at a…
Multiphase flows are of paramount importance in the oil and gas industry, considering that most petroleum industries produce and transport oil and gas simultaneously. However, systematic research on pipeline leakage conveying more than one phase at a…
Oil and Gas operations are now being "datafied." Datafication in the oil industry refers to systematically extracting data from the various oilfield activities that are naturally occurring. Successful digital transformation hinges critically on an…
Oil and Gas operations are now being "datafied." Datafication in the oil industry refers to systematically extracting data from the various oilfield activities that are naturally occurring. Successful digital transformation hinges critically on an…
Oil and Gas operations are now being "datafied." Datafication in the oil industry refers to systematically extracting data from the various oilfield activities that are naturally occurring. Successful digital transformation hinges critically on an…
Oil and Gas operations are now being "datafied." Datafication in the oil industry refers to systematically extracting data from the various oilfield activities that are naturally occurring. Successful digital transformation hinges critically on an…
Oil and Gas operations are now being "datafied." Datafication in the oil industry refers to systematically extracting data from the various oilfield activities that are naturally occurring. Successful digital transformation hinges critically on an…
The energy industry is at a crossroads. Digital technological developments have the potential to change our energy supply, trade, and consumption dramatically. The new digitalization model is powered by the artificial intelligence (AI) technology.…
The current trend indicates that energy demand and supply will eventually be controlled by autonomous software that optimizes decision-making and energy distribution operations. New state-of-the-art machine learning (ML) technologies are integral in…
The rise of the damage to energy systems caused by both natural and man-made disruptive events and the connection between energy systems and socio-economic systems have motivated the study of energy system resilience. This paper conceptualizes and…
Abstract: Inception of mobile devices and applications have seen an exponential growth of data. Bandwidth limitation for cloud-hosted applications is the “Elephant in the room”. This research has designed an algorithm to address the bandwidth…
Inception of mobile devices and applications have seen an exponential growth of data. Bandwidth limitation for cloud-hosted applications is the "Elephant in the room". This research has designed an algorithm to address the bandwidth limitations by…
The construction of systems supporting spatial data has experienced great enthusiasm in the past, due to the richness of this type of data and their semantics, which can be used in the decision-making process in various fields. Thus, the problem of…
Big data with multiple parameters that affect the variation in outcome happens in stock market, mechanical processes, weather, chemical processes etc. The Principal Components Analysis, PCA, an unsupervised analysis is a simple statistical and…
Detection of small leaks in gas pipelines is an important and persistent problem in the oil and gas industry. However, the industry is beginning to investigate how tools of Machine Learning, Artificial Intelligence, Big Data, etc. can be used to…
Detection of small leaks in gas pipelines is an important and persistent problem in the oil and gas industry. However, the industry is beginning to investigate how tools of Machine Learning, Artificial Intelligence, Big Data, etc. can be used to…
Detection of small leaks in gas pipelines is an important and persistent problem in the oil and gas industry. However, the industry is beginning to investigate how tools of Machine Learning, Artificial Intelligence, Big Data, etc. can be used to…
There are various factors that contribute to the Well planning. Be it cost, complexity of the reservoir, safety measures, isolating problem areas, engineering, etc., The whole process of well analysis takes a lot of time and efforts, as the method…
There are various factors that contribute to the Well planning. Be it cost, complexity of the reservoir, safety measures, isolating problem areas, engineering, etc., The whole process of well analysis takes a lot of time and efforts, as the method…
There are various factors that contribute to the Well planning. Be it cost, complexity of the reservoir, safety measures, isolating problem areas, engineering, etc., The whole process of well analysis takes a lot of time and efforts, as the method…
With new sources of big data, it is increasingly possible to practically implement advanced freight forecasting models including activity-based and truck touring models. Such models improve upon traditional trip-based approaches by capturing freight…
as data size is growing up, cloud storage is becoming more familiar to store a significant amount of private information. Government and private organizations require transferring plenty of business files from one end to another. However, we will…
Production planning and performance management imply diverse challenges, mainly when dealing at corporate level in an integrated operating company. Production forecast considers technical capacities, available capacities, and operationally agreed…
Production planning and performance management imply diverse challenges, mainly when dealing at corporate level in an integrated operating company. Production forecast considers technical capacities, available capacities, and operationally agreed…
Production planning and performance management imply diverse challenges, mainly when dealing at corporate level in an integrated operating company. Production forecast considers technical capacities, available capacities, and operationally agreed…
Production planning and performance management imply diverse challenges, mainly when dealing at corporate level in an integrated operating company. Production forecast considers technical capacities, available capacities, and operationally agreed…
Decarbonization of the maritime transportation fuels is a primary objective of the shipping industry. Ammonia is an attractive option because of its relatively low greenhouse gas (GHG) emissions, high energy density, competitive cost, and ubiquitous…
Big data has become a major topic in many industries. Most recently, the oil and gas industry adopted a special interest in data science as a result of the increasing availability of public domains and commercial databases. Utilizing and processing…
Big data has become a major topic in many industries. Most recently, the oil and gas industry adopted a special interest in data science as a result of the increasing availability of public domains and commercial databases. Utilizing and processing…
Big data has become a major topic in many industries. Most recently, the oil and gas industry adopted a special interest in data science as a result of the increasing availability of public domains and commercial databases. Utilizing and processing…
Big data has become a major topic in many industries. Most recently, the oil and gas industry adopted a special interest in data science as a result of the increasing availability of public domains and commercial databases. Utilizing and processing…
This paper presents a workflow based on big data analytics to model the reliability of downhole Inflow Control Valves (ICVs) and predict their failures. The paper also offers economic analysis of optimum ICV stroking frequency to maintain valves…
This paper presents a workflow based on big data analytics to model the reliability of downhole Inflow Control Valves (ICVs) and predict their failures. The paper also offers economic analysis of optimum ICV stroking frequency to maintain valves…
This paper presents a workflow based on big data analytics to model the reliability of downhole Inflow Control Valves (ICVs) and predict their failures. The paper also offers economic analysis of optimum ICV stroking frequency to maintain valves…
This paper presents a workflow based on big data analytics to model the reliability of downhole Inflow Control Valves (ICVs) and predict their failures. The paper also offers economic analysis of optimum ICV stroking frequency to maintain valves…
This paper presents a workflow based on big data analytics to model the reliability of downhole Inflow Control Valves (ICVs) and predict their failures. The paper also offers economic analysis of optimum ICV stroking frequency to maintain valves…
Maintaining well integrity is one of the critical factors in the oil and gas industry. It requires close monitoring during the life cycle of the well, especially in offshore fields, to maximize the well life cycle and avoid catastrophic failure.…
Maintaining well integrity is one of the critical factors in the oil and gas industry. It requires close monitoring during the life cycle of the well, especially in offshore fields, to maximize the well life cycle and avoid catastrophic failure.…
Maintaining well integrity is one of the critical factors in the oil and gas industry. It requires close monitoring during the life cycle of the well, especially in offshore fields, to maximize the well life cycle and avoid catastrophic failure.…
Maintaining well integrity is one of the critical factors in the oil and gas industry. It requires close monitoring during the life cycle of the well, especially in offshore fields, to maximize the well life cycle and avoid catastrophic failure.…
Effective well integrity practices ensure the protection of people, facilities and the environment from the risk of uncontrolled release of formation fluids throughout the life cycle of a well, so petroleum engineers are always required to ensure…
In the past few years, big data related to healthcare has become more important, due to the abundance of data, the increasing cost of healthcare, and the privacy of healthcare. Create, analyze, and process large and complex data that cannot be…
Forecasting of oil production plays a vital role in petroleum engineering and contributes to supporting engineers in the management of petroleum reservoirs. However, reliable production forecasting is difficult to achieve, particularly in view of the…
The digitization of health care information and the rise of value-based care have paved the way to health care big data, which then encouraged the health care industry to use data analytics to make strategic business decisions. Faced with the…
Carbon neutrality is an ambitious goal that has been promulgated to be achieved on or before 2060. However, most of the current energy policies focus more on carbon emission reduction, efficiency and high penetration of renewable energy. Thus, this…