Baltic Dry Index (BDI) is a widely used index that measures the changes in the transportation freight rates of the dry bulk shipping market, which could also serve as an indicator of the prosperity of both general shipping market and the world…
Vortex-induced vibration (VIV) resulting lock-in phenomenon which is the vibration frequency of the structure immersed in a fluid is locked in its resonance frequencies within a flow speed range is a potential cause of vibration fatigue and/or…
This chapter initially covers the definition and main elements of artificial neural networks and how they were originally developed from the behavior of biological neurons. Then the theory behind how neural network finds the pattern between input and…
Petrochemical industry is one of the major sectors contributing to the world-wide economy and the digital transformation is urgent to enhance core competence. In general, ethylene, propylene and butadiene, which are associated with synthetic…
Crude oil price prediction is a challenging task in oil producing countries. Its price is among the most complex and tough to model because fluctuations of price of crude oil are highly irregular, nonlinear and varies dynamically with high…
Mitigating methane leakage from the natural gas system has become an increasing concern for climate change. Efficacious methane leak detection and classification can make mitigation more efficient and cost effective. Optical gas imaging (OGI) is…
This paper presents a novel methodology for volume fraction predictions in multiphase flow meters in offshore petroleum industries using gamma-ray densitometry. The algorithm that interprets spectra recorded at detectors is based on the new…
Detection and diagnosis of defects in pipelines that transmit crude oil is crucial for assuring the safety and integrity of crude oil transportation. With the development of deep learning technologies, studies have been done in the application of…
During the sequential transportation of refined oil pipelines, mixed oil in the intersection area of two different types of oil needs to be identified and cut. Therefore, prediction of the length of the mixed oil (LMO) is significant for scheduling…
With the development of Internet of Vehicles (IoV), the integration of Internet of Things (IoT) and manual vehicles becomes inevitable in Intelligent Transportation Systems (ITS). In ITS, the IoVs communicate wirelessly with other IoVs, Road Side…
Works that use point cloud avoid wasting time and cost of collection, using simulators and datasets available in the literature. In this way, there is access to an unlimited and organized amount of point clouds, an ideal setting for deep learning…
Machine learning, especially deep learning, has been extensively applied and studied in the area of machine health monitoring. For machine health monitoring systems (MHMS), major efforts have been put into designing and deploying more and more…
It is important to assess environmental impact of intelligent transportation systems, and hence developing a vehicle emission model with high accuracy has been a long-standing topic in transportation research. However, current vehicle emission models…
With the extensive electrification introduced into the shipboard power systems, the navigation routine has become more important in an electric propulsion and solar power integrated ships since various sailing paths and speeds will lead to different…
Under the increasingly stringent environmental regulations, the installed capacity of distributed renewable energy is increasing rapidly. How to fully absorb renewable energy without affecting power grid security and ensuring power quality is the key…
In this article, a bi-directional long-short term memory (BiLSTM) network algorithm combined with a support vector machine (SVM), SVM-BiLSTM, is proposed to detect faults in the Gas Station Internet of Things (GS-IoT) system. The operational process…
Phase Change Materials (PCMs) are used for thermal energy storage (TES) due to their high latent heat capacity. While inorganic PCMs have the ability to store large amounts of thermal energy (as they possess higher values of latent heat capacity)…
Reservoir characterization is a crucial step in developing the oil and gas fields. In this research, a new technique has been demonstrated for analyzing pressure transient tests conducted in oil wells using deep learning. The pressure data recorded…
Industrial automation and control systems (IACS) are tremendously employing supervisory control and data acquisition (SCADA) network. However, their integration into IACS is vulnerable to various cyber-attacks. In this article, we first present…
In this study, we propose algorithms to predict future stock market trends based on 8 different input features, including financial technology indicators, gold prices, a gold price volatility index, crude oil price, a crude oil price volatility…
Crude oil spills near oilfields, a continuous threat to the surrounding soil security and ecological environment, are attracting increased environmental monitoring and protection. There is an urgent need to improve the existing methods for…
Energy resources have acquired a strategic significance for economic growth and social welfare of any country throughout the history. Therefore, the prediction of crude oil price fluctuation is a significant issue. In recent years, with the…
In a climate-constrained world, it is crucial to reduce natural gas methane emissions, which can potentially offset the climate benefits of replacing coal with gas. Optical gas imaging (OGI) is a widely-used method to detect methane leaks, but is…
With the popularity of the deep learning model in the engineering fields, it has attracted significant research interests in the economic and finance fields. In this paper, we use the deep learning model to capture the unknown complex nonlinear…
In a climate-constrained world, it is crucial to reduce natural gas methane emissions, which can potentially offset the climate benefits of replacing coal with gas. Optical gas imaging (OGI) is a widely-used method to detect methane leaks, but is…
In the past decade, the amount of data in the petroleum industry has increased rapidly, and the demand for data mining has continued to increase. The method of big data analysis can more scientifically guide the exploration and development, oil…
Thermal Energy Storage (TES) platforms mitigate the paucity between peaks in consumption and supply, i.e., they absorb thermal energy during periods of excess supply and release thermal energy during periods of deficit. Phase change materials (PCMs)…
Phase Change Materials (PCMs) are used for thermal energy storage (TES) due to their high latent heat capacity. While inorganic PCMs have the ability to store large amounts of thermal energy (as they possess higher values of latent heat capacity)…
Industrial storage tanks are widely used in petroleum, chemical industry, metallurgy and other process industries. The use of storage tanks are important in ensuring industrial safety production and product storage. Recently, concerns are rising over…
Detection and diagnosis of defects in pipelines that transmit crude oil is crucial for assuring the safety and integrity of crude oil transportation. With the development of deep learning technologies, studies have been done in the application of…
In the past decade, the amount of data in the petroleum industry has increased rapidly, and the demand for data mining has continued to increase. The method of big data analysis can more scientifically guide the exploration and development, oil…
During the sequential transportation of refined oil pipelines, mixed oil in the intersection area of two different types of oil needs to be identified and cut. Therefore, prediction of the length of the mixed oil (LMO) is significant for scheduling…
The forecasting of the petroleum products consumption is very important as the petroleum industry directly affects the transport sector of any country and so decision making regarding import/export of these products based on consumption prediction is…
In the era of Internet of Things (IoT), huge amount of data is being produced, by humans, sensors and machines. Thus prediction, modeling and decision making, in the majority of fields, have become highly data driven. In the vast field of Energy…
Natural Gas production and transportation are at risk of Gas hydrate plugging especially when in offshore environments where temperature is low and pressure is high. These plugs can eventually block the pipeline, increase back pressure, stop…
Natural gas has been attracting increasing attentions all around the world as a relatively cleaner energy resource compared with coal and crude oil. Except for the direct consumption as fuel, electricity generation is now another…
Germany is the largest market for natural gas in the European Union, with an annual consumption of approx. 95 billion cubic meters. The German high-pressure gas pipeline network's length is roughly 40000km, which enables highly fluctuating quantities…
The key principle of physical layer security (PLS) is to permit the secure transmission of confidential data using efficient signal-processing techniques. Also, deep learning (DL) has emerged as a viable option to address various security concerns…
Pipelines are one of the most common systems for storing and transporting petroleum products, both liquid and gaseous. Despite the durable structures, leakages can occur for many reasons, causing environmental disasters, energy waste, and, in some…
Gas leaks from subsea oil and gas facilities could cause significant ocean environment damage. Such leaks can cause fire and explosion, for example, a fire on the ocean surface west of Mexico's Yucatan peninsula. Detecting a gas leak is critical in…
Pipelines are one of the most common systems for storing and transporting petroleum products, both liquid and gaseous. Despite the durable structures, leakages can occur for many reasons, causing environmental disasters, energy waste, and, in some…
Mitigating methane leakage from the natural gas system has become an increasing concern for climate change. Efficacious methane leak detection and classification can make mitigation more efficient and cost effective. Optical gas imaging (OGI) is…
Gas leaks from subsea oil and gas facilities could cause significant ocean environment damage. Such leaks can cause fire and explosion, for example, a fire on the ocean surface west of Mexico's Yucatan peninsula. Detecting a gas leak is critical in…
In a climate-constrained world, it is crucial to reduce natural gas methane emissions, which can potentially offset the climate benefits of replacing coal with gas. Optical gas imaging (OGI) is a widely-used method to detect methane leaks, but is…
Today, climate change due to global warming is a significant concern to all of us. India's rate of greenhouse gas emissions is increasing day by day, placing India in the top ten emitters in the world. Air pollution is one of the significant…
Fault diagnosis is critical for ensuring safe and stable chemical production. Correct identification of causal relationships among variables in large-scale chemical processes is a prerequisite for analyzing the root causes and propagation paths of…
Due to the extremely complex reservoirs and strong heterogeneity, deep-sea gas hydrate logging porosity calculations still have problems, which further leads to insufficient resource calculation accuracy. Logging reservoir evaluation methods based on…
This study proposes a novel data-driven crude oil price prediction methodology using Google Trends and online media text mining. Convolutional neural network (CNN) is used to automatically extract text features from online crude oil news to…
Reciprocating compressors are widely used in petroleum industry. A small fault in reciprocating compressor may cause serious issues in operation. Traditional regular maintenance and fault diagnosis solutions cannot efficiently detect potential faults…
Whether it is through crisis mapping or event simulation, Artificial Intelligence (AI) is a pioneering new method of emergency planning. It uses the analysis of information or data from deep learning to predict the evacuation routes, allocate…