This chapter introduces typical cases of artificial intelligence and big data application in oil and gas industry. In the upstream field, it introduces how to combine digital rock physics with big data and AI to optimize recovery efficiency. Digital…
This study explores the modernization of road-based technologies for the enhancement of mobility while also implementing safer transportation. Mobility plays a critical role in everyday life on a micro and a macro scale combined. Modernization in…
The advent of Comprehensive Two-dimensional Gas Chromatography (GC × GC) as a practical and accessible analytical tool had a considerable impact on analytical procedures associated to the so-called “omics” sciences. Specially when GC × GC is…
This paper aims to improve the predictability of aggregate oil market volatility with a substantially large macroeconomic database, including 127 macro variables. To this end, we use machine learning from both the variable selection (VS) and common…
Complexity of the construction projects vary by the domain and type of the project. Due to the interaction between different disciplines and parties, Energy and Petroleum Projects (EPP) are considered among the most complex. This complexity produces…
The importance of seismic big data exploration, especially in gas and oil industries, is indispensable. The processing of such complex data becomes more critical when its size is extremely large. These days the dispose of seismic big data over the…
With the rapid development of energy industry, more requirements are put forward for the processing of energy data. In order to extract more value from multi-source heterogeneous data, it is necessary to combine various sources and different forms of…
today, multimedia database management is the most important for the new generation and specifically in big data issues for instant saving, calling and modifying operations for many types of documents as text, video and audio. A huge number of…
The energy data scope is very broad including oil and gas, coal, minerals, new energy, renewable and conversion energy, electricity, and others. The different volume, variety, veracity, and velocity of data have challenge to address with the energy…
When under production, after harvest ‚curing and redrying, tobacco lamina also need a mellowing process in the warehouse of not less than 24 months to achieve naturally mellowy, during which certain temperature and humidity is needed. In the…
In order to ensure the safety of industrial production process, identification and early-warning of abnormal working conditions are very important. In this paper, the abnormal "foaming phenomenon" of natural gas purification desulfurization solution…
Intelligent oil and gas system is becoming more and more popular. Carbonate lithology is a crucial part of reservoir characterization. The classification of lithology is an important task in petroleum exploration and engineering since it influences…
The article notes that at present the competition in the global hydrocarbon market has intensified significantly. This is due to the complication of mining and geological conditions of occurrence of oil and gas layers, depletion of reserves in…
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…
In this paper, we propose a hybrid storage framework WukaStore, which offers a scalable, configurable and reliable big data storage service by integrating stable storage (such as Cloud storage or durable storage utilities) and volatile storage (such…
As we all know, energy helps promote Chinas social and economic growth and the improvement of peoples living standards. Therefore, the oil and gas industry has obtained important development opportunities. However, oil and gas resources are…
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…
The following contribution illustrates effects and potentials that digitalization has on the supply chain. Supply Chain Management itself is considered to be a tool for visualization, optimization and synchronization of various groups of processes…
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.…
Currently, the exponential growth of biomedical data along with the complexities of managing high dimensionality, imbalanced distribution, sparse attributes instigates a difficult challenge of effectively applying functional networks as a new…
Although modern chemical processes are highly automatic, abnormal situation management (ASM) still heavily relies on human operators. Process fault detection and diagnosis (FDD) are one of the most important issues of ASM but few FDD systems have…
This paper focuses on the present applications of big data in Chinese real estate development and marketing from the perspective of real estate enterprises. The problems in this practice for big data's application are analyzed by now. What's more,…
This chapter introduces typical cases of artificial intelligence and big data application in oil and gas industry. In the upstream field, it introduces how to combine digital rock physics with big data and AI to optimize recovery efficiency. Digital…
With new global regulations on supply chains (SCs), sustainable regulation mechanisms have become subject to controversy. The intention is to create and expand green and sustainable supply chains (SSC) to meet environmental and economic standards and…
The accurate examination of the spatial distribution of carbon emissions is critical for carbon reduction strategies. Large uncertainties still exist for previous studies which tried to simulate carbon emissions in spatial, and the resolution needs…
In the context of the survivability of a firm’s supply chain during the worldwide COVID-19 crisis, there is still much to be explored. This study employs the viable system model to conceptualize the virtual enterprise, big data, and knowledge…
People, devices, infrastructures and sensors can constantly communicate exchanging data and generating new data that trace many of these exchanges. This leads to vast volumes of data collected at ever increasing velocities and of different variety, a…
Due to the potential severity of oil and gas pipeline accidents, accurate assessments on the reliability and viability of pipelines in the petroleum industry is of paramount importance. Nevertheless, the safety factor (SF) parameter in some…
This paper reviews how upstream oil and gas organizations can rapidly dissect an expansive volume of data by taking steps to amalgamate all the data by combining the operational data and drilling rig sensor data to real-time windows using advanced…
Pipeline companies deploy a series of pipeline resource optimal configurations and efficiency enhancement strategies with the purpose of improving financial benefits. Thus far, pipeline owners and stakeholders have usually focused on efficiency…
Big data production in industrial Internet of Things (IIoT) is evident due to the massive deployment of sensors and Internet of Things (IoT) devices. However, big data processing is challenging due to limited computational, networking and storage…
Complexity of the construction projects vary by the domain and type of the project. Due to the interaction between different disciplines and parties, Energy and Petroleum Projects (EPP) are considered among the most complex. This complexity produces…
The healthcare industry may benefit from the implementation of a system that facilitates safe and efficient data transmission if business-to-business (B2B) methods were more widely adopted and used. Many aspects of healthcare, like as patient access…
Analyzing the factors that affect the energy efficiency of vehicles is crucial to the overall improvement of the environmental efficiency of the transport sector, one of the top polluting sectors at the global level. This study analyses the energy…
ABSTRACT The significance of big data analytics-powered artificial intelligence has grown in recent years. The literature indicates that big data analytics-powered artificial intelligence has the ability to enhance supply chain performance, but there…
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…
The rugged geographies, geomorphologies and complex geological environments make the explorers more challenging exploration and production (E & P). Despite challenges, many sedimentary basins, associated oil & gas fields and E & P Ventures are…
We use the Big Data paradigm, as a driving mechanism of an integrated research framework. As a case study, we consider analysing various ecological systems and their connectivity in the framework. An unknown coexistence among different species and…
This paper reviews the utilization of Big Data analytics, as an emerging trend, in the upstream and downstream oil and gas industry. Big Data or Big Data analytics refers to a new technology which can be employed to handle large datasets which…
The paper presents a brief introduction to big data and its role in healthcare applications. It is observed that the use of big data architecture and techniques are continuously assisting in managing the expeditious data growth in healthcare…
The consumption data from smart meters and complex questionnaires reveals the electricity consumers’ willingness to adapt their lifestyle to reduce or change their behaviour in electricity usage to flatten the peak in electricity consumption and…
An accurate characterization of spatial-temporal emission patterns and speciation of volatile organic compounds (VOCs) for multiple chemical mechanisms is important to improving the air quality ensemble modeling. In this study, we developed a…
In the real world of practice, data-driven supply chains have gained huge popularity in recent years. This has led operations and supply management researchers to the focus on the role of advanced information and technology, including big data.…
There are both economic and environmental urges for transition from the current outdated power grid to a sensor-embedded smart grid that monitors system stability, integrates distributed energy and schedules energy consumption for household users.…
The China sustainable development is the simultaneously three key facets, including urbanism, industrialization, and information. Building a Smart Low-carbon City is an energy strategy for the sustainable development of Chinese cities. One technology…
Water supply systems in the United States connect raw water sources to hundreds of millions of water consumers through humongous infrastructure that include approximately one million miles of buried water mains and service connections and thousands…
Advanced healthcare applications are needed in current systems. With the exponential increases in population and technology, the number of accidents and medical conditions are also drastically increasing. The demand for many types of smart technology…
Machine Learning (ML) is a powerful tool that can be used to make predictions on the future nature of data based on the past history. ML algorithms operate by building a model from input examples to make data-driven predictions or decisions for the…
In recent years, the rapid development of Internet, Internet of Things, and Cloud Computing have led to the explosive growth of data in almost every industry and business area. Big data has rapidly developed into a hot topic that attracts extensive…
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…