Smart Oilfield Technology

Du, Dianfa; Zhang, Xue; Guo, Qiaoqiao; Zhang, Bin; Zhang, Genkai

doi:10.1007/978-981-13-7127-1_63

Cited by 4 publications

(3 citation statements)

References 2 publications

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“…Using a cloud server is a modern way to handle big amounts of data with high reliability as discussed in some studies, [17]. It manages all the computing, storage, and network resources, making sure everything is well-organized and optimized, [18]. Its SQL system ensures a structured data storage approach.…”

Section: Cloud Server and Database Integrationmentioning

confidence: 99%

Development of an Intelligent Oil Field Management System based on Digital Twin and Machine Learning

Tasmurzayev,

Amangeldy,

Nurakhov

et al. 2023

Wseas Transactions on Electronics

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This article introduces an innovative approach to oil field management using digital twin technology and machine learning. A detailed experimental setup was designed using oil displacement techniques, equipped with sensors, actuators, flow meters, and solenoid valves. The experiments focused on displacing oil using water, polymer, and oil, from which valuable data was gathered. This data was pivotal in crafting a digital twin model of the oil field. Utilizing the digital twin, ML algorithms were trained to predict oil production rates, detect potential equipment malfunctions, and prevent operational issues. Our findings highlight a notable 10-15% improvement in oil production efficiency, underscoring the transformative potential of merging DT and ML in the petroleum industry.

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Section: Cloud Server and Database Integrationmentioning

confidence: 99%

Development of an Intelligent Oil Field Management System based on Digital Twin and Machine Learning

Tasmurzayev,

Amangeldy,

Nurakhov

et al. 2023

Wseas Transactions on Electronics

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“…In the context of Industry 4.0, oilfield industries call for efficient and cost-effective oil production. In the operation and management of the oilfield, a new concept called the "smart oilfield" is introduced [8], which is based on big data, the internet of things, and other technologies to automatically measure, analyze, and optimize oil production [9,10]. Recently, some companies with a strategic vision, such as Shell's NaKika Field [11], Xinjiang Oilfield [12], and Schlumberger's Haradh Smart Oilfield [13], have already started construction of smart oilfields.…”

Section: Introductionmentioning

confidence: 99%

Heterogeneously Integrated Multicore Fibers for Smart Oilfield Applications

et al. 2023

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In the context of Industry 4.0, the smart oilfield is introduced, which relies on large-scale information exchange among various parts, and there is an urgent need for special fiber links for both increased data transmission capacity and high-sensitivity distributed sensing. Multicore fibers can be expected to play a critical role, in the parts of cores that are responsible for data transmission, while others are used for sensing. In this paper, we propose a heterogeneously integrated seven-core fiber for interconnection and awareness applications in smart oilfields, which could not only support digital and analog signal transmission but could also measure temperature and vibration. The core for digital signal transmission has a low differential mode group delay of 10 ps/km over the C-band, and the crosstalk between adjacent cores is lower than −55 dB/km at the pitch of 50 μm. A 25-Gbaud transmission over 50 km is simulated. Each core for analog signal transmission has a large effective area of 172 μm2 to suppress the nonlinear effect due to the watt-scale input power. The proposed heterogeneously multicore fiber exhibits great potential to be applied in smart oilfields, meeting the demand for efficient and cost-effective oil production.

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“…Given the fact that oil is a nonrenewable energy resource, more and more researchers begin to focus on how to increase oil production. Also, along with the development of information technology, the operation and management in oil fields are facing a new revolution [10]. Nowadays, the phrase "smart/intelligent oil fields [11]" or "oil and gas 4.0 [12]" denote the undergoing revolution in oil fields.…”

mentioning

confidence: 99%

Metaverses-Based Parallel Oil Fields in CPSS: A Framework and Methodology

Wang

Cheng

et al. 2023

IEEE Trans. Syst. Man Cybern, Syst.

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Aiming to provide a novel paradigm of oil fields, metaverses-based parallel oil fields are proposed in this article. Compared with the existing smart/intelligent oil fields in cyber-physical systems (CPS), parallel oil fields can take human factors into full consideration and expand the operation space to cyber-physical-social systems (CPSS), which can be regarded as the abstract and scientific explanation of metaverses. In the proposed parallel oil fields, there are three kinds of workers (human workers, digital workers, and robotic workers) coordinating to construct a more reliable and intelligent oil field. Furthermore, the framework and methodology of parallel oil fields are illustrated by parallel systems and the artificial systems, computational experiments, and parallel executions (ACP) approach. Based on the proposed framework, parallel oil fields are capable of generating a more trustworthy artificial system and guaranteeing the realization of the 6S (safety, security, sustainability, sensitivity, service, and smartness) goal. Finally, based on dynamometer cards, fault diagnosis of sucker rod pumping systems (SRPS) is investigated in parallel oil fields.

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Smart Oilfield Technology

Cited by 4 publications

References 2 publications

Development of an Intelligent Oil Field Management System based on Digital Twin and Machine Learning

Development of an Intelligent Oil Field Management System based on Digital Twin and Machine Learning

Heterogeneously Integrated Multicore Fibers for Smart Oilfield Applications

Metaverses-Based Parallel Oil Fields in CPSS: A Framework and Methodology

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