Digital twin is the innovation backbone of the smart manufacturing by delivering virtual representation of the real world. Aiming at constructing virtual representations of visual scenes, scene graph generation is a digital twin task that not only…
This article addresses the stabilization of chaotic characteristics in abnormal data by proposing chaotic correlation feature extraction of big data clustering based on the Internet of things. The chaotic features in big data usually show complex…
Digital twin is the innovation backbone of the smart manufacturing by delivering virtual representation of the real world. Aiming at constructing virtual representations of visual scenes, scene graph generation is a digital twin task that not only…
Oil and gas production operations are key sources of environmental pollution which exposing the people and effect the human activity in the world. Petroleum Development Oman (PDO) is the leading exploration and production oil and gas companies in the…
This article addresses the stabilization of chaotic characteristics in abnormal data by proposing chaotic correlation feature extraction of big data clustering based on the Internet of things. The chaotic features in big data usually show complex…
One comparative analysis method of English comparative literature based on big data Bayesian method has been proposed to improve the calculation accuracy of comparative analysis process of English comparative literature. Firstly, one multilayer…
Oil and gas production operations are key sources of environmental pollution which exposing the people and effect the human activity in the world. Petroleum Development Oman (PDO) is the leading exploration and production oil and gas companies in the…
One comparative analysis method of English comparative literature based on big data Bayesian method has been proposed to improve the calculation accuracy of comparative analysis process of English comparative literature. Firstly, one multilayer…
With the development of submarine oil and gas resources, people pay more and more attention to the safety of pipeline transportation. Once an oil and gas leak occurs in the submarine transportation pipeline, it will not only cause direct economic…
Digital twin is the innovation backbone of the smart manufacturing by delivering virtual representation of the real world. Aiming at constructing virtual representations of visual scenes, scene graph generation is a digital twin task that not only…
In recent years, there has been a significant increase in the quantity of data generated from monitoring technologies for subsurface operations such as permanent downhole sensors, as well as cross-hole and seismic surveys. Traditional models and…
This article addresses the stabilization of chaotic characteristics in abnormal data by proposing chaotic correlation feature extraction of big data clustering based on the Internet of things. The chaotic features in big data usually show complex…
Since leaks in high-pressure pipelines transporting crude oil can cause severe economic losses, a reliable leak risk assessment can assist in developing an effective pipeline maintenance plan and avoiding unexpected incidents. The fast and accurate…
With the development of submarine oil and gas resources, people pay more and more attention to the safety of pipeline transportation. Once an oil and gas leak occurs in the submarine transportation pipeline, it will not only cause direct economic…
Oil and gas production operations are key sources of environmental pollution which exposing the people and effect the human activity in the world. Petroleum Development Oman (PDO) is the leading exploration and production oil and gas companies in the…
Due to the lack of samples and concealed features, petroleum pipeline small leak detection is still a great challenge. In this paper, a method based on virtual sample generation (VSG) and unified feature extraction (UFE) techniques is proposed to…
In recent years, there has been a significant increase in the quantity of data generated from monitoring technologies for subsurface operations such as permanent downhole sensors, as well as cross-hole and seismic surveys. Traditional models and…
One comparative analysis method of English comparative literature based on big data Bayesian method has been proposed to improve the calculation accuracy of comparative analysis process of English comparative literature. Firstly, one multilayer…
Since leaks in high-pressure pipelines transporting crude oil can cause severe economic losses, a reliable leak risk assessment can assist in developing an effective pipeline maintenance plan and avoiding unexpected incidents. The fast and accurate…
Due to the lack of samples and concealed features, petroleum pipeline small leak detection is still a great challenge. In this paper, a method based on virtual sample generation (VSG) and unified feature extraction (UFE) techniques is proposed to…
A method for leak monitoring of metallic pipelines operating in the highly noisy environment of an oil refinery is proposed in this work, that can be utilized in industrial applications of similar nature. This method is based on evaluating a set of…
Natural gas pipeline leaks can cause serious hazards to natural gas transportation and pose considerable risks to the environment and the safety of residents. Therefore, feature extraction of pipeline signals is crucial in natural gas pipeline leak…
With the development of submarine oil and gas resources, people pay more and more attention to the safety of pipeline transportation. Once an oil and gas leak occurs in the submarine transportation pipeline, it will not only cause direct economic…
In recent years, there has been a significant increase in the quantity of data generated from monitoring technologies for subsurface operations such as permanent downhole sensors, as well as cross-hole and seismic surveys. Traditional models and…
Since leaks in high-pressure pipelines transporting crude oil can cause severe economic losses, a reliable leak risk assessment can assist in developing an effective pipeline maintenance plan and avoiding unexpected incidents. The fast and accurate…
A method for leak monitoring of metallic pipelines operating in the highly noisy environment of an oil refinery is proposed in this work, that can be utilized in industrial applications of similar nature. This method is based on evaluating a set of…
Natural gas pipeline leaks can cause serious hazards to natural gas transportation and pose considerable risks to the environment and the safety of residents. Therefore, feature extraction of pipeline signals is crucial in natural gas pipeline leak…
Due to the lack of samples and concealed features, petroleum pipeline small leak detection is still a great challenge. In this paper, a method based on virtual sample generation (VSG) and unified feature extraction (UFE) techniques is proposed to…
Digital twin is the innovation backbone of the smart manufacturing by delivering virtual representation of the real world. Aiming at constructing virtual representations of visual scenes, scene graph generation is a digital twin task that not only…
This article addresses the stabilization of chaotic characteristics in abnormal data by proposing chaotic correlation feature extraction of big data clustering based on the Internet of things. The chaotic features in big data usually show complex…
Oil and gas production operations are key sources of environmental pollution which exposing the people and effect the human activity in the world. Petroleum Development Oman (PDO) is the leading exploration and production oil and gas companies in the…
One comparative analysis method of English comparative literature based on big data Bayesian method has been proposed to improve the calculation accuracy of comparative analysis process of English comparative literature. Firstly, one multilayer…
Digital twin is the innovation backbone of the smart manufacturing by delivering virtual representation of the real world. Aiming at constructing virtual representations of visual scenes, scene graph generation is a digital twin task that not only…
This article addresses the stabilization of chaotic characteristics in abnormal data by proposing chaotic correlation feature extraction of big data clustering based on the Internet of things. The chaotic features in big data usually show complex…
Shale oil and gas have become very promising unconventional energies in recent years. To optimize operations in oil and gas production, a reservoir model is important for understanding the subsurface appropriately. Generally, sensor data, such as…
With the development of network technology, music recommendation system has also developed rapidly, and online music platform has become the first choice for people to listen to music. However, the music recommendation system also faces some…
Effective random noise attenuation is critical for subsequent processing of seismic data, such as velocity analysis, migration, and inversion. Thus, the removal of seismic random noise with an uncertainty level is meaningful. Attenuating 3-D random…
Machine learning is becoming prevalent increasingly for reservoir characteristics analysis in the petroleum industry. This investigation proposes an alternative way for evaluating interwell connectivity in oil fields utilizing machine learning. In…
The diversity of attribute categories brings certain difficulties to data feature detection. In order to improve the accuracy and efficiency of feature detection, a hybrid attribute feature detection method for power system intelligent operation and…
Aiming at the problems of low accuracy and large limitations of the current personalized course recommendation method in the educational big data environment, a personalized course recommendation method based on learner interest mining in the…
More recently, as images, memes and graphics interchange formats have dominated social feeds, typographic/infographic visual content has emerged as an important social media component. This multimodal text combines text and image, defining a novel…
There are few studies for the classification detection and dynamic multitarget detection of the targets in front of vehicles. In order to solve this problem, a dynamic multitarget detection algorithm is proposed. First, a dynamic multitarget…
Coalbed methane (CBM) is a clean energy source. The prediction of CBM production is a critical step during CBM exploitation and utilization, especially for geological well selection, engineering decision making, and production management. In past…
Pipeline leak detection has attracted great research interests for years in the energy industry. Continuous pressure monitoring is one of the most straightforward approaches in leak detection which utilizes pressure point analysis (PPA) algorithms to…
In this paper, a method for leak detection in industrial pipelines during normal operation, is proposed. An accelerometer set on the surface of the pipe was used for the data acquisition. The system, via adapting filtering detects the frequency bands…
Gas pipeline leakage will lead to great economic losses. So, the study of leak detection on gas pipelines is very important. A leak detection method based on Hilbert-Huang transform (HHT) has been proposed. First, the signal is transformed via HHT,…
Natural gas pipeline leaks can cause serious hazards to natural gas transportation and pose considerable risks to the environment and the safety of residents. Therefore, feature extraction of pipeline signals is crucial in natural gas pipeline leak…
Natural gas pipeline leaks can cause serious hazards to natural gas transportation and pose considerable risks to the environment and the safety of residents. Therefore, feature extraction of pipeline signals is crucial in natural gas pipeline leak…
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…
Reservoir numeric simulation is the most commonly used method for oilfield petroleum production forecasting, but its accuracy is based on accurate geological models and high-quality history matching. In order to overcome the shortcomings of numeric…