The article deals with issues related to the transition to digitalization of higher professional education, as well as with the widespread use of distance education technologies. The analysis of methods for monitoring the quality of education of…
Efficient operations at intersections are associated with smooth, safe, and sustainable travel at the network level. It is often challenging to prevent congestion at these locations, especially during rush hours, owing to high traffic demand and…
Big data-driven ensemble learning is explored in this paper for quantitative geological lithofacies modeling, which is an integral and challenging part of petroleum reservoir development and characterization. Quantitative lithofacies modeling…
Big data facial image is an important identity information for people. However, facial image inpainting using existing deep learning methods has some problems such as insufficient feature mining and incomplete semantic expression, leading to output…
The article deals with issues related to the transition to digitalization of higher professional education, as well as with the widespread use of distance education technologies. The analysis of methods for monitoring the quality of education of…
Efficient operations at intersections are associated with smooth, safe, and sustainable travel at the network level. It is often challenging to prevent congestion at these locations, especially during rush hours, owing to high traffic demand and…
Big data-driven ensemble learning is explored in this paper for quantitative geological lithofacies modeling, which is an integral and challenging part of petroleum reservoir development and characterization. Quantitative lithofacies modeling…
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…
In this paper, the current status and research prospect of big data and intelligent optimization methods in oilfield development were reviewed and discussed, including the basic concepts and characteristics of the techniques, the production problems…
Big data facial image is an important identity information for people. However, facial image inpainting using existing deep learning methods has some problems such as insufficient feature mining and incomplete semantic expression, leading to output…
Seismic history matching can play a key role in geological characterization and uncertainty quantification. However, challenges related to intensive computational demands and complexity restricts its application in many practical cases. This paper…
Pipelines enable the largest volume of both intra and international transportation of oil and gas and play critical roles in the energy sufficiency of countries. The biggest drawback with the use of pipelines for oil and gas transportation is the…
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…
Fluid properties are key factors for predicting single well productivity, well test interpretation and oilfield recovery prediction, which directly affect the success of ODP program design. The most accurate and direct method of acquisition is…
In this paper, the current status and research prospect of big data and intelligent optimization methods in oilfield development were reviewed and discussed, including the basic concepts and characteristics of the techniques, the production problems…
The article deals with issues related to the transition to digitalization of higher professional education, as well as with the widespread use of distance education technologies. The analysis of methods for monitoring the quality of education of…
Efficient operations at intersections are associated with smooth, safe, and sustainable travel at the network level. It is often challenging to prevent congestion at these locations, especially during rush hours, owing to high traffic demand and…
Big data-driven ensemble learning is explored in this paper for quantitative geological lithofacies modeling, which is an integral and challenging part of petroleum reservoir development and characterization. Quantitative lithofacies modeling…
Seismic history matching can play a key role in geological characterization and uncertainty quantification. However, challenges related to intensive computational demands and complexity restricts its application in many practical cases. This paper…
Pipelines enable the largest volume of both intra and international transportation of oil and gas and play critical roles in the energy sufficiency of countries. The biggest drawback with the use of pipelines for oil and gas transportation is the…
Fluid properties are key factors for predicting single well productivity, well test interpretation and oilfield recovery prediction, which directly affect the success of ODP program design. The most accurate and direct method of acquisition is…
Big data facial image is an important identity information for people. However, facial image inpainting using existing deep learning methods has some problems such as insufficient feature mining and incomplete semantic expression, leading to output…
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…
With growing worldwide consensus about the impacts of climate change, the oil and gas industry faces unprecedented pressure to minimize its carbon footprint. The biggest source of carbon emissions in the industry is the so-called fugitive emissions,…
In this paper, the current status and research prospect of big data and intelligent optimization methods in oilfield development were reviewed and discussed, including the basic concepts and characteristics of the techniques, the production problems…
Wireless sensor networks (WSN) provide a powerful solution to the task of monitoring the operational conditions of buried and non-buried pipes of different lengths and materials. Due to the limited energy stored in the sensor nodes, the use of…
As flanged pipes have a crucial role in oil and gas transportation, accidental leaks and their detection are of great importance, and represent a great concern in safety management of pipes. The present study develops an integrated approach, based on…
Seismic history matching can play a key role in geological characterization and uncertainty quantification. However, challenges related to intensive computational demands and complexity restricts its application in many practical cases. This paper…
Pipelines enable the largest volume of both intra and international transportation of oil and gas and play critical roles in the energy sufficiency of countries. The biggest drawback with the use of pipelines for oil and gas transportation is the…
Fluid properties are key factors for predicting single well productivity, well test interpretation and oilfield recovery prediction, which directly affect the success of ODP program design. The most accurate and direct method of acquisition is…
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…
With growing worldwide consensus about the impacts of climate change, the oil and gas industry faces unprecedented pressure to minimize its carbon footprint. The biggest source of carbon emissions in the industry is the so-called fugitive emissions,…
Wireless sensor networks (WSN) provide a powerful solution to the task of monitoring the operational conditions of buried and non-buried pipes of different lengths and materials. Due to the limited energy stored in the sensor nodes, the use of…
As flanged pipes have a crucial role in oil and gas transportation, accidental leaks and their detection are of great importance, and represent a great concern in safety management of pipes. The present study develops an integrated approach, based on…
Smart Fields are distinguished with two characteristics: Big Data and Real-Time access. A small smart field with only ten wells can generate more than a billion data points every year. This data is streamed in real-time while being stored in data…
Reciprocating compressors are widely used in the petroleum industry, and a small fault in reciprocating compressors may cause serious issues in operation. Monitoring and detecting potential faults help compressors to continue normal operation. This…
Due to international commitments on carbon capture and storage (CCS), an increase in CCS projects isexpected in the near future. Saline aquifers and depleted hydrocarbon reservoirs with good seals and locatedin tectonically stable zones make an…
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…
Due to international commitments on carbon capture and storage (CCS), an increase in CCS projects is expected in the near future. Saline aquifers and depleted hydrocarbon reservoirs with good seals and located in tectonically stable zones make an…
With growing worldwide consensus about the impacts of climate change, the oil and gas industry faces unprecedented pressure to minimize its carbon footprint. The biggest source of carbon emissions in the industry is the so-called fugitive emissions,…
The article deals with issues related to the transition to digitalization of higher professional education, as well as with the widespread use of distance education technologies. The analysis of methods for monitoring the quality of education of…
Efficient operations at intersections are associated with smooth, safe, and sustainable travel at the network level. It is often challenging to prevent congestion at these locations, especially during rush hours, owing to high traffic demand and…
Big data-driven ensemble learning is explored in this paper for quantitative geological lithofacies modeling, which is an integral and challenging part of petroleum reservoir development and characterization. Quantitative lithofacies modeling…
Big data facial image is an important identity information for people. However, facial image inpainting using existing deep learning methods has some problems such as insufficient feature mining and incomplete semantic expression, leading to output…
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…
In this paper, the current status and research prospect of big data and intelligent optimization methods in oilfield development were reviewed and discussed, including the basic concepts and characteristics of the techniques, the production problems…
Seismic history matching can play a key role in geological characterization and uncertainty quantification. However, challenges related to intensive computational demands and complexity restricts its application in many practical cases. This paper…
Pipelines enable the largest volume of both intra and international transportation of oil and gas and play critical roles in the energy sufficiency of countries. The biggest drawback with the use of pipelines for oil and gas transportation is the…
Fluid properties are key factors for predicting single well productivity, well test interpretation and oilfield recovery prediction, which directly affect the success of ODP program design. The most accurate and direct method of acquisition is…