This paper reports the development and tests of an advance methodologies to predict Upstream plant risky events, such as flaring, applying an integrated framework. The core idea is to exploit Machine Learning and big data analytics techniques to…
This paper reports the development and tests of an advance methodologies to predict Upstream plant risky events, such as flaring, applying an integrated framework. The core idea is to exploit Machine Learning and big data analytics techniques to…
The democratization of artificial intelligence began with the collection of large datasets and the ability to consume them for inferences and prediction by leveraging exponentially increasing computational power. This was further enhanced by the…
This paper reports the development and tests of an advance methodologies to predict Upstream plant risky events, such as flaring, applying an integrated framework. The core idea is to exploit Machine Learning and big data analytics techniques to…
The democratization of artificial intelligence began with the collection of large datasets and the ability to consume them for inferences and prediction by leveraging exponentially increasing computational power. This was further enhanced by the…
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,…
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 democratization of artificial intelligence began with the collection of large datasets and the ability to consume them for inferences and prediction by leveraging exponentially increasing computational power. This was further enhanced by the…
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,…
This paper reports the development and tests of an advance methodologies to predict Upstream plant risky events, such as flaring, applying an integrated framework. The core idea is to exploit Machine Learning and big data analytics techniques to…
This paper reports the development and tests of an advance methodologies to predict Upstream plant risky events, such as flaring, applying an integrated framework. The core idea is to exploit Machine Learning and big data analytics techniques to…
Industrial process control systems collect a vast amount of production data, especially time-series data from various sensors in a plant. This data provides a plethora of potential use cases for AI and machine learning that can help plant operators…
Predicting impending failure of hard disk drives (HDDs) is crucial to avoid losing essential data and service downtime. However, most HDD failure prediction is being challenged by using labelled data itself to evaluate failure rate, while the fact…
Anomaly detection has to do with finding patterns in data that do not conform to an expected behavior. It has recently attracted the attention of the research community because of its real-world application. The correct detection unusual events…
Smart Grid Technology is an important part of increasing resilience and reliability of power grids. Applying Phasor Measurement Units (PMUs) to obtain synchronized phasor measurements, or synchrophasors, provides more detailed, higher fidelity data…