Gaining insights from the dense network of interrelated documents involved in E&P projects requires experience, knowledge, and awareness about the existence of the required data. This framework aims to facilitate the decision-making process while…
Gaining insights from the dense network of interrelated documents involved in E&P projects requires experience, knowledge, and awareness about the existence of the required data. This framework aims to facilitate the decision-making process while…
Two-phase gas-liquid flows are crucial to the pipeline system. Due to their complicated flow state, existing leak detection techniques are unsuitable for two-phase flow pipelines. To avoid accidents caused by a leak of pipelines, we present a…
Long short-term memory (LSTM) has been widely applied to real-time automated natural gas leak detection and localization. However, LSTM approach could not provide the interpretation that this leak position is localized instead of other positions.…
Gaining insights from the dense network of interrelated documents involved in E&P projects requires experience, knowledge, and awareness about the existence of the required data. This framework aims to facilitate the decision-making process while…
Two-phase gas-liquid flows are crucial to the pipeline system. Due to their complicated flow state, existing leak detection techniques are unsuitable for two-phase flow pipelines. To avoid accidents caused by a leak of pipelines, we present a…
Pipelines are one of the most common systems for storing and transporting petroleum products, both liquid and gaseous. Despite the durable structures, leakages can occur for many reasons, causing environmental disasters, energy waste, and, in some…
Long short-term memory (LSTM) has been widely applied to real-time automated natural gas leak detection and localization. However, LSTM approach could not provide the interpretation that this leak position is localized instead of other positions.…
Pipelines are integral components for storing and transporting liquid and gaseous petroleum products. Despite being durable structures, ruptures can still occur, resulting not only in financial losses and energy waste but, most importantly, in…
It is important for monitoring and predicting equipment failures. The existing fault prediction method has poor efficiency and accuracy on processing imbalanced data. This paper proposes a feature pattern-based LSTM method (called FLSTM, Feature…
Pipelines are one of the most common systems for storing and transporting petroleum products, both liquid and gaseous. Despite the durable structures, leakages can occur for many reasons, causing environmental disasters, energy waste, and, in some…
Two-phase gas-liquid flows are crucial to the pipeline system. Due to their complicated flow state, existing leak detection techniques are unsuitable for two-phase flow pipelines. To avoid accidents caused by a leak of pipelines, we present a…
Pipelines are integral components for storing and transporting liquid and gaseous petroleum products. Despite being durable structures, ruptures can still occur, resulting not only in financial losses and energy waste but, most importantly, in…
It is important for monitoring and predicting equipment failures. The existing fault prediction method has poor efficiency and accuracy on processing imbalanced data. This paper proposes a feature pattern-based LSTM method (called FLSTM, Feature…
Long short-term memory (LSTM) has been widely applied to real-time automated natural gas leak detection and localization. However, LSTM approach could not provide the interpretation that this leak position is localized instead of other positions.…
Pipelines are one of the most common systems for storing and transporting petroleum products, both liquid and gaseous. Despite the durable structures, leakages can occur for many reasons, causing environmental disasters, energy waste, and, in some…
Pipelines are integral components for storing and transporting liquid and gaseous petroleum products. Despite being durable structures, ruptures can still occur, resulting not only in financial losses and energy waste but, most importantly, in…
The rapid growth in data collection, storage, and transformation technologies offered new approaches that can be effectively utilized to improve traffic crash prediction. Considering the probability of traffic crash occurrence vary due to the…
It is important for monitoring and predicting equipment failures. The existing fault prediction method has poor efficiency and accuracy on processing imbalanced data. This paper proposes a feature pattern-based LSTM method (called FLSTM, Feature…
Gaining insights from the dense network of interrelated documents involved in E&P projects requires experience, knowledge, and awareness about the existence of the required data. This framework aims to facilitate the decision-making process while…
The rapid growth in data collection, storage, and transformation technologies offered new approaches that can be effectively utilized to improve traffic crash prediction. Considering the probability of traffic crash occurrence vary due to the…
Two-phase gas-liquid flows are crucial to the pipeline system. Due to their complicated flow state, existing leak detection techniques are unsuitable for two-phase flow pipelines. To avoid accidents caused by a leak of pipelines, we present a…
Long short-term memory (LSTM) has been widely applied to real-time automated natural gas leak detection and localization. However, LSTM approach could not provide the interpretation that this leak position is localized instead of other positions.…
Gaining insights from the dense network of interrelated documents involved in E&P projects requires experience, knowledge, and awareness about the existence of the required data. This framework aims to facilitate the decision-making process while…
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…
Long short-term memory (LSTM) has been widely applied to real-time automated natural gas leak detection and localization. However, LSTM approach could not provide the interpretation that this leak position is localized instead of other positions.…
Long short-term memory (LSTM) has been widely applied to real-time automated natural gas leak detection and localization. However, LSTM approach could not provide the interpretation that this leak position is localized instead of other positions.…
Understanding maritime network structure and traffic flow changes is a challenging task that must incorporate economic, energy, geopolitics, maritime transportation, and network sciences. Crude oil is the most imported energy in the world.…
Variability of renewable energy sources (RES) creates great challenges for their owners and power system operator. In recent years energy storage system is employed to mitigate the fluctuation of RESs. This paper addresses optimal decision-making of…
Energy resources have acquired a strategic significance for economic growth and social welfare of any country throughout the history. Therefore, the prediction of crude oil price fluctuation is a significant issue. In recent years, with the…
In recent years, harsh environmental conditions (lightning, wind and rain) have posed significant threats to the safe operation of long oil and gas pipelines, especially in oil and gas pipelines in other countries. The operation and emergency…
Kick is a downhole phenomenon which can lead to blowout, and so early detection is important. In addition to early detection, the need to prevent false alarm is also useful in order to minimize wastage of operation time. A major challenge in ensuring…
In cyber-physical petroleum systems (CPPS), accurate estimation of interwell connectivity is an important process to know reservoir properties comprehensively, determine water injection rate scientifically, and enhance oil recovery effectively for…
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…
In this study, we propose algorithms to predict future stock market trends based on 8 different input features, including financial technology indicators, gold prices, a gold price volatility index, crude oil price, a crude oil price volatility…
In the middle or late stage of oilfield exploitation in China, the storage speed of oil well does not match pumping speed, resulting in pumping unit in the state of “non-full pumping” or “empty pumping”, which wastes lots of electricity. This paper…
Understanding maritime network structure and traffic flow changes is a challenging task that must incorporate economic, energy, geopolitics, maritime transportation, and network sciences. Crude oil is the most imported energy in the world.…
The authors propose a time series model that predicts future values of various types of liquid cargo traffic based on long short-term memory (LSTM), a deep learning technique. Existing liquid cargo traffic prediction models are based on traditional…
Machine learning algorithms provide feasibility for crude oil price prediction. In this paper, a novel multi-hybrid predictive neural network model is proposed based on complex deep learning algorithm, which integrates empirical wavelet transform,…
This chapter initially covers the definition and main elements of artificial neural networks and how they were originally developed from the behavior of biological neurons. Then the theory behind how neural network finds the pattern between input and…
Oil has to be redistributed around the world because of their uneven distribution. Therefore, the method of accurately identifying and forecasting the risks of oil import has always been the focus of research. Thus, we re-examined the risk of oil…
Energy consumption is an important issue of global concern. Accurate energy consumption forecasting can help balance energy demand and energy production. Although there are various energy consumption forecasting methods, the forecasting accuracy…
Oil has to be redistributed around the world because of their uneven distribution. Therefore, the method of accurately identifying and forecasting the risks of oil import has always been the focus of research. Thus, we re-examined the risk of oil…