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…
Integrated asset modeling, application of big data, and automation are among the top emerging trends in the oil and gas industry. The value associated with such implementation projects is very closely linked with the efficient use of the project…
Accelerating the deep integration of digitalization and industrialization is an important way and inevitable for the energy industry to achieve high-quality development. Big data, artificial intelligence and other technologies are key production…
The energy data scope is very broad including oil and gas, coal, minerals, new energy, renewable and conversion energy, electricity, and others. The different volume, variety, veracity, and velocity of data have challenge to address with the energy…
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…
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…
today, multimedia database management is the most important for the new generation and specifically in big data issues for instant saving, calling and modifying operations for many types of documents as text, video and audio. A huge number of…
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…
HSE (Health, Safety, and Environment) management is one of the most concerned matters of every business, especially in petroleum Industry. Currently, analyzing the origin of accident and tracing the responsibility of accident commonly happened after…
Big data refers to store, manage, analyze, and process efficiently a huge amount of datasets and to distribute it. Recent advancements in big data technologies include data recording, storage, and processing, and now big data is used in the refinery…
In recent years, the rapid development of information science and technology is also changing the way of life of human beings. Especially with the application of advanced technologies such as big data analysis technology, digital media technology and…
This paper details the successful validation process of advanced DP (Dynamic Positioning) and power management tools and solutions through processing big data from offshore drilling operations. Along with outlining the technical details behind the…
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…
Fugitive volatile organic compound (VOC) emissions from the petroleum-refining industry constitute a complex issue in China. This problem has a wide range of implications that require comprehensive measures, including a series of critical policing…
Integrated asset modeling, application of big data, and automation are among the top emerging trends in the oil and gas industry. The value associated with such implementation projects is very closely linked with the efficient use of the project…
The traditional accounting model has obvious disadvantages: high cost, low efficiency, tedious work, and there is a large development space in the existing accounting system. This paper introduces the development process of cloud computing, and…
In the age of big data, all forms of data with increasing samples and high-dimensional characteristics are demonstrating their importance in a variety of fields, including data mining, pattern recognition, machine learning, and the Internet of Things…
At present, the big data industry is developing rapidly in many fields around the world, and it brings opportunities for the transformation and upgradation of the traditional oil industry. The whole oil business chain is of large scale, and there are…
Accelerating the deep integration of digitalization and industrialization is an important way and inevitable for the energy industry to achieve high-quality development. Big data, artificial intelligence and other technologies are key production…
In the past decade, the amount of data in the petroleum industry has increased rapidly, and the demand for data mining has continued to increase. The method of big data analysis can more scientifically guide the exploration and development, oil…
The energy data scope is very broad including oil and gas, coal, minerals, new energy, renewable and conversion energy, electricity, and others. The different volume, variety, veracity, and velocity of data have challenge to address with the energy…
This paper presents the analytics of physics-driven big data in reservoir hydrodynamic simulation and parameter optimization for EOR projects in Daqing oilfield. An application model proposed in this study enables reservoir engineers to dynamically…
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…
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…
With recent developments in data acquisition and storage techniques, there exists huge amount of available data for data-driven decision making in the Oil & Gas industry. This study explores an application of using Big Data Analytics to establish the…
today, multimedia database management is the most important for the new generation and specifically in big data issues for instant saving, calling and modifying operations for many types of documents as text, video and audio. A huge number of…
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…
In recent years, the development speed of big data related technology is extremely rapid, and it gradually penetrates into all fields of society from a more in-depth and broader perspective, which provides an objective data basis for the development…
HSE (Health, Safety, and Environment) management is one of the most concerned matters of every business, especially in petroleum Industry. Currently, analyzing the origin of accident and tracing the responsibility of accident commonly happened after…
Big data refers to store, manage, analyze, and process efficiently a huge amount of datasets and to distribute it. Recent advancements in big data technologies include data recording, storage, and processing, and now big data is used in the refinery…
In recent years, the rapid development of information science and technology is also changing the way of life of human beings. Especially with the application of advanced technologies such as big data analysis technology, digital media technology and…
This paper details the successful validation process of advanced DP (Dynamic Positioning) and power management tools and solutions through processing big data from offshore drilling operations. Along with outlining the technical details behind the…
Fugitive volatile organic compound (VOC) emissions from the petroleum-refining industry constitute a complex issue in China. This problem has a wide range of implications that require comprehensive measures, including a series of critical policing…
Non-metallic materials such as plastics and elastomers are widely used for sealing in downhole operations of the oil and gas industry. These materials are used because of their inherent elasticity and resilience over a wide range of deformation, and…
The traditional accounting model has obvious disadvantages: high cost, low efficiency, tedious work, and there is a large development space in the existing accounting system. This paper introduces the development process of cloud computing, and…
In the age of big data, all forms of data with increasing samples and high-dimensional characteristics are demonstrating their importance in a variety of fields, including data mining, pattern recognition, machine learning, and the Internet of Things…
Since the beginning of the 21st century, the geoscience research has been entering a significant transitional period with the establishment of a new knowledge system as the core and with the drive of big data as the means. It is a revolutionary leap…
At present, the big data industry is developing rapidly in many fields around the world, and it brings opportunities for the transformation and upgradation of the traditional oil industry. The whole oil business chain is of large scale, and there are…
Cloud computing has strong computing power and huge storage space. Machine learning algorithm, combining with cloud computing, makes the processing of large-scale data practical. Logistic regression algorithm is a widely popular machine…
In the past decade, the amount of data in the petroleum industry has increased rapidly, and the demand for data mining has continued to increase. The method of big data analysis can more scientifically guide the exploration and development, oil…
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…
This paper presents the analytics of physics-driven big data in reservoir hydrodynamic simulation and parameter optimization for EOR projects in Daqing oilfield. An application model proposed in this study enables reservoir engineers to dynamically…
Drilling with mud motors (positive displacement motors) dominates oilfield drilling operations due to its operational and economic advantages over conventional rotary drilling. In US land operations, whether it is a bent-motor or rotary steerable BHA…
Integrated asset modeling, application of big data, and automation are among the top emerging trends in the oil and gas industry. The value associated with such implementation projects is very closely linked with the efficient use of the project…
With recent developments in data acquisition and storage techniques, there exists huge amount of available data for data-driven decision making in the Oil & Gas industry. This study explores an application of using Big Data Analytics to establish the…
In recent years, the development speed of big data related technology is extremely rapid, and it gradually penetrates into all fields of society from a more in-depth and broader perspective, which provides an objective data basis for the development…
This work presents a set of interconnected open source big data technologies through an example case to demonstrate the processes used to generate, process, store, and consume real-time wellsite information transfer standard markup language (WITSML)…
Accelerating the deep integration of digitalization and industrialization is an important way and inevitable for the energy industry to achieve high-quality development. Big data, artificial intelligence and other technologies are key production…
Non-metallic materials such as plastics and elastomers are widely used for sealing in downhole operations of the oil and gas industry. These materials are used because of their inherent elasticity and resilience over a wide range of deformation, and…