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…
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…
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…
The scheduling algorithm generally only considers the factors that directly affect the computing performance, such as processor, internal and external storage, and network, but ignores the data itself. In data-intensive computing applications, data…
Through the increasing use of interconnected sensors, instrumentation, and smart machines, and the proliferation of social media and other open data, industrial operations and physical systems are generating ever increasing volumes of data of many…
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…
The paper is devoted to the assessment of the possibility of implementing Big Data techniques for processing large amount of data to identify cause-effect relationships (patterns) that precede an event and to develop proactive measures to prevent…
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…
Marine seismic data processing is investigated to monitor possible leakages from the geological Carbon storage. Due to the high importance of storage permanence, a precise leakage monitoring strategy is crucial. Advanced seismic monitoring solutions…
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…
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…
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…
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…
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…
With the continuous development of digitization and informationization, students' data generated by various kinds of application systems in colleges and universities is also accelerating. A big data environment of colleges and universities has been…
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)…
In less than a decade, there has been a tremendous evolution in the various storage solutions used to contain wellsite data in the upstream oil and gas industry. Many organizations from wellsite data management providers to the oil and gas operators…
The Oil and Gas (O&G) industry is embracing modern and intelligent digital technologies such as big data analytics, cloud services, machine learning etc. to increase productivity, enhance operations safety, reduce operation cost and mitigate adverse…
Over the past three years, the oil and gas industry has experienced its deepest downturn since the 1980s. Recovery has been slow, setting the deepwater industry at a strategic inflection point where step changes are necessary to remain competitive.…
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…
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…
The scheduling algorithm generally only considers the factors that directly affect the computing performance, such as processor, internal and external storage, and network, but ignores the data itself. In data-intensive computing applications, data…
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…
Through the increasing use of interconnected sensors, instrumentation, and smart machines, and the proliferation of social media and other open data, industrial operations and physical systems are generating ever increasing volumes of data of many…
Management of Environmental Impact Assessment (EIA) study and information for long period and complicated operation is one of challenge in brown field operation, an application to establish an efficient and effective tool for communication and…
The paper is devoted to the assessment of the possibility of implementing Big Data techniques for processing large amount of data to identify cause-effect relationships (patterns) that precede an event and to develop proactive measures to prevent…
Performance prediction is one of the important contents of oilfield development. It is also an important content affecting investment decision-making, especially for offshore oilfields with large investment. At present, most oilfields in China have…
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…
Cenovus Energy has deployed a rigorous multiphase flow assurance online solution to detect leaks and monitor hydrate formation conditions at the White Rose Field and satellite extensions 350 km east of St. John's, Newfoundland and Labrador, Canada.…
Marine seismic data processing is investigated to monitor possible leakages from the geological Carbon storage. Due to the high importance of storage permanence, a precise leakage monitoring strategy is crucial. Advanced seismic monitoring solutions…
Seismic data is one of earliest data acquired in a prospect evaluation and the data are utilized throughout the exploration and production stages of a prospect. With recent advances in the handling of big data, it is essential to re-evaluate the best…
Delivery of crude oil from Single Point Mooring (SPM) through subsea pipeline to Onshore Receiving Facility (ORF) play critical role for refinery processing and operation. The pipeline laid in seabed, connecting oil tanker to storage facility on…
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…
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…
With the continuous development of digitization and informationization, students' data generated by various kinds of application systems in colleges and universities is also accelerating. A big data environment of colleges and universities has been…
In less than a decade, there has been a tremendous evolution in the various storage solutions used to contain wellsite data in the upstream oil and gas industry. Many organizations from wellsite data management providers to the oil and gas operators…
For many years the aerospace and automotive industries have realized significant improvements in efficiency, performance and cost savings by simulating multiple prototype vehicle designs and control systems under various operating conditions. These…
The Oil and Gas (O&G) industry is embracing modern and intelligent digital technologies such as big data analytics, cloud services, machine learning etc. to increase productivity, enhance operations safety, reduce operation cost and mitigate adverse…
Over the past three years, the oil and gas industry has experienced its deepest downturn since the 1980s. Recovery has been slow, setting the deepwater industry at a strategic inflection point where step changes are necessary to remain competitive.…
Petroleum exploration and production processes typically generate enormous amounts of petro-Technical data using sub-surface and surface sensors. The acquisition, transferring, managing, and interpreting of these huge sensor data, as well as the…
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…
LPG utilization need more attention to safety aspects of human, environmental and equipment. This research aims to develop a wheeled robot which is capable of detecting LPG leaks in horizontal pipes by data acquisition via wireless internet, so that…