One of the most important tools for studying fluid flow behavior in oil and gas reservoirs is reservoir simulation. It is constructed based on a comprehensive geological information. A comprehensive numerical reservoir model has tens of millions of…
Billions of events (image, video, tweet, purchase, delivery, or failure) are captured in the era of Big Data and used as training data in business analytic models. But, the event relevance and the consequent effect on a target variable are difficult…
Imbalanced data become an obstacle in data mining nowadays, minority class sometimes are more important than majority class, just like in medical diagnosis, credit card fraud and etc. This paper focuses on the imbalanced data problem that adaboost…
Considered the wireless sensor network clustering structure, a new big data collecting method based on compressive sensing is proposed. The collection process is as follows: in the cluster, the sink node sets the corresponding seed vector based on…
Effective random noise attenuation is critical for subsequent processing of seismic data, such as velocity analysis, migration, and inversion. Thus, the removal of seismic random noise with an uncertainty level is meaningful. Attenuating 3-D random…
Lithology recognition is an essential part of reservoir parameter prediction. Compared to conventional algorithms, deep learning that needs a large amount of training data as support can extract features automatically. In the process of real data…
Big Data is the massive amount of data that is generated at such a high speed that is very difficult to analyze with traditional tools. Hadoop provides distributed storage and processing, to extract useful information from such huge data. On the…
Coal-geology course is one of the core courses of resource exploration engineering major in most universities of geology, mining and petroleum. In the process of teaching, we should constantly improve the optimization design of course content,…
The Internet of Things (IoT) has been widely adopted in a range of verticals, e.g., automation, health, energy, and manufacturing. Many of the applications in these sectors, such as self-driving cars and remote surgery, are critical and high stakes…
The microseismic monitoring technique is widely applied to petroleum reservoirs to understand the process of hydraulic fracturing. Geophones continuously record the microseismic events triggered by fluid injection on the Earth’s surface or in…
With the increasing of fracturing scale and displacement, the risk of engineering operation is increased because the high friction of string. Therefore, it is very important to predict the friction in fracturing operation. Used the local…
Water content of crude oil has always been an important indicator of evaluating the exploiting capacity of an oil field. Accurate rate of water content will optimize the production and decrease energy consumption. Due to the complicated working…
This paper presents an extension of a comparative study of classifier architectures for automatic fault diagnosis, with a special emphasis on the Extreme Learning Machine (ELM), with and without kernel mapping. Besides the explanation of the ELM…
This paper describes successful and cost effective design & implementation of PC-based SCADA training system for the natural gas transmission and distribution industry. The design provides robust and automated environment for centralized control of a…
The dynamics of commodity prices has become a major field of analysis in the last 20 years. Standard econometric procedures to describe the behavior of prices have not been able to provide accurate description of the real dynamics. In this paper we…
Automatic detection of workers wearing safety helmets at the construction site is essential for safe production. Aiming at the problem of low recognition rate caused by factors such as background and light in the automatic detection of safety helmets…
Industrial automation and control systems (IACS) are tremendously employing supervisory control and data acquisition (SCADA) network. However, their integration into IACS is vulnerable to various cyber-attacks. In this article, we first present…
This paper investigates the multi-objective optimal operation problem of an integrated energy system (IES) which integrates grid-connected photovoltaic (PV) generator, gas boiler, battery energy storage system, and thermal storage to satisfy energy…
Engineering geophysical prospecting is used to identify anomalous underground bodies, which are typically identified by inversion results. In recent years, machine learning has been applied to many geophysics studies, including geophysical data…
The mooring systems give stability to the floating platforms against environmental conditions, stabilizing the platform with mooring lines attached to the seabed. The mooring systems are among the main components that guarantee the safety of the…
The Internet of things (IoT) has certainly become one of the hottest technology frameworks of the year. It is deep in many industries, affecting people’s lives in all directions. The rapid development of the IoT technology accelerates the process of…
Reservoir characterization is a crucial step in developing the oil and gas fields. In this research, a new technique has been demonstrated for analyzing pressure transient tests conducted in oil wells using deep learning. The pressure data recorded…
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…
The development of Intelligent Cyber-Physical Systems (ICPSs) in virtual network environment is facing severe challenges. On the one hand, the Internet of things (IoT) based on ICPSs construction needs a large amount of reasonable network resources…
Most of the time the mechanical equipment is in normal operation state, which results in high imbalance between fault data and normal data. In addition, traditional signal processing methods rely heavily on expert experience, making it difficult for…
Mounting evidence suggests that the brain works in a Bayesian way. Probabilistic inference models based on Bayesian theory have been widely applied in human memory modeling, such as search of associative memory (SAM) and retrieving effectively from…
Space-air-ground integrated network (SAGIN) is a new type of wireless network mode. The effective management of SAGIN resources is a prerequisite for high-reliability communication. However, the storage capacity of space-air network segment is…
In industrial production, fabric products will always inevitably appear flaws due to uncontrollable factors such as production and transportation. However, there are many problems with the manual inspection methods used by manufacturers, such as low…
Traditional ground wireless communication networks cannot provide high-quality services for artificial intelligence (AI) applications such as intelligent transportation systems (ITS) due to deployment, coverage and capacity issues. The…
Works that use point cloud avoid wasting time and cost of collection, using simulators and datasets available in the literature. In this way, there is access to an unlimited and organized amount of point clouds, an ideal setting for deep learning…
Automatic detection of workers wearing safety helmets at the construction site is essential for safe production. Aiming at the problem of low recognition rate caused by factors such as background and light in the automatic detection of safety helmets…
In order to study the rule of wax deposition of Daqing oilfield crude oil in oil pipeline, an experimental unit is made by self. Based on experimental results, the relationship between the wax deposition rate and its influencing factors are…