Digital Drilling in Holographic World

2021 ◽  
Author(s):  
Yu Fan ◽  
Jianhua Guo ◽  
Quan Cao ◽  
JingLun Ma ◽  
Jun Zhu ◽  
...  

Abstract Nowadays oil & gas industry is receiving a bulk of data than ever before from its onsite wells where may hundred miles away from operator's headquarter, which benefits us monitoring and analyzing those digital fortune in a data hub, saving a lot of expenditure and improving the efficiency compared to old-fashioned approach which requires senior engineers with rich experience working on wellsite. In this way, the oil & gas operators save money tremendously on human cost under the booming of drilling operations. While, could we do more to dig out further values from those data? Make our operations less dependable on limited resources, the senior drilling engineers, especially when the oil and gas industry face the chasm of human resources sustainability after the hit of downturn, also make the plain real-time data more intuitive and self-explanatory to the operation decision makers in an unprecedented way. What's more, could we make our drilling activities more visible and interactive? This paper is going to introduce using augmented reality technology to create an intuitive platform to integrate and present real-time operation parameters and data. Like any revolutionary method or technology, it could improve the industry efficiency in a non-negligible way, help us manage massive real-time data more effectively and efficiently. The 3D holographic projection presents dynamic models or systems based on the data stream and graphic algorithm, which evolves our industry from 2D world to 3D world, combining the reality environment with the digital world, creating a digital reflection of the real wellsite, bottom hole assembly (BHA), well trajectories, lithological layers, etc. Thanks to the visualization technologies and augmented reality, we can create a digital twin of physic world for those engineers, technicians, managers using holographic method to interact with, scale up and down, analyzing in a better awareness. In this paper, we will describe a digital drilling wellsite which is established on operator's Real Time Operation Center (RTOC)office to monitor and analyze live field operations, the operator could have an overview of their on-site operations, tracking the equipment performance, engineering parameters and downhole status to enhance the understanding and interaction with the on-going field operations. The wellbore trajectory model gives the team a superior knowledge by combining the engineering data or geological data. Not only help well placement in desired reservoir but also improve the anti-collision concept in direction drilling. This model is extreme meaningful when engineers need a discussion to optimize or change their drilling plan as it is 3D visible and able to interact with. We will continues digging out further more value of the real-time data collected from wellsite to educate us find the cost-saving ways which improve our performance and eliminate the complicated conditions that normally resulted in Non production time (NPT) event. For our oil & gas industry, we are just start to have a more adventure and prosperous journey in digitalizing transforming.

J ◽  
2021 ◽  
Vol 4 (2) ◽  
pp. 147-153
Author(s):  
Paula Morella ◽  
María Pilar Lambán ◽  
Jesús Antonio Royo ◽  
Juan Carlos Sánchez

Among the new trends in technology that have emerged through the Industry 4.0, Cyber Physical Systems (CPS) and Internet of Things (IoT) are crucial for the real-time data acquisition. This data acquisition, together with its transformation in valuable information, are indispensable for the development of real-time indicators. Moreover, real-time indicators provide companies with a competitive advantage over the competition since they enhance the calculus and speed up the decision-making and failure detection. Our research highlights the advantages of real-time data acquisition for supply chains, developing indicators that would be impossible to achieve with traditional systems, improving the accuracy of the existing ones and enhancing the real-time decision-making. Moreover, it brings out the importance of integrating technologies 4.0 in industry, in this case, CPS and IoT, and establishes the main points for a future research agenda of this topic.


Author(s):  
Bernd Resch ◽  
Andreas Wichmann ◽  
Nicolas Göll

Even though advantages of 3D visualisation of multi-temporal geo-data versus 2D approaches have been widely proven, the particular pertaining challenge of real-time visualisation of geo-data in mobile Digital Earth applications has not been thoroughly tackled so far. In the emerging field of Augmented Reality (AR), research needs comprise finding the optimal information density, the interplay between orientation data in the background and other information layers, using the appropriate graphical variables for display, or selecting real-time base data with adequate quality and suitable spatial accuracy. In this paper we present a concept for integrating real-time data into 4D (three spatial dimensions plus time) AR environments, i.e., data with “high” spatial and temporal variations. We focus on three research challenges: 1.) high-performance integration of real-time data into AR; 2.) usability design in terms of displaying spatio-temporal developments and the interaction with the application; and 3.) design considerations regarding reality vs. virtuality, visualisation complexity and information density. We validated our approach in a prototypical application and extracted several limitations and future research areas including natural feature recognition, the cross-connection of (oftentimes monolithic) AR interface developments and well-established cartographic principles, or fostering the understanding of the temporal context in dynamic 4D Augmented Reality environments.


2019 ◽  
Vol 31 (1) ◽  
pp. 265-290 ◽  
Author(s):  
Ganjar Alfian ◽  
Muhammad Fazal Ijaz ◽  
Muhammad Syafrudin ◽  
M. Alex Syaekhoni ◽  
Norma Latif Fitriyani ◽  
...  

PurposeThe purpose of this paper is to propose customer behavior analysis based on real-time data processing and association rule for digital signage-based online store (DSOS). The real-time data processing based on big data technology (such as NoSQL MongoDB and Apache Kafka) is utilized to handle the vast amount of customer behavior data.Design/methodology/approachIn order to extract customer behavior patterns, customers’ browsing history and transactional data from digital signage (DS) could be used as the input for decision making. First, the authors developed a DSOS and installed it in different locations, so that customers could have the experience of browsing and buying a product. Second, the real-time data processing system gathered customers’ browsing history and transaction data as it occurred. In addition, the authors utilized the association rule to extract useful information from customer behavior, so it may be used by the managers to efficiently enhance the service quality.FindingsFirst, as the number of customers and DS increases, the proposed system was capable of processing a gigantic amount of input data conveniently. Second, the data set showed that as the number of visit and shopping duration increases, the chance of products being purchased also increased. Third, by combining purchasing and browsing data from customers, the association rules from the frequent transaction pattern were achieved. Thus, the products will have a high possibility to be purchased if they are used as recommendations.Research limitations/implicationsThis research empirically supports the theory of association rule that frequent patterns, correlations or causal relationship found in various kinds of databases. The scope of the present study is limited to DSOS, although the findings can be interpreted and generalized in a global business scenario.Practical implicationsThe proposed system is expected to help management in taking decisions such as improving the layout of the DS and providing better product suggestions to the customer.Social implicationsThe proposed system may be utilized to promote green products to the customer, having a positive impact on sustainability.Originality/valueThe key novelty of the present study lies in system development based on big data technology to handle the enormous amounts of data as well as analyzing the customer behavior in real time in the DSOS. The real-time data processing based on big data technology (such as NoSQL MongoDB and Apache Kafka) is used to handle the vast amount of customer behavior data. In addition, the present study proposed association rule to extract useful information from customer behavior. These results can be used for promotion as well as relevant product recommendations to DSOS customers. Besides in today’s changing retail environment, analyzing the customer behavior in real time in DSOS helps to attract and retain customers more efficiently and effectively, and retailers can get a competitive advantage over their competitors.


2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Sandeep Kumar Singh ◽  
Mamata Jenamani

Purpose The purpose of this paper is to design a supply chain database schema for Cassandra to store real-time data generated by Radio Frequency IDentification technology in a traceability system. Design/methodology/approach The real-time data generated in such traceability systems are of high frequency and volume, making it difficult to handle by traditional relational database technologies. To overcome this difficulty, a NoSQL database repository based on Casandra is proposed. The efficacy of the proposed schema is compared with two such databases, document-based MongoDB and column family-based Cassandra, which are suitable for storing traceability data. Findings The proposed Cassandra-based data repository outperforms the traditional Structured Query Language-based and MongoDB system from the literature in terms of concurrent reading, and works at par with respect to writing and updating of tracing queries. Originality/value The proposed schema is able to store the real-time data generated in a supply chain with low latency. To test the performance of the Cassandra-based data repository, a test-bed is designed in the lab and supply chain operations of Indian Public Distribution System are simulated to generate data.


2016 ◽  
Vol 41 (1) ◽  
pp. 11-23
Author(s):  
Michael Takeo Magruder ◽  
Jeremy Pilcher

Michael Takeo Magruder, visual artist and researcher, discusses his digital and new media art and practice with Jeremy Pilcher, lawyer and academic, whose research engages with the intersection of art and law. Takeo's work asks viewers to question their relationship both to and within the real-time data flows generated by emerging technologies and the implications these have for archives. His art concerns the way institutions use such systems to create narratives that structure societies. This conversation discusses how Takeo's practice invites us, as individuals, to critically reflect on the implications of the stories that are both told to and about us by using gathered and distributed data.


2013 ◽  
Vol 373-375 ◽  
pp. 888-891
Author(s):  
Fang Liu ◽  
Wei Tong ◽  
Zhi Jun Qian ◽  
Yu Hong Dong

This paper introduced the laboratory model of Real-time monitor system based on the 3D Visualization for calefaction furnace, depicted the process of the model.In this paper we created a virtual environment and transport the real-time data which we collected from the locale to the virtual scene,to realize the real time monitor on the real environment.Through simulating in the lab,the effect of this system was realistic at the same time it arrived at the goal of better monitoring with better real-time.


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