The Intelligent Field Development Plan Through Integrated Cloud Computing and Artificial Intelligence AI Solutions

2021 ◽  
Author(s):  
Samat Ramatullayev ◽  
Shi Su ◽  
Coriolan Rat ◽  
Alaa Maarouf ◽  
Monica Mihai ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Cloud Computing ◽  
History Matching ◽  
Cutting Edge ◽  
Optimization Process ◽  
Computing Technology ◽  
History Match ◽  
Field Development ◽  
Uncertainty Parameters

Abstract Brownfield field development plans (FDP) must be revisited on a regular basis to ensure the generation of production enhancement opportunities and to unlock challenging untapped reserves. However, for decades, the conventional workflows have remained largely unchanged, inefficient, and time-consuming. The aim of this paper is to demonstrate that combination of the cutting-edge cloud computing technology along with artificial intelligence (AI) and machine learning (ML) solutions enable an optimization plan to be delivered in weeks rather than months with higher confidence. During this FDP optimization process, every stage necessitates the use of smart components (AI & ML techniques) starting from reservoir/production data analytics to history match and forecast. A combined cloud computing and AI solutions are introduced. First, several static and dynamic uncertainty parameters are identified, which are inherited from static modelling and the history match. Second, the elastic cloud computing technology is harnessed to perform hundreds to thousands of history match scenarios with the uncertainty parameters in a much shorter period. Then AI techniques are applied to extract the dominant key features and determine the most likely values. During the FDP optimization process, the data liberation paved the way for intelligent well placement which identifies the "sweet spots" using a probabilistic approach, facilitating the identification and quantification of by-passed oil. The use of AI-assisted analytics revealed how the gas-oil ratio behavior of various wells drilled at various locations in the field changed over time. It also explained why this behavior was observed in one region of the reservoir when another nearby reservoir was not suffering from the same phenomenon. The cloud computing technology allowed to screen hundreds of uncertainty cases using high-resolution reservoir simulator within an hour. The results of the screening runs were fed into an AI optimizer, which produced the best possible combination of uncertainty parameters, resulting in an ensemble of history-matched cases with the lowest mismatch objective functions. We used an intuitive history matching analysis solution that can visualize mismatch quality of all wells of various parameters in an automated manner to determine the history matching quality of an ensemble of cases. Finally, the cloud ecosystem's data liberation capability enabled the implementation of an intelligent algorithm for the identification of new infill wells. The approach serves as a benchmark for optimizing FDP of any reservoir by orders of magnitude faster compared to conventional workflows. The methodology is unique in that it uses cloud computing technology and cutting-edge AI methods to create an integrated intelligent framework for FDP that generates rapid insights and reliable results, accelerates decision making, and speeds up the entire process by orders of magnitude.

Reinforcement Learning for Cloud Computing Digital Library

2014 ◽  
Vol 571-572 ◽  
pp. 105-108
Author(s):  
Lin Xu
Keyword(s):  
Artificial Intelligence ◽  
Cloud Computing ◽  
Reinforcement Learning ◽  
Digital Library ◽  
Learning Algorithms ◽  
Experimental Results ◽  
Current Status ◽  
Self Learning ◽  
New Framework

This paper proposes a new framework of combining reinforcement learning with cloud computing digital library. Unified self-learning algorithms, which includes reinforcement learning, artificial intelligence and etc, have led to many essential advances. Given the current status of highly-available models, analysts urgently desire the deployment of write-ahead logging. In this paper we examine how DNS can be applied to the investigation of superblocks, and introduce the reinforcement learning to improve the quality of current cloud computing digital library. The experimental results show that the method works more efficiency.

scholarly journals Consumer perspective of omnichannel commerce

Management ◽  
2017 ◽  
Vol 21 (2) ◽  
pp. 95-108 ◽  
Author(s):  
Dominika Kaczorowska-Spychalska
Keyword(s):  
Artificial Intelligence ◽  
Cloud Computing ◽  
Multidimensional Analysis ◽  
Computing Technology ◽  
Market Intelligence ◽  
Shopping Experience ◽  
Consumer Perspective ◽  
Positive Experiences ◽  
And Behavior

SummaryThe evolution of hypermedia space and growing saturation of the market with mobile devices, an increasing role of Big Data, which allow for multidimensional analysis of data from offline and online markets, growing popularization of solutions of Market Intelligence supported by Cloud Computing technology as well as development of potential and opportunities of adapting the Artificial Intelligence (AI) and Internet of Things (IoT) in commerce cause that customers and their experience become a major point of activity of companies/brands. Shopping experience of a buyer is an effect of multiple and multidimensional contacts, often conducted simultaneously in many channels and in the real time. It forces an increasingly growing number of challenges that companies/brands are presented with if they want to optimize a space of customer journey and have to ensure continuity, coherence and complexity of experiences for their customers. Searching or creating these benefits that customers expect and their constant development becomes a prerequisite in this situation so that variety of positive experiences resulting in customer satisfaction and happiness could be guaranteed.The paper is an attempt to verify the essence of omnichannel commerce from the consumer’s perspective. The author discusses a problem of omnichannel model while taking into consideration some elements that can influence building and intensification of buyers’ experiences and behavior in various channels of commerce. The discussion is supported with the results of own studies in that area.

Quantitative 4D Seismic Assisted History Matching Using Ensemble-Based Methods on the Vilje Field

2020 ◽  
Author(s):  
Konrad Wojnar ◽  
Jon S?trom ◽  
Tore Felix Munck ◽  
Martha Stunell ◽  
Stig Sviland-Østre ◽  
...  
Keyword(s):  
Decision Making ◽  
Seismic Data ◽  
History Matching ◽  
Reservoir Characterization ◽  
Reservoir Management ◽  
History Match ◽  
Field Development ◽  
Qualitative And Quantitative ◽  
Reservoir Models ◽  
4D Seismic

Abstract The aim of the study was to create an ensemble of equiprobable models that could be used for improving the reservoir management of the Vilje field. Qualitative and quantitative workflows were developed to systematically and efficiently screen, analyze and history match an ensemble of reservoir simulation models to production and 4D seismic data. The goal of developing the workflows is to increase the utilization of data from 4D seismic surveys for reservoir characterization. The qualitative and quantitative workflows are presented, describing their benefits and challenges. The data conditioning produced a set of history matched reservoir models which could be used in the field development decision making process. The proposed workflows allowed for identification of outlying prior and posterior models based on key features where observed data was not covered by the synthetic 4D seismic realizations. As a result, suggestions for a more robust parameterization of the ensemble were made to improve data coverage. The existing history matching workflow efficiently integrated with the quantitative 4D seismic history matching workflow allowing for the conditioning of the reservoir models to production and 4D data. Thus, the predictability of the models was improved. This paper proposes a systematic and efficient workflow using ensemble-based methods to simultaneously screen, analyze and history match production and 4D seismic data. The proposed workflow improves the usability of 4D seismic data for reservoir characterization, and in turn, for the reservoir management and the decision-making processes.

Current Applications in Health Care Communication and Technology

2021 ◽  
Vol 3 (1) ◽  
Keyword(s):  
Health Care ◽  
Cloud Computing ◽  
Social Networking ◽  
Care Setting ◽  
Online Social Network ◽  
Cost Effective ◽  
Computing Technology ◽  
Health Care Communication ◽  
Communication And Technology

Communication and technology in a health care setting is the most important tool in health promotion. Recently, cloud computing technology is used to enable cost-effective applications to facilitate communication, information sharing and record maintenance regarding health and medicine. It allows dissemination of information from facebook, which is currently the largest online social network. Combining cloud computing and social networking could allow creating health social networking system employing a human –oriented, interactive medical web and this would improve the quality of current applications in health care communication and technology.

Construction on Virtualized Environment for Digital Library Based on Cloud Computing Technology

2014 ◽  
Vol 687-691 ◽  
pp. 3019-3022 ◽  
Author(s):  
Jun Jun Liu
Keyword(s):  
Cloud Computing ◽  
Digital Library ◽  
Resource Sharing ◽  
Virtual Machines ◽  
Computing Environment ◽  
Computing Technology ◽  
Cloud Computing Environment ◽  
Key Technology ◽  
Virtualization Technology

Cloud computing technology is emerging technology in the field of information technology, and its technical advantage has brought new opportunities and challenges for the development and service of digital library in the Internet era. Virtualization is the key technology of cloud computing, and the paper discusses the virtualization of digital library in the cloud computing environment from technical level. Firstly, the paper introduced cloud computing and virtualization technology; then created a virtualized environment for digital library based on the cloud computing technology, and described the function of various levels; finally, the capacity of virtual machines appointment scheduling can be calculated according to formulas. The paper has great significance in enhancing the efficiency and quality of library service, constructing resource sharing system of digital library.

A Survey on Strategies, Trends, Economics, and Prospects of Cloud-Based Gaming

2017 ◽  
pp. 1-24
Author(s):  
Sharon Moses J. ◽  
Dhinesh Babu L. D. ◽  
Nirmala M. ◽  
M. Rajasekhara Babu ◽  
P. Venkata Krishna
Keyword(s):  
Growth Rate ◽  
Cloud Computing ◽  
Service Provider ◽  
Quality Of Experience ◽  
Computing Technology ◽  
Web Browser ◽  
Thin Client

Cloud gaming-as-a-service is emerging as one of the potential revenue generating futuristic fields with a higher growth rate. Cloud gaming service is an entertainment service that depends totally on the cloud computing technology. Cloud gaming delivers games to the gamers, anywhere at any time without any gaming specific hardware and without diminishing the gamer's quality of experience. From getting the user command to rendering the graphics, everything is processed at the gaming service provider end. The only need for the gamer is to use a thin client like web browser to access the cloud game server. In this chapter, we have detailed about the cloud game systems, cloud game services, issues in cloud gaming, economics of cloud gaming, research prospects and the evolution of cloud gaming service.

scholarly journals The Application of Artificial Intelligence Technology in Cloud Computing Environment Resources

2021 ◽  
Author(s):  
Yuan Zheng ◽  
Xiangbin Wen
Keyword(s):  
Artificial Intelligence ◽  
Cloud Computing ◽  
Service Providers ◽  
Daily Life ◽  
Cloud Service ◽  
Mobile Internet ◽  
Computing Environment ◽  
Computing Technology ◽  
Processing Technologies ◽  
Cloud Computing Environment

With the continuous innovation and development of modern computer science and mobile Internet and other information technologies, artificial intelligence (AI) is not a new thing. It has been widely studied and applied in many fields, and it is very important for people in modern society. The research fields of artificial intelligence mainly include: deep learning, natural language processing, computer vision, intelligent robot, automatic programming, data mining and so on. All kinds of industrial production and daily life will bring a very important practical significance and far-reaching influence. The rapid development and improvement of AI have effectively changed the daily life of modern people and improved work efficiency, and promoted the vigorous and healthy development of human economic and social civilization and the progress of information technology. When widely used, traditional network information and big data processing technologies are difficult to adapt to its development needs. Only by closely combining cloud computing technology with other technologies can it play a better role and give full play to AI technology and its development. The enthusiasm and promotion of related application technologies have promoted the smooth progress of AI technology and related undertakings. With the development and improvement of cloud computing technology, more and more users tend to use the cloud to work. However, a large number of cloud service failures occurred, causing huge losses for enterprises and individuals. In order to prevent damage to the interests of enterprises and individuals, cloud service providers will provide high-quality services as much as possible. This paper aims to study the application of AI technology in cloud computing environment resources, research on the indicator of reliability, and propose a cloud service reliability verification method for the infrastructure-as-a-service layer. Experimental research shows that through the reliability detection method in this paper, users can easily and quickly obtain the reliability of the purchased cloud service, and can intuitively feel whether the performance of each server meets the promised situation in the cloud service provider’s SLA.

Service-oriented analysis and design of corporate information systems

2018 ◽  
pp. 108-115
Author(s):  
N. Р. Sidorova ◽  
Yu. . Sidorov
Keyword(s):  
Artificial Intelligence ◽  
Cloud Computing ◽  
Information Systems ◽  
Cloud Services ◽  
Computing Technology ◽  
Analysis And Design ◽  
Service Oriented ◽  
Corporate Information Systems ◽  
Cloud Technologies ◽  
Corporate Information

The article deals with the development of cloud computing technology. The application of artificial intelligence methods as the main direction of development of cloud technologies is singled out. An overview of intelligent cloud services is given.

scholarly journals Sistem Informasi Manajemen Ruangan Berbasis Cloud Computing (Studi Kasus : Universitas Respati Yogyakarta)

Respati ◽  
2019 ◽  
Vol 14 (1) ◽  
Author(s):  
Lindung Siswanto
Keyword(s):  
Cloud Computing ◽  
Low Cost ◽  
Computing Technology ◽  
Management Information ◽  
Academic Activities ◽  
Important Means ◽  
Work Units ◽  
The University ◽  
Development Methods

INTISARIRuangan dalam kaitan nya untuk kegiatan akademik di Universitas Respati Yogyakarta (UNRIYO) baik itu ruangan kuliah, laboratorium atau ruangan lain yang digunakan secara bersama merupakan sarana yang penting untuk mendukung kelancaran dalam kegiatan akademik. Kegiatan akademik yang diselenggarakan oleh dosen, mahasiswa dan unit kerja lain yang dilakukan di UNRIYO seringkali terjadi hambatan yang disebabkan keterbatasan ruangan, dan hal ini tidak tertangani dengan baik karena tidak adanya monitoring dan pengaturan terhadap penggunaan ruangan. Penelitian bertujuan untuk merancang dan membangun sistem informasi manajemen ruangan dengan metode pengembangan perangkat lunak dengan SDLC didukung dengan teknologi cloud computing sebagai penyedia infrastuktur dengan kemampuannya untuk bisa disesuaikan dengan kapasistas sistem yang akan dibangun, pemeliharaan yang mudah dengan biaya rendah sehingga kuaitas layanan sistem yang diberikan dapat terjaga dengan baik. Dari hasil penelitian diharapkan dapat membantu UNRIYO khususnya dosen, mahasiswa dan unit kerja yang bertanggung jawab terhadap pengelolaan ruangan untuk dapat memonitoring serta pemanfaatan ruangan secara baik dan maksimal. Kata kunci — Sistem informasi manajemen, pemesanan ruangan, akademik, iaas, cloud computing. ABSTRACTThe room in relation to academic activities at the University of Respati Yogyakarta (UNRIYO) whether lecture rooms, laboratories or other rooms that are used together is an important means to support fluency in academic activities. Academic activities organized by lecturers, students and other work units conducted at UNRIYO often occur due to limited space constraints, and this is not handled properly because there is no monitoring and regulation of room use.The research aims to design and build a room management information system with software development methods with SDLC supported by cloud computing technology as a provider of infrastructure with the ability to be adapted to the capacity of the system to be built, easy maintenance at low cost so that the quality of service systems provided can well maintained.The results of the study are expected to help UNRIYO especially lecturers, students and work units who are responsible for the management of the room to be able to monitor and use the space properly and optimally.Keywords —  Management information systems, room reservations, academics, iaas, cloud computing.

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