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Lessons learned from world-wide deployments of model-based real time production optimization solutions

Lessons learned from world-wide deployments of model-based r...

引用

SPE Digital Energy conference and Exhibition 2015

作者： Bakshi, Amol Uniacke, Eric Dias, Edgar Chevron Energy Technology Company Division of Chevron U.S.A. Inc. United States

ISBN: (纸本)9781510800595

Real Time Production Optimization (RTPO) solutions have been deployed in Chevron assets starting in the 2008-2009 timeframe as part of the i-field® program. These solutions provide a common platform for accessing and integrating real-time field and well performance data with predictive modeling results. RTPO is a solution in the i-field® program that encompasses all aspects of people, process, and technology, with the objective of fundamentally transforming the way highly instrumented assets of the future are monitored using the right combination of physics-based modeling and high frequency real time field data. Chevron uses the Digital Oil Field tool suite from Petroleum Experts Ltd. (Petex) for RTPO deployments. The enterprise common solution includes model-based surveillance and analysis workflows, data integration with real-time field data and well test data, and visualization interfaces. Over the past few years, RTPO solutions have been deployed to a large number of Chevron oilfield assets worldwide, each presenting its own opportunities and challenges. In this paper, we will summarize key lessons learned from our experience so far, and our vision of the future of RTPO in Chevron. Copyright 2015, Society of Petroleum Engineers.

关键词： data integration

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An Introduction to Verification of visualization Techniques

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2015年

作者： Tiago Etiene Robert M. Kirby Claudio T. Silva

ISBN: (数字)9781627058346

As we increase our reliance on computer-generated information, often using it as part of our decision-making process, we must devise tools to assess the correctness of that information. Consider, for example, software embedded on vehicles, used for simulating aircraft performance, or used in medical imaging. In those cases, software correctness is of paramount importance as there"s little room for error. Software verification is one of the tools available to attain such goals. Verification is a well known and widely studied subfield of computer science and computational science and the goal is to help us increase confidence in the software implementation by verifying that the software does what it is supposed to do. The goal of this book is to introduce the reader to software verification in the context of visualization. In the same way we became more dependent on commercial software, we have also increased our reliance on visualization software. The reason is simple: visualization is the lens through which users can understand complex data, and as such it must be verified. The explosion in our ability to amass data requires tools not only to store and analyze data, but also to visualize it. This book is comprised of six chapters. After an introduction to the goals of the book, we present a brief description of both worlds of visualization (Chapter 2) and verification (Chapter 3). We then proceed to illustrate the main steps of the verification pipeline for visualization algorithms. We focus on two classic volume visualization techniques, namely, Isosurface Extraction (Chapter 4) and Direct Volume Rendering (Chapter 5). We explain how to verify implementations of those techniques and report the latest results in the field of verification of visualization techniques. The last chapter concludes the book and highlights new research topics for the future.

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Discerning the Scientific Research Status of Harbin Engineering University Based on CiteSpaceII Software 4

Discerning the Scientific Research Status of Harbin Engineer...

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4th International conference on Computer Science and Network Technology (ICCSNT)

作者： Xu Jian-zhong Wang Ming-yang Zheng Dan Harbin Engn Univ Sch Econ & Management Harbin Peoples R China Northeast Forestry Univ Coll Informat & Comp Engn Harbin Peoples R China

ISBN: (纸本)9781467381734

In order to show the scientific status of Harbin Engineering University (HEU) in recent five years, the scientific papers published by the staff in HEU in the period of 2008-2012 were extracted out from the SCI database. These papers were processed by the CiteSpaceII software, which is a visual software for Bibliometrics. The kernel researchers, kernel fields, and the kernel institutions and countries which have close cooperation relationship with HEU were detected out. These results present important data to know the whole scientific research level and international influence of HEU. This would be helpful for the further development of the scientific research of HEU.

关键词： CiteSpaceII software Harbin Engineering University Scientific Research Level visualization analysis

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Bayesian mapping of medical data

Bayesian mapping of medical data

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International cartographic conference, CARTOCON 2014

作者： Marek, Lukáš Pászto, Vít Tuček, Pavel Department of Geoinformatics Palacky University in Olomouc Olomouc Czech Republic

ISBN: (纸本)9783319079257

Disease mapping, the visualization of disease rates and the clustering of disease data are still one of the most interesting topics in geosciences. This is because of the nature of the data, which are often purely spatial with a rich descriptive part and which are easy to combine with other data (demographic, economic, etc.). This contribution aims to present the usage of empirical Bayesian methods in disease mapping and the subsequent creation of disease maps. Bayesian methods incorporate prior knowledge about the phenomenon (or underlying processes) to provide a more accurate and easily understandable description of the situation. Empirical Bayesian procedures are used for disease rates smoothing in the case of a choropleth map. They also help to identify local clusters of more/less affected areas. The main topic of the case study in this paper is the analysis of the spatial distribution of a disease called campylobacteriosis in the Czech Republic between the years 2008 and 2012 with the usage of global empirical Bayesian estimates based on binomial distribution and local empirical Bayesian estimates based on first order queen contiguity. © Springer International Publishing Switzerland 2015.

关键词： Bayesian networks

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Extraction and visualization of wind speed in a GIS environment from a weather research and forecasting (WRF) output using python 36

Extraction and visualization of wind speed in a GIS environm...

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36th Asian conference on Remote Sensing: Fostering Resilient Growth in Asia, ACRS 2015

作者： Tolentino, Jerome T. Rejuso, Ma. Victoria Villanueva, Jara Kaye Inocencio, Loureal Camille Ang, Ma. Rosario Concepcion University of the Philippines Diliman Quezon City Metro Manila1101 Philippines

Wind is one of the rapidly developing sources of renewable energy in the Philippines. However, determining wind speed and wind pattern poses a tough challenge to developers and researchers. The Weather Research and Forecasting (WRF) model is an open source Numerical Weather Prediction (NWP) system used for determining meteorological data like wind speed in a specific area. The default format of each WRF output is in netCDF which can be viewed in a GIS environment. Even though GIS can handle large files, it will take long processing time. An alternative is to convert the netCDF file into a format that is readable by the Grid analysis and Display System (GrADS), which is an open source post-processing tool used to access, manipulate and visualize earth science data. However, creating a script for GrADS is very complex. Thus, this study developed a Python-based GUI software for extraction of wind speed using the PyGrADS library, a Python interface for GrADS. After extraction, these can be interpolated in a GIS environment to produce a raster file. The extracted and averaged wind speed data are from 2008 (La Niña), 2010 (El Niño) and 2014 of Quezon City WRF output with a domain of 1km by 1km resolution. Given the amount and number of data points, using python script in extracting and averaging wind speed is faster than doing it manually. A GIS environment can now project the extracted output because it has a smaller file compared to the raw netCDF file. It was also able to show that the output visualized in the GIS environment has a similar trend with the output of the previous NREL study. It can be concluded that this study has shown that extracting and averaging wind speed using Python is more flexible than other post-processing softwares.

关键词： Python

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Research of Large-Scale and Complex Agricultural data Classification Algorithms Based on the Spatial Variability

Research of Large-Scale and Complex Agricultural Data Classi...

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The 9th International conference on Computer and Computing Technologies in Agriculture (CCTA 2015)

作者： Hang Chen Guifen Chen Lixia Cai Yuqin Yang College of Information Technology Jilin Agricultural University Institute of Scientific and Technical Information of Jilin

ISBN: (纸本)9783319483566

In the actual classification problems, as a result of lack of clear boundary information between classification objects, that could lead to loss of classification accuracy easily. Therefore, this article from the spatial patterns of the sample properties to proceed, fuzzy clustering algorithm is proposed based on the sensitivity of attribute weights, through using the attribute weights to improve the classification capability between confusing samples, that is for researching and analysing soil nutrient spatial data with consecutive years to collect in Nongan town. Then through the analysis of the visualization technology to realize the visualization of the algorithm. Experimental results show that introducing weights portray attribute information could reduce the objective function value, and effectively alleviate the phenomenon of boundary data that cannot distinguish. Ultimately to improve the classification accuracy. Meanwhile, use of MATLAB to form visualization of three-dimensional image. The results provide a basis for to improve the accuracy of data classification and clustering analysis of large and complex agricultural data.

关键词： Large-scale and complex data Spatial variation law Fuzzy clustering Soil nutrients Sensitive attribute weights soil nutrients agricultural statistics visualization Sorting algorithm data classification large sizes MATLAB

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An information acquisition and management system for maize breeding

An information acquisition and management system for maize b...

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IEEE International conference on Software Engineering and Service Sciences (ICSESS)

作者： Sha Chen Hongju Gao Li Li Yanzhe Liu College of Information and Electrical Engineering China Agricultural University Beijing China

ISBN: (纸本)9781479983544

In order to make researchers in maize breeding gather information in field electronically, store and analyze experimental data more scientifically and efficiently, an information acquisition and management system is designed and implemented for maize breeding in this paper. The entire system includes two parts, which are desktop system and handheld system. Desktop system consists of data management module, data analysis module and databases, and is developed with Visual C++ 6.0. data management module provides functions to add, query, delete and modify data. MySQL databases are used to achieve the structural storage of maize traits that need to be observed or measured in breeding process. Handheld system runs on the handheld terminal such as a wearable PDA (Personal Digital Assistant), and is used for recording, storing and classifying the breeding information according to growth stages in field in a fast and efficient paperless way. It is developed with Visual Studio 2008 C# language on WinCE environment. data in handheld terminals can be automatically synchronized with desktop database via USB connection and Microsoft ActiveSync software. This information acquisition and management system has been put into use for over one year, and can run smoothly and stably with required convenience. In-field data can be input and stored easily via a handheld terminal at anytime and anywhere, further processed and analyzed efficiently through a desktop system, satisfying breeders with unified breeding information collection and management.

关键词： Information management Computers visualization Agriculture Visual databases

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Integration of near-surface monitoring information using ArcGIS at the Illinois Basin - Decatur Project, USA 12

Integration of near-surface monitoring information using Arc...

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12th International conference on Greenhouse Gas Control Technologies (GHGT)

作者： Korose, Christopher P. Locke, Randall A., II Blakley, Curt S. Carman, Carl H. Univ Illinois Illinois State Geol Survey Champaign IL 61820 USA

The Illinois Basin Decatur Project (IBDP) is a large-scale carbon capture and storage (CCS) demonstration injecting 1 million metric tons (1.1 million tons) of carbon dioxide into a deep saline reservoir over a period of 3 years. Near-surface site characterization and monitoring was initiated in 2008, and it includes multiple data streams that need to be periodically compiled, organized, and assessed throughout all phases of the project. A database of over 150 spatial data layers from external sources and project partners was compiled for the project using Esri's ArcGIS software. The database is used to integrate IBDP near-surface monitoring measurements into an accessible and flexible spatially-referenced framework. The geographic information systems (GIS) map database enables a wide range of information visualization and exploration. Although some limitations do exist (e.g., data management overhead, a selectively-optimized environment for temporal data representation), the IBDP GIS-based data management solution works well for map-based information visualization, as well as spatial data exploration and analysis. In particular, the automation of routine spatial analytical tasks has resulted in significant time savings when applied to mapping and analysis of near-surface field monitoring data (e.g., soil fluxes) and is an example of how a GIS framework can be applied to other data streams at IBDP and other CCS projects. (C) 2015 Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://***/licesses/by-nc-nd/3.0/). Peer-review under responsibility of the Organizing Committee of GLIGT-12

关键词： Illinois Basin IBDP CCS geologic carbon storage MVA near-surface monitoring soil CO2 flux GIS spatial data management analysis mapping automation

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Visual Models for Categorical data in Economic Research 36th

Visual Models for Categorical Data in Economic Research

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36th Annual conference of the German-Classification-Society (GfKl)

作者： Brzezinska, Justyna Univ Econ Katowice Dept Stat 1 Maja 50 PL-40287 Katowice Poland

ISBN: (纸本)9783319015958;9783319015941

This paper is concerned with the use of visualizing categorical data in qualitative data analysis (Friendly, Visualizing categorical data, SAS Press, 2000. ISBN 1-58025-660-0;Meyer et al., J. Stat. Softw., 2006;Meyer et al., vcd: Visualizing Categorical data. R package version 1.0.9, 2008). Graphical methods for qualitative data and extension using a variety of R packages will be presented. This paper outlines a general framework for visual models for categorical data. These ideas are illustrated with a variety of graphical methods for categorical data for large, multi-way contingency tables. Graphical methods are available in R software in vcd and vcdExtra library including mosaic plot, association plot, sieve plot, double-decker plot or agreement plot. These R packages include methods for the exploration of categorical data, such as fitting and graphing, plots and tests for independence or visualization techniques for log-linear models. Some graphs, e.g. mosaic display plots are well-suited for detecting patterns of association in the process of model building, others are useful in model diagnosis and graphical presentation and summaries. The use of log-linear analysis, as well as visualizing categorical data in economic research, will be presented in this paper.

关键词： Graphic methods

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The Construction of Control Chart for PM10 Functional data

The Construction of Control Chart for PM10 Functional Data

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3rd International conference on Mathematical Sciences

作者： Shaadan, Norshahida Jemain, Abdul Aziz Deni, Sayang Mohd Fac Comp & Math Sci Ctr Stat & Decis Sci Studies Uitm Shah Alam 40450 Selangor Malaysia Univ Kebangsaan Malaysia Fac Sci & Technol Sch Math Sci DELTA Bangi 43600 Selangor Malaysia

ISBN: (纸本)9780735412361

In this paper, a statistical procedure to construct a control chart for monitoring air quality (PM10) using functional data is proposed. A set of daily indices that represent the daily PM10 curves were obtained using Functional Principal Component analysis (FPCA). By means of an iterative charting procedure, a reference data set that represented a stable PM10 process was obtained. The data were then used as a reference for monitoring future data. The application of the procedure was conducted using seven-year (2004-2010) period of recorded data from the Klang air quality monitoring station located in the Klang Valley region of Peninsular Malaysia. The study showed that the control chart provided a useful visualization tool for monitoring air quality and was capable in detecting abnormality in the process system. As in the case of Klang station, the results showed that with reference to 2004-2008, the air quality (PM10) in 2010 was better than that in 2009.

关键词： Control chart PM10 air quality monitoring FPCA

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