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4 edition of Application of DPCA to oil data pH model building and comparison of optimal CBM policies found in the catalog.

Application of DPCA to oil data pH model building and comparison of optimal CBM policies

Gao, Yan.

Application of DPCA to oil data pH model building and comparison of optimal CBM policies

by Gao, Yan.

  • 372 Want to read
  • 32 Currently reading

Published by National Library of Canada in Ottawa .
Written in English


Edition Notes

Thesis (M.A.Sc.) -- University of Toronto, 2003.

SeriesCanadian theses = -- Th`eses canadiennes
The Physical Object
FormatMicroform
Pagination1 microfiche : negative.
ID Numbers
Open LibraryOL19722837M
ISBN 100612785394
OCLC/WorldCa54081749

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Application of DPCA to oil data pH model building and comparison of optimal CBM policies by Gao, Yan. Download PDF EPUB FB2

These covariance matrices are used when applying DPCA to reduce the dimensionality of oil data. DPCA is an extension of the original PCA method applied to the matrix composed of the time-shifted data vectors (see e.g.

Ku et al. () for an application of DPCA Cited by: In this paper, we apply DPCA to a set of real oil data and use the principal components as covariates in condition-based maintenance (CBM) modeling.

The CBM model (Model 1) is then compared with the CBM model which uses raw oil data as the covariates (Model 2).Cited by: An application of DPCA to oil data for CBM modeling Article in European Journal of Operational Research (1) February with 22 Reads How we measure 'reads'.

The second method is based on vector autoregressive (VAR) modeling of CM data, DPCA, and building a proportional hazards (PH) decision model using the retained principal components as covariates. These methodologies are illustrated by an example using real oil data histories obtained from spectrometric analysis of heavy-hauler truck transmission oil samples taken at regular Cited by: 1.

PCA is applied to a simulated CBM data set and two real data sets obtained from industry: oil analysis data and vibration data. Reasonable results are obtained. This paper proposes the application of a principal components proportional hazards regression model in condition-based maintenance (CBM) by: Brillinger [22, 23]; other related applications include the construction and analysis of economic indicators [24] and volatility modeling [25].

A key point in the implementation of the DPCA method is the selection of the number of lags to be used, i.e. the number of shifted versions for each variable to include in the DPCA by: 1) model, neural network model, support vector machine model, etc.

Oil field development system is a complex multi variables non-linear dynamical systems, different predicting model has different characteristics like pre- dicting accuracy.

Neural network model and support vec- tor machine model are two effective methods to solve. The CBM model (Model 1) is then compared with the CBM model which uses raw oil data as the covariates (Model 2). Using the PDCA cycle in the real world.

P a g e 3 subsidiary policies such as referring to privacy, confidentiality, customer complaints, Various HR policies Communicating those policie s to workers and other interested parties e.g. In manuals, on intranet, on display in reception or main office, in management system software, published.

Preparing Oil & Gas PVT Data for Reservoir Simulation Curtis H. Whitson NTNU / PERA. PERA Tasks Model Field-Data Based Initialization GOC. PERA 10 15 20 25 30 C7+ Mole Percent Depth, ft SSL Reference Depth GOC for black-oil Size: KB.

Petroleum Production Optimization Technology | Petroleum Production Optimization IPM model is an oil or gas production system which includes reservoir, wells and the surface network. The following table give a synthetic WC mobilizing immobile oil in ¾ mile range. Application of this technology well suits well/field having the following.

heavy oil or oil sands) or by producing oil remaing in reservoirs after current conventional production. Currently, it is expected that the world's oil elds have an average recovery below 50%.

With an increasing demand for oil and di cultiesin ndingnewmajoroil elds, theresearchine cientexploration of existing elds is becoming increasingly by: 1.

Industry Data Model. Upstream Oil & Gas. The upstream segment of oil and gas industry encompasses exploration and production (E&P) activities related to exploring for, recovery and production of crude oil, natural gas, and natural gas liquids (NGLs).

ADRM Software's Upstream Oil & Gas data model set consists of Enterprise. DPCA covariates, derived from DPCA of the oil data, represent most of the variability in the original data with reduced dimension and little cross-correlation.

This makes DPCA covariates ideal for. A Control-Limit Policy And Software For Condition-Based Maintenance Optimization.

real oil and vibration data is reported. applied to find the optimal condition based maintenance model [ The application of this method to chemical event detection is based in the idea that the appearance of a new component in con- tact to the sensor array will produce a new source of variance.

Gao's 13 research works with 3 citations and reads, including: Dynamic Behavior of p53 Driven by Delay and a Micrornaa-Mediated Feedback Loop. Table Pareto optimal solutions from the weighting function method Table B Gas injection and oil production rates for a set of 56 wells Table B Gas injection and oil production rates for a set of 56 wells obtained from theCited by: USED ENGINE OIL ANALYSIS USER INTERPRETATION GUIDE Abstract Used oil analysis is an important part of engine maintenance.

It provides information about the condition of the oil, its suitability for further use and to a certain extent information about the condition of the machinery lubricated by the Size: KB. Data Quality Enhancement in Oil Reservoir Operations: An application of IPMAP Paul Hong-Yi Lin Working Paper CISL# June Composite Information Systems Laboratory (CISL) Sloan School of Management, Room E Massachusetts Institute of Technology Cambridge, MA.

Data Acquisition and Characterization The IPM suite Integrated Production Modelling – is developed by Petroleum Experts (Petex).

IPM model is an oil or gas production system which includes reservoir, wells and the surface network. shock waves produced downhole can increase oil production in currently producing well with high WC.product’s) Material Safety Data Sheet or contact Nippon Kayaku head office.

No freedom from any patent is granted or to be inferred. Cautions for handling and storage of KAYARD, KAYAMER, and KAYACURE DPCA KAYARAD DPCA KAYARAD DPCA KAYARAD DPCA KAYARAD DN Mixture of multifunctional KAYARAD.Using these data, the model is then used to predict the production from all major oil producing countries, regions and continents up to the year The limited regional and global potential to compensate this decline with unconventional oil and oil-equivalents is also presented.

Keywords: After the oil peak, regional oil production and.