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INTELLIGENT SIGNAL PROCESSING FOR OILFIELD
WATERFLOOD MANAGEMENT
by
Feilong Liu
A Dissertation Presented to the
FACULTY OF THE GRADUATE SCHOOL
UNIVERSITY OF SOUTHERN CALIFORNIA
In Partial Fulfillment of the
Requirements for the Degree
DOCTOR OF PHILOSOPHY
(ELECTRICAL ENGINEERING)
May 2008
Copyright 2008 Feilong Liu
Object Description
| Title | Intelligent signal processing for oilfield waterflood management |
| Author | Liu, Feilong |
| Author email | feilongl@usc.edu |
| Degree | Doctor of Philosophy |
| Document type | Dissertation |
| Degree program | Electrical Engineering |
| School | Viterbi School of Engineering |
| Date defended/completed | 2008-03-14 |
| Date submitted | 2008 |
| Restricted until | Unrestricted |
| Date published | 2008-04-11 |
| Advisor (committee chair) | Mendel, Jerry M. |
| Advisor (committee member) |
Jenkins, B. Keith Ershaghi, Iraj |
| Abstract | This thesis addresses two problems about water-flood management: (1) infer reservoir heterogeneity using measured injection and production rates, and (2) construct a decision support system to optimize oil production using computing with words (CWW) and the inferred reservoir heterogeneity.; To infer reservoir heterogeneity, we first present an adaptive method using an Extended Kalman Filter (EKF) for the case of multiple injectors and a single producer, and then present a pseudo-virtual reservoir method for the case of multiple injectors and multiple producers, respectively. In the EKF method, a very simple parametric model, one with two parameters per injector, is used so that if a producer depends upon N injectors our model contains exactly 2N parameters; and the EKF is used to adaptively estimate the 2N parameters, from which the injector-producer relationship (IPR) between each injector and a producer is then estimated. In the pseudo-virtual reservoir method, a virtual reservoir model is used to model the reservoir, and a pseudo- virtual reservoir model is used to estimate the regional impact from each injector, so that the problem for this case reduces to the problem for the case of multiple injectors and a single producer.; The study for decision support system using CWW focuses on the encoder component (called type-2 fuzzistics) of a perceptual computer (Per-C), a specific architecture for CWW using interval type-2 fuzzy sets, and our work so far has been to transform linguistic perceptions, words, into interval type-2 fuzzy sets (IT2 FS) that activate a CWW engine. We have proposed a new and simple approach, called the Interval Approach (IA), to type-2 fuzzistics, one that captures the strong points of both the person membership function and interval end-points approaches. It collects interval end-point data from subjects, does not require subjects to be knowledgeable about fuzzy sets, has a straightforward mapping from data to footprint of uncertainty (FOU), does not require an a priori assumption about whether or not a FOU is symmetric or non-symmetric, and leads to an IT2 FS word model that reduces to a T1 FS word model automatically if all subjects provide the same intervals. |
| Keyword | oilfield waterflood management; reservoir connectivity; injector-producer relationship; regional impact; extended kalman filter; decision support system; computing with words; fuzzistics; interval approach |
| Language | English |
| Part of collection | University of Southern California dissertations and theses |
| Publisher (of the original version) | University of Southern California |
| Place of publication (of the original version) | Los Angeles, California |
| Publisher (of the digital version) | University of Southern California. Libraries |
| Type | texts |
| Legacy record ID | usctheses-m1102 |
| Rights | Liu, Feilong |
| Repository name | Libraries, University of Southern California |
| Repository address | Los Angeles, California |
| Repository email | http://www.usc.edu/isd/libraries/services/ask_a_librarian/email/ |
| Filename | etd-Liu-20080411 |
| Archival file | uscthesesreloadpub_Volume29/etd-Liu-20080411.pdf |
Description
| Title | Page 1 |
| Full text | INTELLIGENT SIGNAL PROCESSING FOR OILFIELD WATERFLOOD MANAGEMENT by Feilong Liu A Dissertation Presented to the FACULTY OF THE GRADUATE SCHOOL UNIVERSITY OF SOUTHERN CALIFORNIA In Partial Fulfillment of the Requirements for the Degree DOCTOR OF PHILOSOPHY (ELECTRICAL ENGINEERING) May 2008 Copyright 2008 Feilong Liu |
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