Page 1 |
Save page Remove page | Previous | 1 of 294 | Next |
|
small (250x250 max)
medium (500x500 max)
large ( > 500x500)
Full Resolution
All (PDF)
|
This page
All
Subset
|
DATA ASSIMILATION FOR FRACTURED SHALE GAS RESERVOIRS USING
ENSEMBLE KALMAN FILTER
by
Parham Ghods
A Dissertation Presented to the
FACULTY OF THE USC GRADUATE SCHOOL
UNIVERSITY OF SOUTHERN CALIFORNIA
In Partial Ful llment of the
Requirements for the Degree
DOCTOR OF PHILOSOPHY
(PETROLEUM ENGINEERING)
May 2012
Copyright 2012 Parham Ghods
Object Description
| Title | Data assimilation for fractured shale gas reservoirs using ensemble Kalman filter |
| Author | Ghods, Parham |
| Author email | pghods@usc.edu;parham.ghods@gmail.com |
| Degree | Doctor of Philosophy |
| Document type | Dissertation |
| Degree program | Petroleum Engineering |
| School | Viterbi School of Engineering |
| Date defended/completed | 2012-02-01 |
| Date submitted | 2012-02-08 |
| Date approved | 2012-02-08 |
| Restricted until | 2012-02-08 |
| Date published | 2012-02-08 |
| Advisor (committee chair) | Zhang, Dongxiao |
| Advisor (committee member) |
Ershaghi, Iraj Mendel, Jerry |
| Abstract | Production of shale gas reservoirs depends on natural and hydraulic fractures, which represent a significant challenge in numerical simulation. Unknown fracture characteristics such as location, orientation, aperture, and conductivity make reservoir modeling difficult. Even by knowing these properties, numerical models must be refined to capture the complex flow behavior around the fractures. Discrete fracture networks require model dependent unstructured gridding. Furthermore, for history matching and data assimilation, fracture characteristics must be updated, which causes changing the entire gridding of the model and is complicated and time consuming. Systematic history matching of shale gas reservoirs has not yet been addressed in the literature. In this study, we use shale gas wells' measurements to estimate the fractured reservoirs properties using Ensemble Kalman Filter (EnKF), a minimum mean square error data assimilation tool. We propose using dual porosity dual permeability modeling (DPDP), an averaging technique that does not require the knowledge of the fracture network characteristics. In the combined EnKF/DPDP methodology, numerical models are updated without changing the gridding as more measurements become available. We introduce and develop a new DPDP compartmentalized modeling, which represents the complex fracture network around a well. The updated models reproduce the historical performance of the reservoir and predict its future behavior. ❧ We test our proposed methodology on synthetic and real field cases from Appalachian Marcellus shale. It is shown that the algorithm does not require information about the locations and orientations of the fractures. We also show that if the knowledge about the fracture network statistics is available, it can be integrated into the algorithm yielding more accurate estimates of the reservoirs' field properties such as fracture porosity and permeability. Gridding is simple and DPDP models are simulated much faster than either the refined or DFN models. ❧ It is illustrated that the proposed methodologies provide a reliable and robust data assimilation and modeling tool for history matching of fractured reservoirs. They do not require changes in gridding and take less CPU time. Although the proposed methods are applied to shale gas reservoirs in this dissertation, their application can be extended to other types of fractured reservoirs. |
| Keyword | dual porosity dual permeability; ensemble Kalman filter; fracture modeling; numerical simulation; shale gas reservoirs; tight gas reservoirs |
| 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 |
| Provenance | Electronically uploaded by the author |
| Type | texts |
| Legacy record ID | usctheses-m |
| Contributing entity | University of Southern California |
| Rights | Ghods, Parham |
| Access conditions | The author retains rights to his/her dissertation, thesis or other graduate work according to U.S. copyright law. Electronic access is being provided by the USC Libraries in agreement with the author, as the original true and official version of the work, but does not grant the reader permission to use the work if the desired use is covered by copyright. It is the author, as rights holder, who must provide use permission if such use is covered by copyright. The original signature page accompanying the original submission of the work to the USC Libraries is retained by the USC Libraries and a copy of it may be obtained by authorized requesters contacting the repository e-mail address given. |
| Repository name | University of Southern California Digital Library |
| Repository address | USC Digital Library, University of Southern California, University Park Campus MC 7002, 106 University Village, Los Angeles, California 90089-7002, USA |
| Repository email | cisadmin@usc.edu |
| Archival file | uscthesesreloadpub_Volume6/etd-GhodsParha-472.pdf |
Description
| Title | Page 1 |
| Contributing entity | University of Southern California |
| Full text | DATA ASSIMILATION FOR FRACTURED SHALE GAS RESERVOIRS USING ENSEMBLE KALMAN FILTER by Parham Ghods A Dissertation Presented to the FACULTY OF THE USC GRADUATE SCHOOL UNIVERSITY OF SOUTHERN CALIFORNIA In Partial Ful llment of the Requirements for the Degree DOCTOR OF PHILOSOPHY (PETROLEUM ENGINEERING) May 2012 Copyright 2012 Parham Ghods |
