The effects of incorporating dynamic data on estimates of uncertainty /

Bibliographic Details
Main Author: Mulla, Shahebaz Hisamuddin, 1975-
Other Authors: McVay, Duane A. (Thesis advisor)
Format: Thesis eBook
Language:English
Published: [College Station, Tex.] : [Texas A&M University], [2004]
Subjects:
Online Access:Link to OAK Trust copy

MARC

Tag First Indicator Second Indicator Subfields
LEADER 00000cam a2200000Ka 4500
001 in00001839733
005 20151026065631.0
006 m d
007 cr unu--------
008 040618s2004 txu obm 000 0 eng d
035 |a (OCoLC)ocm55673706 
035 |a (TxCM)etd-tamu-2003C-PETE-Mulla 
040 |a TXA  |c TXA  |d UtOrBLW 
049 |a TXAM 
099 |a 2003  |a Thesis  |a M76 
100 1 |a Mulla, Shahebaz Hisamuddin,  |d 1975- 
245 1 4 |a The effects of incorporating dynamic data on estimates of uncertainty /  |c by Shahebaz Hisamuddin Mulla. 
264 1 |a [College Station, Tex.] :  |b [Texas A&M University],  |c [2004] 
336 |a text  |b txt  |2 rdacontent 
337 |a computer  |b c  |2 rdamedia 
338 |a online resource  |b cr  |2 rdacarrier 
500 |a "Major Subject: Petroleum Engineering" 
500 |a Title from author supplied metadata (automated record created on Apr. 30, 2004.) 
500 |a Vita. 
500 |a Abstract. 
502 |b M. S.  |c Texas A&M University  |d 2003. 
504 |a Includes bibliographical references. 
516 |a Text (Thesis). 
520 3 |a Petroleum exploration and development are capital intensive and smart economic decisions that need to be made to profitably extract oil and gas from the reservoirs. Accurate quantification of uncertainty in production forecasts will help in assessing risk and making good economic decisions. This study investigates the effect of combining dynamic data with the uncertainty in static data to see the effect on estimates of uncertainty in production forecasting. Fifty permeability realizations were generated for a reservoir in west Texas from available petrophysical data. We quantified the uncertainty in the production forecasts using a likelihood weighting method and an automatic history matching technique combined with linear uncertainty analysis. The results were compared with the uncertainty predicted using only static data. We also investigated approaches for best selecting a smaller number of models from a larger set of realizations to be history matched for quantification of uncertainty. We found that incorporating dynamic data in a reservoir model will result in lower estimates of uncertainty than considering only static data. However, incorporation of dynamic data does not guarantee that the forecasted ranges will encompass the true value. Reliability of the forecasted ranges depends on the method employed. When sampling multiple realizations of static data for history matching to quantify uncertainty, a sampling over the entire range of realization likelihoods shows larger confidence intervals and is more likely to encompass the true value for predicted fluid recoveries, as compared to selecting the best models. 
538 |a Mode of access: World Wide Web. 
538 |a System requirements: World Wide Web access and Adobe Acrobat Reader. 
500 |a Electronic resource. 
650 4 |a Major petroleum engineering. 
653 |a reservoir simulation 
653 |a uncertianty estimation 
653 |a dynamic data 
700 1 |a McVay, Duane A.,  |e thesis advisor. 
856 4 0 |u http://hdl.handle.net/1969.1/183  |z Link to OAK Trust copy  |t 0 
994 |a C0  |b TXA 
999 |a MARS 
999 f f |s 6629c8f7-b19c-35f5-808a-5966bab675b7  |i 6d5a6dab-4f78-35cb-a3ce-d6105c16ac0e  |t 0 
952 f f |a Texas A&M University  |b College Station  |c Electronic Resources  |d Available Online  |t 0  |e 2003 Thesis M76  |g Electronic  |h Other scheme 
998 f f |a 2003 Thesis M76  |t 0  |l Available Online