Optimal reservoir management and well placement under geologic uncertainty /

Bibliographic Details
Main Author: Taware, Satyajit Vijay
Other Authors: Datta-Gupta, Akhil (Thesis advisor), King, Michael (Thesis advisor)
Format: Thesis eBook
Language:English
Published: [College Station, Tex.] : [Texas A&M University], [2012]
Subjects:
Online Access:Link to OAK Trust copy

MARC

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100 1 |a Taware, Satyajit Vijay. 
245 1 0 |a Optimal reservoir management and well placement under geologic uncertainty /  |c by Satyajit Vijay Taware. 
264 1 |a [College Station, Tex.] :  |b [Texas A&M University],  |c [2012] 
300 |a 1 online resource. 
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" 
588 |a Description from author supplied metadata (automated record created 2012-10-22 13:24:58). 
502 |b Doctor of Philosophy  |c Texas A&M University  |d 2012  |o http://hdl.handle.net/1969.1/ETD-TAMU-2012-08-11670 
504 |a Includes bibliographical references. 
516 |a Text (Dissertation) 
520 3 |a Reservoir management, sometimes referred to as asset management in the context of petroleum reservoirs, has become recognized as an important facet of petroleum reservoir development and production operations. In the first stage of planning field development, the simulation model is calibrated to dynamic data (history matching). One of the aims of the research is to extend the streamline based generalized travel time inversion method for full field models with multimillion cells through the use of grid coarsening. This makes the streamline based inversion suitable for high resolution simulation models with decades long production history and numerous wells by significantly reducing the computational effort. In addition, a novel workflow is proposed to integrate well bottom-hole pressure data during model calibration and the approach is illustrated via application to the CO₂ sequestration. In the second stage, field development strategies are optimized. The strategies are primarily focused on rate optimization followed by infill well drilling. A method is proposed to modify the streamline-based rate optimization approach which previously focused on maximizing sweep efficiency by equalizing arrival time of the waterfront to producers, to account for accelerated production for improving the net present value (NPV). Optimum compromise between maximizing sweep efficiency and maximizing NPV can be selected based on a 'trade-off curve'. The proposed method is demonstrated on field scale application considering geological uncertainty. Finally, a novel method for well placement optimization is proposed that relies on streamlines and time of flight to first locate the potential regions of poorly swept and drained oil. Specifically, the proposed approach utilizes a dynamic measure based on the total streamline time of flight combined with static and dynamic parameters to identify "Sweet-Spots" for infill drilling. The "Sweet-Spots" can be either used directly as potential well-placement locations or as starting points during application of a formal optimization technique. The main advantage of the proposed method is its computational efficiency in calculating dynamic measure map. The complete workflow was also demonstrated on a multimillion cell reservoir model of a mature carbonate field with notable success. The infill locations based on dynamic measure map have been verified by subsequent drilling. 
500 |a Electronic resource. 
650 4 |a Major Petroleum Engineering. 
653 |a Reservoir simulation 
653 |a CO2 sequestration 
653 |a well placement optimization 
653 |a history matching 
653 |a production optimization 
700 1 |a Datta-Gupta, Akhil,  |e thesis advisor. 
700 1 |a King, Michael,  |e thesis advisor. 
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