Accurate prediction of infill well production is crucial since the expected amount
of incremental production is used in the decision-making process to choose the best infill
locations. Making a good decision requires taking into account all possible outcomes and
so it is necessary to quantify the uncertainty in forecasts. Many researchers have
addressed the infill well location selection problem previously. Some of them used
optimization algorithms, others presented empirical methods and some of them tried to
solve this problem with statistical approaches. In this study, a reservoir simulation based
approach was used to select infill well locations. I used multiple reservoir realizations to
take different possible outcomes into consideration, generated probabilistic distributions
of incremental field production and, finally, used descriptive statistical analysis to
evaluate results. I quantified the uncertainty associated with infill location selection in
terms of incremental field production and validated the approach on a synthetic reservoir
model. Results of this work gave us the possible infill locations, which have a mean
higher than the minimum economic limit, with a range of expected incremental
production.
| Identifer | oai:union.ndltd.org:tamu.edu/oai:repository.tamu.edu:1969.1/ETD-TAMU-2806 |
| Date | 15 May 2009 |
| Creators | Senel, Ozgur |
| Contributors | McVay, A. Duane |
| Source Sets | Texas A and M University |
| Language | en_US |
| Detected Language | English |
| Type | Book, Thesis, Electronic Thesis, text |
| Format | electronic, application/pdf, born digital |
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