Finding and developing oil and gas resources requires accurate geological information with which to formulate strategies for exploration and exploitation ventures. When data are scarce, statistical procedures are sometimes substituted to compensate for the lack of information about reservoir properties. The most modern methods incorporate geostatistics. Even the best geostatistical methods yield results with varying degrees of uncertainty in their solutions. Geological information is, by its nature, spatially limited and the geoscientist is handicapped in determining appropriate values for various geological parameters that affect the final reservoir model (Massonnat, 1999). This study focuses on reservoir models that depend on geostatistical methods. This is accomplished by quantifying the uncertainty in outcome of reservoir simulations as six different geological variables are changed during a succession of reservoir simulations. In this study, variations in total fluid produced are examined by numerical modeling. Causes of uncertainty in outcomes of the model runs are examined by changing one of six geological parameters for each run. The six geological parameters tested for their impact on reservoir performances include the following: 1) variogram range used to krig thickness layers, 2) morphology around well 14, 3) shelf edge orientation, 4) bathymetry ranges attributed for each facies, 5) variogram range used to simulate facies distribution, 6) extension of the erosion at top of the reservoir. The parameters were assigned values that varied from a minimum to a maximum quantity, determined from petrophysical and core analysis. After simulation runs had been completed, a realistic, 3-dimensional reservoir model was developed that revealed a range of reservoir production data. The parameters that had the most impact on reservoir performance were: 1) the amount of rock eroded at the top of the reservoir zone and 2) the bathymetry assigned to the reservoir facies. This study demonstrates how interaction between geological parameters influence reservoir fluid production, how variations in those parameters influence uncertainties in reservoir simulations, and it highlights the interdependencies between geological variables. The analysis of variance method used to quantify uncertainty in this study was found to be rapid, accurate, and highly satisfactory for this type of study. It is recommended for future applications in the petroleum industry.
| Identifer | oai:union.ndltd.org:TEXASAandM/oai:repository.tamu.edu:1969.1/1302 |
| Date | 17 February 2005 |
| Creators | Schepers, Karine Chrystel |
| Contributors | Ahr, Wayne M., Mc Vay, Duane A., Zhan, Hongbin, Hajash, Andrew |
| Publisher | Texas A&M University |
| Source Sets | Texas A and M University |
| Language | en_US |
| Detected Language | English |
| Type | Electronic Thesis, text |
| Format | 5893690 bytes, electronic, application/pdf, born digital |
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