| 000 | 02017nab a2200217 4500 | ||
|---|---|---|---|
| 005 | 20260608201742.0 | ||
| 008 | 260224s2012 xxu ing | ||
| 041 | _aInglés | ||
| 100 | 1 |
_aKhosravi, M. _953188 |
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| 100 | 1 |
_aRostami, B. _943421 |
|
| 100 | 1 |
_aFatemi, S. _953189 |
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| 245 | 0 | 0 |
_aUncertainty Analysis of a Fractured Reservoir's Performance _bA Case Study |
| 260 |
_a _b _cmayo/jun. 2012 |
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| 270 | _a15/05/2013 ; 15/05/2013 | ||
| 300 | _a10 p. ; 423-433 | ||
| 520 | _aTraducción del resúmen del autor: In recent years, the oil industry has given great importance to reservoir management and reservoir uncertainty analysis. The development of a method that can model and quantify uncertainties in reservoir simulation studies in an efficient and practical way is clearly desirable. Different approaches such as Response Surface Methodology (RSM) and Monte-Carlo simulation have been used to address the uncertainties. In this paper, response surface method is used to realize the most influential parameters on pressure drop and recovery factor changes, regarding their practical levels of uncertainties during the development of fractured reservoir model. The present approach is performed to magnify the significant parameters and developing compatible and more realistic proxy equation for forecasting oil recovery from a typical low permeable fractured reservoir. The proxy model allows Monte-Carlo analysis to determine sensitivities and the quantification of the impact of uncertainty on production forecasts. Results indicate that the oil recovery is more sensitive to aquifer strength, fracture permeability and block height. In addition, however the interaction between other parameters, such as matrix size, fracture permeability and aquifer volume, showed a degree of importance during this analysis. Monte-Carlo analysis forecasts wide range of oil recovery for this field development. | ||
| 581 | _a3 | ||
| 773 | _g | ||
| 942 | _cARTICULO | ||
| 999 |
_c187694 _d187694 |
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