| 000 | 02492nab a2200205 4500 | ||
|---|---|---|---|
| 005 | 20260520001756.0 | ||
| 008 | 260224s2009 xxu | ||
| 245 | 0 | 0 | _aComparison of interwell connectivity predictions using percolation, geometrical, and Monte Carlo models |
| 260 |
_a _b _coct. 2009 |
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| 270 | _a16/06/2010 ; 16/06/2010 | ||
| 300 | _a7 p. ; 180-186 | ||
| 520 | _aTranscripción del resumen del autor. Reservoir connectivity is often an important consideration for reservoir management. For example, connectivity controls waterflood sweep efficiency and it affects decisions concerning well placement and spacing. The uncertainty of sandbody distributions, however, can make interwell connectivity prediction extremely difficult. Percolation models are a useful tool to simulate sandbody connectivity behavior to estimate interwell connectivity. This study applies a percolation method to estimate interwell connectivity. Using results derived by Andrade, King, and others for fluid travel time between locations in a percolation model, we develop a method to estimate interwell connectivity. Four parameters are needed to use this approach: the net-to-gross ratio psand, the typical sandbody size, reservoir length and well spacing. To evaluate this new percolation method, the results are compared to results from geometrical models, Monte Carlo, and reservoir simulation. These methods were applied to estimate interwell connectivity for three non-communicating stratigraphic intervals in Monument Butte oil field, Utah. The results suggest that the percolation method can estimate the probability of interwell connectivity reliably for thin intervals for any values of psand, well spacing, and reservoir length. The geometrical model also performs well, but can only be applied in fields where the well spacing is less than one-half of the sandbody size. The proposed method requires that the reservoir interval for evaluation be sufficiently thin so that 2D percolation results can be applied. For thick intervals or heterogeneous sandbody distributions, the percolation method developed here is not suitable because it assumes thin layers. Future percolation research will be needed to adapt this new method to 3D cases. | ||
| 581 | _a3-4 | ||
| 773 | 0 |
_tJournal of Petroleum Science & Engineering _g68 |
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| 942 | _cARTICULO | ||
| 100 | 1 |
_aLi, Weiqiang _942845 |
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| 100 | 1 |
_aJensen, Jerry L. _942846 |
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| 100 | 1 |
_aAyers, Walter B. _920439 |
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| 999 |
_c171109 _d171109 |
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