Using percolation techniques to estimate interwell connectivity probability

Reservoir connectivity is often an important consideration for reservoir management. For example, connectivity is an important control on waterflood sweep efficiency and requires evaluation to optimize injection well rates. The uncertainty of sandbody distributions, however, can make interwell conn...

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Main Author: Li, Weiqiang
Other Authors: Jensen, Jerry
Format: Others
Language:en_US
Published: 2010
Subjects:
Online Access:http://hdl.handle.net/1969.1/ETD-TAMU-1954
http://hdl.handle.net/1969.1/ETD-TAMU-1954
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spelling ndltd-tamu.edu-oai-repository.tamu.edu-1969.1-ETD-TAMU-19542013-01-08T10:40:56ZUsing percolation techniques to estimate interwell connectivity probabilityLi, WeiqiangPERCOLATIONINTERWELL CONNECTIVITYReservoir connectivity is often an important consideration for reservoir management. For example, connectivity is an important control on waterflood sweep efficiency and requires evaluation to optimize injection well rates. The uncertainty of sandbody distributions, however, can make interwell connectivity prediction extremely difficult. Percolation models are a useful tool to simulate sandbody connectivity behavior and can be used to estimate interwell connectivity. This study discusses the universal characteristics of different sandbody percolation models and develops an efficient percolation method to estimate interwell connectivity. Using King and others results for fluid travel time between locations in a percolation model, we developed a method to estimate interwell connectivity. Three parameters are needed to use this approach: the sandbody occupied probabilitysandp, the dimensionless reservoir length, and the well spacing. To evaluate this new percolation method, the procedure was coded using Visual Basic and Mathematica and the results compared to those from two other methods, a simple geometrical model and Monte Carlo simulation. All these methods were applied to estimate interwell connectivity for the D1, D2, and D3 intervals in the Monument Butte field. The results suggest that the new percolation method can give reasonable effective-square sandbody dimensions and can estimate the interwell connectivity accurately for thin intervals with sandp in the 60% to 80% range. The proposed method requires that the reservoir interval for evaluation be sufficiently thin so that 2D percolation results can be applied. To extend the method to 3D cases, we propose an approach that can be used to estimate interwell connectivity for reservoirs having multiple, noncommunicating layers, and that considers the weight of each interval for multilayer estimation. This approach is applied to the three-layer case of Monument Butte field and the estimates showed the method gives useful results for well pattern design. For example, water saturation and interval thickness affect the weight of each interval to be included in the multilayer estimation. 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 percolation method.Jensen, Jerry2010-01-15T00:15:21Z2010-01-16T02:24:41Z2010-01-15T00:15:21Z2010-01-16T02:24:41Z2007-082009-06-02BookThesisElectronic Thesistextelectronicapplication/pdfborn digitalhttp://hdl.handle.net/1969.1/ETD-TAMU-1954http://hdl.handle.net/1969.1/ETD-TAMU-1954en_US
collection NDLTD
language en_US
format Others
sources NDLTD
topic PERCOLATION
INTERWELL CONNECTIVITY
spellingShingle PERCOLATION
INTERWELL CONNECTIVITY
Li, Weiqiang
Using percolation techniques to estimate interwell connectivity probability
description Reservoir connectivity is often an important consideration for reservoir management. For example, connectivity is an important control on waterflood sweep efficiency and requires evaluation to optimize injection well rates. The uncertainty of sandbody distributions, however, can make interwell connectivity prediction extremely difficult. Percolation models are a useful tool to simulate sandbody connectivity behavior and can be used to estimate interwell connectivity. This study discusses the universal characteristics of different sandbody percolation models and develops an efficient percolation method to estimate interwell connectivity. Using King and others results for fluid travel time between locations in a percolation model, we developed a method to estimate interwell connectivity. Three parameters are needed to use this approach: the sandbody occupied probabilitysandp, the dimensionless reservoir length, and the well spacing. To evaluate this new percolation method, the procedure was coded using Visual Basic and Mathematica and the results compared to those from two other methods, a simple geometrical model and Monte Carlo simulation. All these methods were applied to estimate interwell connectivity for the D1, D2, and D3 intervals in the Monument Butte field. The results suggest that the new percolation method can give reasonable effective-square sandbody dimensions and can estimate the interwell connectivity accurately for thin intervals with sandp in the 60% to 80% range. The proposed method requires that the reservoir interval for evaluation be sufficiently thin so that 2D percolation results can be applied. To extend the method to 3D cases, we propose an approach that can be used to estimate interwell connectivity for reservoirs having multiple, noncommunicating layers, and that considers the weight of each interval for multilayer estimation. This approach is applied to the three-layer case of Monument Butte field and the estimates showed the method gives useful results for well pattern design. For example, water saturation and interval thickness affect the weight of each interval to be included in the multilayer estimation. 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 percolation method.
author2 Jensen, Jerry
author_facet Jensen, Jerry
Li, Weiqiang
author Li, Weiqiang
author_sort Li, Weiqiang
title Using percolation techniques to estimate interwell connectivity probability
title_short Using percolation techniques to estimate interwell connectivity probability
title_full Using percolation techniques to estimate interwell connectivity probability
title_fullStr Using percolation techniques to estimate interwell connectivity probability
title_full_unstemmed Using percolation techniques to estimate interwell connectivity probability
title_sort using percolation techniques to estimate interwell connectivity probability
publishDate 2010
url http://hdl.handle.net/1969.1/ETD-TAMU-1954
http://hdl.handle.net/1969.1/ETD-TAMU-1954
work_keys_str_mv AT liweiqiang usingpercolationtechniquestoestimateinterwellconnectivityprobability
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