When estimating permeability (k) from NMR logs, a key assumption is that the surface relaxivity (r2) parameter, which scales the relationship between transverse relaxation time (T2) and the surface-to-volume ratio (S/V) of the pore system, remains constant. With this assumption, the r2 parameter can be accounted for in the premultiplier of the SDR permeability equation. However, the presence of clays and/or heavy minerals in complex reservoirs can have a significant effect on r2, and the permeability estimate can be significantly improved if this variation is accounted for. Recently, Zielinski and coworkers proposed a method for deriving r2 from the two-dimensional (2D) diffusion relaxation time maps, or D-T2 maps, as an alternative to the traditional methods that rely on the matching NMR T2distributions and mercury porosimetry (MICP) or BET surface area measurements. This methodology is based on the fact that the translational self-diffusion coefficient (D) of a fluid saturating a porous media has its diffusional displacements restricted by collisions with the pore walls, so that D becomes a function of the pore size distribution, i.e. the T2 distribution. In the present work we applied this novel approach for obtaining r2 directly from NMR measurements and used it to improve the classical SDR permeability estimator. The equation used to estimate permeability with this new methodology was called kp. We have applied this improved k estimation technique to a set of benchmark quarried rock cores, whose results have shown a significant decrease in data dispersion and in the predicted error, when compared to the classical SDR equation. The ability to acquire D-T2 correlation maps downhole makes the new methodology presented here very promising in heterogeneous wells where previous estimators show sometimes poor correlations.
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Permeability Prediction Improvement Using 2D NWR Diffusion-T2 Maps
Andre Souza;
Andre Souza
Schlumberger Brazil Research and Geoengineering Center
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Giovanna Carneiro;
Giovanna Carneiro
Schlumberger Brazil Research and Geoengineering Center
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Lukasz Zielinski;
Lukasz Zielinski
Schlumberger Houston Formation Evaluation Center
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Lawrence Schwartz;
Lawrence Schwartz
Schlumberger-Doll Research Center
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Martin D. Hürlimann;
Martin D. Hürlimann
Schlumberger-Doll Research Center
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Austin Boyd;
Austin Boyd
Schlumberger Brazil Research and Geoengineering Center
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Edmilson Helton Rios;
Edmilson Helton Rios
Petrobras Research and Development Center
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Bernardo Coutinho Camilo dos Santos;
Bernardo Coutinho Camilo dos Santos
Petrobras Research and Development Center
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Willian Andrighetto Trevizan;
Willian Andrighetto Trevizan
Petrobras Research and Development Center
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Vinícius de França Machado;
Vinícius de França Machado
Petrobras Research and Development Center
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Rodrigo Bagueira de Vasconcellos Azeredo
Rodrigo Bagueira de Vasconcellos Azeredo
Federal Fluminense University
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Paper presented at the SPWLA 54th Annual Logging Symposium, New Orleans, Louisiana, June 2013.
Paper Number:
SPWLA-2013-U
Published:
June 22 2013
Citation
Souza, Andre, Carneiro, Giovanna, Zielinski, Lukasz, Polinski, Ralf, Schwartz, Lawrence, Hürlimann, Martin D., Boyd, Austin, Rios, Edmilson Helton, dos Santos, Bernardo Coutinho Camilo, Trevizan, Willian Andrighetto, de França Machado, Vinícius, and Rodrigo Bagueira de Vasconcellos Azeredo. "Permeability Prediction Improvement Using 2D NWR Diffusion-T2 Maps." Paper presented at the SPWLA 54th Annual Logging Symposium, New Orleans, Louisiana, June 2013.
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