Journal
MATHEMATICAL GEOSCIENCES
Volume 45, Issue 6, Pages 753-771Publisher
SPRINGER HEIDELBERG
DOI: 10.1007/s11004-013-9473-2
Keywords
Bimodal Gaussian density function; Inverse problem; Pore-size distribution; Petrophysical modeling; Rock typing
Funding
- University of Texas at Austin's Research Consortium
- Afren
- Anadarko
- Apache
- Aramco
- Baker-Hughes
- BG
- BHP Billiton
- BP
- Chevron
- China Oilfield Services, LTD.
- ConocoPhillips
- ENI
- ExxonMobil
- Halliburton
- Hess
- Maersk
- Marathon Oil Corporation
- Mexican Institute for Petroleum
- Nexen
- ONGC
- OXY
- Petrobras
- Repsol
- RWE
- Schlumberger
- Shell
- Statoil
- Total
- Weatherford
- Wintershall
- Woodside Petroleum Limited
Ask authors/readers for more resources
This paper introduces a bimodal Gaussian density function to characterize pore-size distributions in terms of incremental pore volume versus logarithmic pore-throat radius. An inverse problem is formulated and solved to reconstruct mercury injection capillary pressure curves by enforcing a bimodal Gaussian pore-size distribution. The bimodal Gaussian model generates six petrophysically interpretable attributes which provide a quantitative basis for petrophysical modeling and rock typing. Correlations between these attributes and their associated petrophysical properties are investigated to verify interpretations. In the field case, the correlation coefficient (R (2)) between absolute permeability, end-point gas relative permeability and the mean value of large pore-throat size mode are 0.93 and 0.715, respectively. Correlation (R (2)=0.613) is also observed between critical water saturation and pore volume connected by small pore-throat sizes. Petrophysical modeling based on the bimodal Gaussian pore-size distribution with sufficient core data calibration predicts static and dynamic petrophysical properties that are in agreement with laboratory core measurements. The quantitative pore-system description underlies a new petrophysical rock typing method that combines all relevant pore-system attributes. Verification of the method was performed with field data from two key wells in the Hugoton carbonate gas field, Kansas.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available