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Permeability prediction and drainage capillary pressure simulation in sandstone reservoirs

Knowledge of reservoir porosity, permeability, and capillary pressure is essential to
exploration and production of hydrocarbons. Although porosity can be interpreted fairly
accurately from well logs, permeability and capillary pressure must be measured from
core. Estimating permeability and capillary pressure from well logs would be valuable
where cores are unavailable.
This study is to correlate permeability with porosity to predict permeability and
capillary pressures. Relationships between permeability to porosity can be complicated
by diagenetic processes like compaction, cementation, dissolution, and occurrence of clay
minerals. These diagenetic alterations can reduce total porosity, and more importantly,
reduce effective porosity available for fluid flow. To better predict permeability, effective
porosity needs to be estimated. A general equation is proposed to estimate effective
porosity. Permeability is predicted from effective porosity by empirical and theoretical
equations.
A new capillary pressure model is proposed. It is based on previous study, and
largely empirical. It is tested with over 200 samples covering a wide range of lithology
(clean sandstone, shaly sandstone, and carbonates dominated by intergranular pores).
Parameters in this model include: interfacial tension, contact angle, shape factor,
porosity, permeability, irreducible water saturation, and displacement pressure. These
parameters can be measured from routine core analysis, estimated from well log, and
assumed. An empirical equation is proposed to calculate displacement pressure from
porosity and permeability. The new capillary-pressure model is applied to evaluate
sealing capacity of seals, calculate transition zone thickness and saturation above free
water level in reservoirs. Good results are achieved through integration of well log data,
production data, core, and geological concepts.

Identiferoai:union.ndltd.org:tamu.edu/oai:repository.tamu.edu:1969.1/1496
Date17 February 2005
CreatorsWu, Tao
ContributorsBerg, Robert R.
PublisherTexas A&M University
Source SetsTexas A and M University
Languageen_US
Detected LanguageEnglish
TypeBook, Thesis, Electronic Dissertation, text
Format1270954 bytes, electronic, application/pdf, born digital

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