Отправлено: 22.10.17 14:14. Заголовок: Identification of sedimentary-diagenetic facies and reservoir porosity and permeability prediction

Identification of sedimentary-diagenetic facies and reservoir porosity
and permeability prediction: An example from the Eocene beach-bar
sandstone in the Dongying Depression, China

Jian Wang a, b, *
, Yingchang Cao a, b, **, Keyu Liu a, c
, Jie Liu d
, Muhammad Kashif a

Marine and Petroleum Geology 82 (2017) 69e84


Absracts
Accurate prediction of reservoir porosity and permeability is essential for prospecting hydrocarbon reserves
and petroleum production capacity. We propose an innovative reservoir porosity and permeability
prediction method through identifying sedimentary-diagenetic facies, determining the porositypermeability
trends using core measurement data, extrapolating the spatial distribution of the
sedimentary-diagenetic facies using log data through the Bayes discriminant analysis and predicting the
reservoir porosity and permeability.
The essence of the method was illustrated and its effectiveness was demonstrated using the Eocene
beach-bar sandstones in the Dongying Depression, Bohai Bay Basin, eastern China.

The Eocene beach bar sandstones are classified into fine sandstone, siltstone, and argillaceous
siltstone based on grain sizes, sorting, and matrix contents. The major diagenetic processes that
influence the porosity and permeability of the beach-bar sandstones are compaction, carbonate
cementation and feldspar dissolution.

Seven sedimentary-diagenetic facies were identified in the beachbar sandstones based on the lithological types,
and their corresponding diagenesis and influence extent
on reservoir properties.
The variation ranges of porosity and permeability (log K) of these sedimentarydiagenetic
facies are typically less than 6% and 1.2, respectively. Both the porosity and permeability have
well defined functional relationships with depth.

The sedimentary-diagenetic facies can be identified effectively from logging data through the use of the
Bayes discriminant analysis and corresponding crossplots.

The porosity and permeability (log K) of the well evaluated in the study were predicted with errors
in the range of ±3% and ±0.6, respectively, based on the distribution and the fitting equation of the trend
lines for the seven sedimentary-diagenetic facies. The predicted porosities and permeability of
sedimentary-diagenetic facies match the measured porosities and permeability well.