10.1021/ef401815q.s001
Zhaomin Li
Zhaomin
Li
Shuhua Wang
Shuhua
Wang
Songyan Li
Songyan
Li
Wei Liu
Wei
Liu
Binfei Li
Binfei
Li
Qi-Chao Lv
Qi-Chao
Lv
Accurate Determination of the CO<sub>2</sub>–Brine
Interfacial Tension Using Graphical Alternating Conditional Expectation
American Chemical Society
2015
monovalent cation molalities
formation water salinity
IFT
CO 2 impurities
ACE
CH 4 mole fraction
Spearman correlation coefficients
SD
bivalent cation molalities
reservoir pressure
CO 2 streams
rank correlation coefficients
AARE
2015-12-17 00:14:32
Dataset
https://acs.figshare.com/articles/dataset/Accurate_Determination_of_the_CO_sub_2_sub_Brine_Interfacial_Tension_Using_Graphical_Alternating_Conditional_Expectation/2027661
A newly
developed CO<sub>2</sub>–brine interfacial tension
(IFT) correlation based on the alternating condition expectation (ACE)
algorithm has been successfully proposed to more accurately estimate
the CO<sub>2</sub>–brine IFT for a wide range of reservoir
pressure, temperature, formation water salinity and injected gas composition.
The new CO<sub>2</sub>–brine correlation is expressed as a
function of reservoir pressure, temperature, monovalent cation molalities
(Na<sup>+</sup> and K<sup>+</sup>), bivalent cation molalities (Ca<sup>2+</sup> and Mg<sup>2+</sup>), N<sub>2</sub> mole fraction and CH<sub>4</sub> mole fraction in injected gas. This prediction model is originated
from a CO<sub>2</sub>–brine IFT database from the literature
that covers 1609 CO<sub>2</sub>–brine IFT data for pure and
impure CO<sub>2</sub> streams. To test the validity and accuracy of
the developed CO<sub>2</sub>–brine IFT model, the entire dataset
was divided into two groups: a training database consisting of 805
points and a testing dataset consisting of 804 points, which was arbitrarily
selected from the total database. To further examine its predicted
capacity, the new CO<sub>2</sub>–brine IFT correlation is validated
with four commonly used pure CO<sub>2</sub>–pure water IFT
correlations in the literature, it is found that the new CO<sub>2</sub>–brine IFT correlation provides the comprehensive and accurate
reproduction of the literature pure CO<sub>2</sub>–pure water
IFT data with an average absolute relative error (% AARE) of 12.45%
and standard deviation (% SD) of 18.57%, respectively. In addition,
the newly developed CO<sub>2</sub>–brine IFT correlation results
in the accurate prediction of the CO<sub>2</sub>–brine IFT
with a % AARE of 10.19% and % SD of 13.16%, respectively, compared
to two CO<sub>2</sub>–brine IFT correlations. Furthermore,
sensitivity analysis was performed based on the Spearman correlation
coefficients (rank correlation coefficients). The major factor influenced
on the CO<sub>2</sub>–brine IFT is reservoir pressure, which
has a major negative impact on the CO<sub>2</sub>–brine IFT.
In contrast, the effects of CO<sub>2</sub> impurities and salt components
in the water on the CO<sub>2</sub>–brine IFT are in the following
order in terms of their positive impact: bivalent cation molalities
(Ca<sup>2+</sup> and Mg<sup>2+</sup>), CH<sub>4</sub>, N<sub>2</sub>, and monovalent cation molalities (Na<sup>+</sup> and K<sup>+</sup>).