Adsorption of gases on heterogeneous shale surfaces: A review
Many studies tied to adsorption on heterogeneous surfaces have been reported in the literature. However, finding an adsorption model that accurately describes the sorption mechanism in gas shales remains a challenge. This is due to the complex surface heterogeneity and the presence of multiple compo...
Saved in:
Main Authors: | , , , , |
---|---|
Format: | Article |
Published: |
2022
|
Online Access: | http://scholars.utp.edu.my/id/eprint/33853/ https://www.scopus.com/inward/record.uri?eid=2-s2.0-85115013419&doi=10.1016%2fj.petrol.2021.109466&partnerID=40&md5=eef1011cdbed6c54d67de2df467e168b |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Summary: | Many studies tied to adsorption on heterogeneous surfaces have been reported in the literature. However, finding an adsorption model that accurately describes the sorption mechanism in gas shales remains a challenge. This is due to the complex surface heterogeneity and the presence of multiple components in the formation. Modelling and simulation at reservoir conditions for adsorption studies are also computationally expensive. An optimized adsorption model is therefore essential because it can lead to an accurate estimation of the adsorbed gas amount and ultimately improve the production process. This work presents a review of the adsorption models that have been used in characterizing shale formation. Moreover, the mechanisms and factors that control adsorption in shale formation and their interaction are also analyzed. As observed from the current review, Langmuir is the most used adsorption model. However, like other existing models, it does not adequately represent the sorption phenomenon in shale formation where surface heterogeneity and the presence of multi-component are eminent. There has thus been works to improve and enhance it for use in shale formation. On the other hand, the advancement of molecular simulation presents an opportunity for better representation of the sorption mechanism. © 2021 Elsevier B.V. |
---|