Document Type

Journal Article

Publication Title

Scientific Reports

Volume

12

Issue

1

PubMed ID

35075172

Publisher

Nature

School

School of Engineering

RAS ID

52090

Funders

Ministry of Education and Science of the Russian Federation (075-10-2020-119)

Comments

Ivanova, A., Orekhov, A., Markovic, S., Iglauer, S., Grishin, P., & Cheremisin, A. (2022). Live imaging of micro and macro wettability variations of carbonate oil reservoirs for enhanced oil recovery and CO2 trapping/storage. Scientific Reports, 12(1), 1-12. https://doi.org/10.1038/s41598-021-04661-2

Abstract

Carbonate hydrocarbon reservoirs are considered as potential candidates for chemically enhanced oil recovery and for CO² geological storage. However, investigation of one main controlling parameter—wettability—is usually performed by conventional integral methods at the core-scale. Moreover, literature reports show that wettability distribution may vary at the micro-scale due to the chemical heterogeneity of the reservoir and residing fluids. These differences may profoundly affect the derivation of other reservoir parameters such as relative permeability and capillary pressure, thus rendering subsequent simulations inaccurate. Here we developed an innovative approach by comparing the wettability distribution on carbonates at micro and macro-scale by combining live-imaging of controlled condensation experiments and X-ray mapping with sessile drop technique. The wettability was quantified by measuring the differences in contact angles before and after aging in palmitic, stearic and naphthenic acids. Furthermore, the influence of organic acids on wettability was examined at micro-scale, which revealed wetting heterogeneity of the surface (i.e., mixed wettability), while corresponding macro-scale measurements indicated hydrophobic wetting properties. The thickness of the adsorbed acid layer was determined, and it was correlated with the wetting properties. These findings bring into question the applicability of macro-scale data in reservoir modeling for enhanced oil recovery and geological storage of greenhouse gases.

DOI

10.1038/s41598-021-04661-2

Creative Commons License

Creative Commons Attribution 4.0 License
This work is licensed under a Creative Commons Attribution 4.0 License.

Share

 
COinS