Evidence map›Paper›PMID 35010052›Full record

ArticleNanomaterials (Basel, Switzerland)2021

Experimental Pore-Scale Study of a Novel Functionalized Iron-Carbon Nanohybrid for Enhanced Oil Recovery (EOR).

Fatemeh Razavirad, Abbas Shahrabadi, Parham Babakhani Dehkordi, Alimorad Rashidi

Abstract read
In one paragraph

Article in Nanomaterials (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

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4 · The record

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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Fatemeh RazaviradResearch Institute of Petroleum Industry, Tehran 1485613111, Iran.
Abbas ShahrabadiResearch Institute of Petroleum Industry, Tehran 1485613111, Iran.
Parham Babakhani DehkordiResearch Institute of Petroleum Industry, Tehran 1485613111, Iran.
Alimorad RashidiResearch Institute of Petroleum Industry, Tehran 1485613111, Iran.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Nanofluid flooding, as a new technique to enhance oil recovery, has recently aroused much attention. The current study considers the performance of a novel iron-carbon nanohybrid to EOR. Carbon nanoparticles was synthesized via the hydrothermal method with citric acid and hybridize with iron (Fe3O4). The investigated nanohybrid is characterized by its rheological properties (viscosity), X-ray diffraction (XRD), and Fourier transform infrared spectroscopy (FTIR) analysis. The efficiency of the synthetized nanoparticle in displacing heavy oil is initially assessed using an oil-wet glass micromodel at ambient conditions. Nanofluid samples with various concentrations (0.05 wt % and 0.5 wt %) dispersed in a water base fluid with varied salinities were first prepared. The prepared nanofluids provide high stability with no additive such as polymer or surfactant. Before displacement experiments were run, to achieve a better understanding of fluid-fluid and grain-fluid interactions in porous media, a series of sub-pore scale tests-including interfacial tension (IFT), contact angle, and zeta potential-were conducted. Nanofluid flooding results show that the nanofluid with the medium base fluid salinity and highest nanoparticle concertation provides the highest oil recovery. However, it is observed that increasing the nanofluid concentration from 0.05% to 0.5% provided only three percent more oil. In contrast, the lowest oil recovery resulted from low salinity water flooding. It was also observed that the measured IFT value between nanofluids and crude oil is a function of nanofluid concentration and base fluid salinities, i.e., the IFT values decrease with the increase of nanofluid concentration and base fluid salinity reduction. However, the base fluid salinity enhancement leads to wettability alteration towards more water-wetness. The main mechanisms responsible for oil recovery enhancement during nanofluid flooding is mainly attributed to wettability alteration toward water-wetness and micro-dispersion formation. However, the interfacial tension (IFT) reduction using the iron-carbon nanohybrid is also observed but the reduction is not significant.

Indexed as

alterationenhanced oil recoveryheavy oiliron-carbon nanohybridoil-wet micromodelwettability

Identifiers

PMID35010052
PMCPMC8746808

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.