Evidence map›Paper›PMID 35457953›Full record

ArticleNanomaterials (Basel, Switzerland)2022

Date-Leaf Carbon Particles for Green Enhanced Oil Recovery.

Bashirul Haq, Md Abdul Aziz, Dhafer Al Shehri, Nasiru Salahu Muhammed, Shaik Inayath Basha, Abbas Saeed Hakeem, Mohammed Ameen Ahmed Qasem, Mohammed Lardhi, Stefan Iglauer

Open access · goldAbstract read
In one paragraph

Article in Nanomaterials (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
3.1field-weighted citation impact, top 8% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed, 35 citations in OpenAlex.

  1. Article
  2. Review
  3. Review
  4. Phytogenic nanoparticles: synthesis, characterization, and their roles in physiology and biochemistry of plants.Biometals : an international journal on the role of metal ions in biology, biochemistry, and medicine · 2024
    Review
  5. Review
  6. Nanomaterials for Catalysis and Energy Storage.Nanomaterials (Basel, Switzerland) · 2023
    Article
4 · The record

Corrections and comments

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

9 authors at 3 institutions in 3 countries.

Bashirul HaqDepartment of Petroleum Engineering, King Fahd University of Petroleum and Minerals, Dhahran 31261, Saudi Arabia.ORCID 0000-0003-1414-9976
Md Abdul AzizInterdisciplinary Research Center for Hydrogen and Energy Storage, King Fahd University of Petroleum and Minerals, Dhahran 31261, Saudi Arabia.ORCID 0000-0002-1537-2785
Dhafer Al ShehriDepartment of Petroleum Engineering, King Fahd University of Petroleum and Minerals, Dhahran 31261, Saudi Arabia.ORCID 0000-0002-7032-5199
Nasiru Salahu MuhammedDepartment of Petroleum Engineering, King Fahd University of Petroleum and Minerals, Dhahran 31261, Saudi Arabia.
Shaik Inayath BashaDepartment of Civil and Environmental Engineering, King Fahd University of Petroleum and Minerals, Dhahran 31261, Saudi Arabia.
Abbas Saeed HakeemInterdisciplinary Research Center for Hydrogen and Energy Storage, King Fahd University of Petroleum and Minerals, Dhahran 31261, Saudi Arabia.ORCID 0000-0003-1422-442X
Mohammed Ameen Ahmed QasemInterdisciplinary Research Center for Hydrogen and Energy Storage, King Fahd University of Petroleum and Minerals, Dhahran 31261, Saudi Arabia.
Mohammed LardhiDepartment of Reservoir Geoscience and Engineering, IFP School, 69 Avenue Paul Doumer, 92500 Rueil-Malmaison, France.ORCID 0000-0002-4644-354X
Stefan IglauerSchool of Engineering, Edith Cowan University, 270 Joondalup Drive, Joondalup, WA 6027, Australia.
King Fahd University of Petroleum and Minerals · SAEdith Cowan University · AUIFP Énergies nouvelles · FR

Funding

CPG Start-Up Fund SF19005
6 · The paper itself

Abstract

Green enhanced oil recovery (GEOR) is an environmentally friendly enhanced oil recovery (EOR) process involving the injection of green fluids to improve macroscopic and microscopic sweep efficiencies while boosting tertiary oil production. Carbon nanomaterials such as graphene, carbon nanotube (CNT), and carbon dots have gained interest for their superior ability to increase oil recovery. These particles have been successfully tested in EOR, although they are expensive and do not extend to GEOR. In addition, the application of carbon particles in the GEOR method is not well understood yet, requiring thorough documentation. The goals of this work are to develop carbon nanoparticles from biomass and explore their role in GEOR. The carbon nanoparticles were prepared from date leaves, which are inexpensive biomass, through pyrolysis and ball-milling methods. The synthesized carbon nanomaterials were characterized using the standard process. Three formulations of functionalized and non-functionalized date-leaf carbon nanoparticle (DLCNP) solutions were chosen for core floods based on phase behavior and interfacial tension (IFT) properties to examine their potential for smart water and green chemical flooding. The carboxylated DLCNP was mixed with distilled water in the first formulation to be tested for smart water flood in the sandstone core. After water flooding, this formulation recovered 9% incremental oil of the oil initially in place. In contrast, non-functionalized DLCNP formulated with (the biodegradable) surfactant alkyl polyglycoside and NaCl produced 18% more tertiary oil than the CNT. This work thus provides new green chemical agents and formulations for EOR applications so that oil can be produced more economically and sustainably.

Indexed as

ball millingcarbon nanoparticlecarboxylic acid functionalizationdate leavesgreen enhanced oil recovery (GEOR)pyrolysissmart water flooding

Identifiers

PMID35457953
PMCPMC9029107
OpenAlexW4224244981

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.