Evidence map›Paper›PMID 37251148›Full record

ArticleACS omega2023

Corrosion Inhibition of Carbon Steel in a Sour (H

Muhammad Imran Ulhaq, Qasim Saleem, Hassan Ajwad, Rashed M Aleisa, Nayef M Alanazi, Matteo Leoni, Ibrahim Zahrani, Taras Makogon

Abstract read
In one paragraph

Article in ACS omega, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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

1 citing paper in PubMed.

  1. 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

8 authors.

Muhammad Imran UlhaqSaudi Aramco, Research and Development Center, Dhahran 31311, Saudi Arabia.ORCID https://orcid.org/0000-0003-2600-0319
Qasim SaleemSaudi Aramco, Research and Development Center, Dhahran 31311, Saudi Arabia.
Hassan AjwadSaudi Aramco, Research and Development Center, Dhahran 31311, Saudi Arabia.
Rashed M AleisaSaudi Aramco, Research and Development Center, Dhahran 31311, Saudi Arabia.
Nayef M AlanaziSaudi Aramco, Research and Development Center, Dhahran 31311, Saudi Arabia.
Matteo LeoniSaudi Aramco, Research and Development Center, Dhahran 31311, Saudi Arabia.
Ibrahim ZahraniSaudi Aramco, Research and Development Center, Dhahran 31311, Saudi Arabia.
Taras MakogonSaudi Aramco, Research and Development Center, Dhahran 31311, Saudi Arabia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Corrosion poses safety and operational challenges in the oil and gas field, particularly in a sour environment. Corrosion inhibitors (CIs) are thus employed to protect the integrity of industrial assets. However, CIs have the potential to dramatically impair the effectiveness of other co-additives, such as kinetic hydrate inhibitors (KHIs). Here, we propose an acryloyl-based copolymer, previously used as a KHI, as an effective CI. The copolymer formulation provided a corrosion inhibition efficiency of up to 90% in a gas production environment, implying that it can reduce or even eliminate the need for an additional dedicated CI in the system. It also demonstrated a corrosion inhibition efficiency of up to 60% under field-simulated conditions for a wet sour crude processing environment. Molecular modeling suggests that the enhanced corrosion protection is imparted by the favorable interaction of the heteroatoms of the copolymer with the steel surface, potentially displacing adhered water molecules. All in all, we show that an acryloyl-based copolymer with dual functionalities can potentially overcome issues caused by incompatibilities in a sour environment, resulting in significant cost savings and operational ease.

Identifiers

PMID37251148
PMCPMC10210039

What OpenQuestion holds

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LicenceCC BY-NC-ND
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.