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Gbenga Thompson Awojinrin · Peerford

University of Ibadan / Scholars

GA

Gbenga Thompson Awojinrin

University of Ibadan

Publishing since 2022, latest 2024

Mechanical Engineering
Ocean Engineering

ORCID 0000-0003-2760-5408
Their record on OpenAlex
Download CV:PDF Word
Who they write with Where their co-authors are Every publication
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Publications: 22022–2024
Citations: 14to those papers
h-index: 2i10-index 1
Field-weighted impact: 4.241.00 is the world average
World top 10%: 50%1 of 2 scored papers
Open access: 0%0 papers free to read

By year

Papers, and the citations to them

Publications, left axisCitations to that year’s papers, right axis2026 still in progress

Citations received each year

Peerford

To all their work, old papers included. Google Scholar also counts citations from theses, books and web pages, so its line runs higher.

What they work on

From the classification of each paper

Subfields

Mechanical Engineering2100%

Publications

2 in all

Newest Most cited Oldest Title

Search their publications by title

Production Forecasting in Gas Lifted Wells using Interpretable Machine Learning Techniques
2024SPE Nigeria Annual International Conference and ExhibitionPublication2 citations10.2118/221631-ms
Machine Learning Workflow for the Determination of Hole Cleaning Conditions
2022SPE Annual Technical Conference and ExhibitionPublication

Ocean Engineering2100%

Physical Sciences

Topics most written on

Hydraulic Fracturing and Reservoir Analysis2
Reservoir Engineering and Simulation Methods2
Drilling and Well Engineering1
Oil and Gas Production Techniques1

Who they write with

Their most frequent co-authors, and the papers those co-authors share

Where they publish

SPE Annual Technical Conference and Exhibition1
SPE Nigeria Annual International Conference and Exhibition1

How it can be read

0% free to read

Closed 2 · 100%Behind a paywall

Most cited

Machine Learning Workflow for the Determination of Hole Cleaning Conditions
SPE Annual Technical Conference and Exhibition
202212 citationsWorld top 10%
Production Forecasting in Gas Lifted Wells using Interpretable Machine Learning Techniques
SPE Nigeria Annual International Conference and Exhibition
20242 citations

First author

Corresponding

12 citations

10.2118/212381-stu