Julius U. Akpabio

758 total citations
25 papers, 535 citations indexed

About

Julius U. Akpabio is a scholar working on Ocean Engineering, Mechanical Engineering and Civil and Structural Engineering. According to data from OpenAlex, Julius U. Akpabio has authored 25 papers receiving a total of 535 indexed citations (citations by other indexed papers that have themselves been cited), including 24 papers in Ocean Engineering, 18 papers in Mechanical Engineering and 7 papers in Civil and Structural Engineering. Recurrent topics in Julius U. Akpabio's work include Hydraulic Fracturing and Reservoir Analysis (17 papers), Reservoir Engineering and Simulation Methods (15 papers) and Drilling and Well Engineering (12 papers). Julius U. Akpabio is often cited by papers focused on Hydraulic Fracturing and Reservoir Analysis (17 papers), Reservoir Engineering and Simulation Methods (15 papers) and Drilling and Well Engineering (12 papers). Julius U. Akpabio collaborates with scholars based in Nigeria. Julius U. Akpabio's co-authors include Okorie Ekwe Agwu, Adewale Dosunmu, Udoinyang G. Inyang, Imo Eyoh, Moses E. Ekpenyong and Anietie N. Okon and has published in prestigious journals such as Powder Technology, Journal of Petroleum Science and Engineering and Heliyon.

In The Last Decade

Julius U. Akpabio

22 papers receiving 518 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Julius U. Akpabio Nigeria 12 397 306 151 50 49 25 535
Luís Américo Calçada Brazil 13 347 0.9× 303 1.0× 96 0.6× 43 0.9× 47 1.0× 60 508
Okorie Ekwe Agwu Nigeria 15 495 1.2× 383 1.3× 177 1.2× 72 1.4× 71 1.4× 41 708
Cláudia Míriam Scheid Brazil 13 333 0.8× 287 0.9× 91 0.6× 52 1.0× 44 0.9× 61 491
Adewale Dosunmu Nigeria 11 438 1.1× 359 1.2× 117 0.8× 43 0.9× 88 1.8× 86 593
Rahul Gajbhiye Saudi Arabia 15 538 1.4× 321 1.0× 192 1.3× 82 1.6× 147 3.0× 75 681
Antonio Rodríguez de Castro France 14 249 0.6× 244 0.8× 58 0.4× 37 0.7× 91 1.9× 30 478
Mohsen Talebkeikhah Iran 12 250 0.6× 320 1.0× 71 0.5× 169 3.4× 96 2.0× 17 573
Oyinkepreye D. Orodu Nigeria 13 389 1.0× 253 0.8× 95 0.6× 54 1.1× 146 3.0× 72 564
Mojtaba P. Shahri United States 17 864 2.2× 667 2.2× 121 0.8× 34 0.7× 215 4.4× 66 948
Saeed Khezerloo‐ye Aghdam Iran 12 317 0.8× 265 0.9× 99 0.7× 39 0.8× 127 2.6× 16 504

Countries citing papers authored by Julius U. Akpabio

Since Specialization
Citations

This map shows the geographic impact of Julius U. Akpabio's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Julius U. Akpabio with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Julius U. Akpabio more than expected).

Fields of papers citing papers by Julius U. Akpabio

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Julius U. Akpabio. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Julius U. Akpabio. The network helps show where Julius U. Akpabio may publish in the future.

Co-authorship network of co-authors of Julius U. Akpabio

This figure shows the co-authorship network connecting the top 25 collaborators of Julius U. Akpabio. A scholar is included among the top collaborators of Julius U. Akpabio based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Julius U. Akpabio. Julius U. Akpabio is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Akpabio, Julius U., et al.. (2023). Drilling fluid design for depleted zone drilling: An integrated review of laboratory, field, modelling and cost studies. Geoenergy Science and Engineering. 226. 211706–211706. 5 indexed citations
2.
Akpabio, Julius U., et al.. (2023). The Use of Machine Learning in Oil Well Petrophysics and Original Oil in Place Estimation: A Systematic Literature Review Approach. Journal of Engineering Research and Reports. 25(6). 40–54. 3 indexed citations
3.
Akpabio, Julius U., et al.. (2023). Machine Learning-Based Models for Basic Sediment & Water and Sand-Cut Prediction in Matured Niger Delta Fields. Journal of Energy Research and Reviews. 15(2). 70–93. 1 indexed citations
4.
Agwu, Okorie Ekwe, et al.. (2021). A critical review of drilling mud rheological models. Journal of Petroleum Science and Engineering. 203. 108659–108659. 72 indexed citations
5.
Agwu, Okorie Ekwe, et al.. (2021). A comprehensive review of laboratory, field and modelling studies on drilling mud rheology in high temperature high pressure (HTHP) conditions. Journal of Natural Gas Science and Engineering. 94. 104046–104046. 50 indexed citations
6.
Agwu, Okorie Ekwe, Julius U. Akpabio, & Adewale Dosunmu. (2021). Modeling the downhole density of drilling muds using multigene genetic programming. 6. 100030–100030. 7 indexed citations
7.
Akpabio, Julius U., et al.. (2021). Comparison of Three Artificial Lift Operations in the Niger Delta. Current Journal of Applied Science and Technology. 97–116.
8.
Agwu, Okorie Ekwe, et al.. (2020). Potentials of waste seashells as additives in drilling muds and in oil well cements. Cleaner Engineering and Technology. 1. 100008–100008. 16 indexed citations
9.
Akpabio, Julius U., et al.. (2020). Evaluating the Challenges in Pressure – Volume – Temperature (PVT) Analysis of Gas Condensate Reservoirs. Journal of Engineering Research and Reports. 13–18. 1 indexed citations
10.
Okon, Anietie N., et al.. (2020). Evaluating the locally sourced materials as fluid loss control additives in water-based drilling fluid. Heliyon. 6(5). e04091–e04091. 28 indexed citations
11.
Akpabio, Julius U., et al.. (2020). Economic Analysis of Gas Reinjection for Enhanced Oil Recovery: A Case Study of the Niger Delta. Journal of Engineering Research and Reports. 48–64. 1 indexed citations
12.
Akpabio, Julius U., et al.. (2020). Digital Transformation: After the Big Data, What Next?. SPE Nigeria Annual International Conference and Exhibition. 1 indexed citations
13.
Agwu, Okorie Ekwe, Julius U. Akpabio, & Adewale Dosunmu. (2019). Artificial neural network model for predicting the density of oil-based muds in high-temperature, high-pressure wells. Journal of Petroleum Exploration and Production Technology. 10(3). 1081–1095. 37 indexed citations
14.
Agwu, Okorie Ekwe, et al.. (2019). Rice husk and saw dust as filter loss control agents for water-based muds. Heliyon. 5(7). e02059–e02059. 33 indexed citations
15.
Agwu, Okorie Ekwe, et al.. (2018). Artificial intelligence techniques and their applications in drilling fluid engineering: A review. Journal of Petroleum Science and Engineering. 167. 300–315. 108 indexed citations
16.
Agwu, Okorie Ekwe, et al.. (2018). Settling velocity of drill cuttings in drilling fluids: A review of experimental, numerical simulations and artificial intelligence studies. Powder Technology. 339. 728–746. 50 indexed citations
17.
Okon, Anietie N., et al.. (2017). Water Coning Prediction Review and Control: Developing an Integrated Approach. Journal of Scientific Research and Reports. 14(4). 1–24. 12 indexed citations
18.
Okon, Anietie N., et al.. (2017). Rate Decline-based Models for Gas Reservoir Performance Prediction in Niger Delta Region. British Journal of Applied Science & Technology. 19(1). 1–14. 1 indexed citations
19.
Akpabio, Julius U., et al.. (2015). PVT Fluid Sampling, Characterization and Gas Condensate Reservoir Modeling. Advances in Research. 5(5). 1–11. 3 indexed citations
20.
Akpabio, Julius U., et al.. (2013). INTERNATIONAL JOURNA L OF ENGINEERING SCI ENCES & RESEARCH TECHNOLOGY Horizontal Well Performance in Thin Oil Rim Reservoirs. 3 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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