Mohammad Anemangely

794 total citations
8 papers, 645 citations indexed

About

Mohammad Anemangely is a scholar working on Ocean Engineering, Mechanical Engineering and Geophysics. According to data from OpenAlex, Mohammad Anemangely has authored 8 papers receiving a total of 645 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Ocean Engineering, 7 papers in Mechanical Engineering and 2 papers in Geophysics. Recurrent topics in Mohammad Anemangely's work include Drilling and Well Engineering (8 papers), Hydraulic Fracturing and Reservoir Analysis (7 papers) and Mineral Processing and Grinding (3 papers). Mohammad Anemangely is often cited by papers focused on Drilling and Well Engineering (8 papers), Hydraulic Fracturing and Reservoir Analysis (7 papers) and Mineral Processing and Grinding (3 papers). Mohammad Anemangely collaborates with scholars based in Iran and United Kingdom. Mohammad Anemangely's co-authors include Ahmad Ramezanzadeh, Behzad Tokhmechi, Mohammad Sabah, Mohammad Javad Ameri, David A. Wood, Rasool Khosravanian and Mohsen Talebkeikhah and has published in prestigious journals such as Journal of Petroleum Science and Engineering, Journal of Natural Gas Science and Engineering and Journal of Geophysics and Engineering.

In The Last Decade

Mohammad Anemangely

8 papers receiving 637 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Mohammad Anemangely Iran 8 486 428 175 124 119 8 645
Ahmad Ramezanzadeh Iran 17 604 1.2× 533 1.2× 373 2.1× 290 2.3× 150 1.3× 50 943
Atif Ismail Pakistan 13 277 0.6× 302 0.7× 269 1.5× 33 0.3× 157 1.3× 31 462
Makoto Naoi Japan 16 224 0.5× 232 0.5× 294 1.7× 44 0.4× 339 2.8× 40 601
Olalere Oloruntobi Canada 13 266 0.5× 218 0.5× 122 0.7× 35 0.3× 137 1.2× 16 368
Mohammad Islam Miah Bangladesh 9 196 0.4× 176 0.4× 149 0.9× 52 0.4× 50 0.4× 21 313
Jin Yang China 14 470 1.0× 326 0.8× 170 1.0× 87 0.7× 33 0.3× 70 643
M. Młynarczuk Poland 12 172 0.4× 206 0.5× 167 1.0× 46 0.4× 21 0.2× 41 403
Ruizhi Zhong Australia 13 457 0.9× 331 0.8× 408 2.3× 39 0.3× 33 0.3× 34 660
Tron Golder Kristiansen Norway 16 576 1.2× 507 1.2× 188 1.1× 69 0.6× 365 3.1× 74 755
Ramin Soltanmohammadi United States 9 158 0.3× 137 0.3× 130 0.7× 45 0.4× 48 0.4× 16 331

Countries citing papers authored by Mohammad Anemangely

Since Specialization
Citations

This map shows the geographic impact of Mohammad Anemangely'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 Mohammad Anemangely with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mohammad Anemangely more than expected).

Fields of papers citing papers by Mohammad Anemangely

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Mohammad Anemangely. 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 Mohammad Anemangely. The network helps show where Mohammad Anemangely may publish in the future.

Co-authorship network of co-authors of Mohammad Anemangely

This figure shows the co-authorship network connecting the top 25 collaborators of Mohammad Anemangely. A scholar is included among the top collaborators of Mohammad Anemangely 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 Mohammad Anemangely. Mohammad Anemangely is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

8 of 8 papers shown
1.
Sabah, Mohammad, et al.. (2019). A machine learning approach to predict drilling rate using petrophysical and mud logging data. Earth Science Informatics. 12(3). 319–339. 106 indexed citations
2.
Anemangely, Mohammad, et al.. (2018). Geomechanical parameter estimation from mechanical specific energy using artificial intelligence. Journal of Petroleum Science and Engineering. 175. 407–429. 56 indexed citations
3.
Anemangely, Mohammad, et al.. (2018). Application of hybrid artificial neural networks for predicting rate of penetration (ROP): A case study from Marun oil field. Journal of Petroleum Science and Engineering. 175. 604–623. 117 indexed citations
4.
Anemangely, Mohammad, et al.. (2018). Development of a new rock drillability index for oil and gas reservoir rocks using punch penetration test. Journal of Petroleum Science and Engineering. 166. 131–145. 28 indexed citations
5.
Anemangely, Mohammad, et al.. (2018). Drilling rate prediction from petrophysical logs and mud logging data using an optimized multilayer perceptron neural network. Journal of Geophysics and Engineering. 15(4). 1146–1159. 98 indexed citations
6.
Anemangely, Mohammad, et al.. (2018). Machine learning technique for the prediction of shear wave velocity using petrophysical logs. Journal of Petroleum Science and Engineering. 174. 306–327. 130 indexed citations
7.
Anemangely, Mohammad, Ahmad Ramezanzadeh, & Behzad Tokhmechi. (2017). Determination of constant coefficients of Bourgoyne and Young drilling rate model using a novel evolutionary algorithm. Journal of mining and environment. 8(4). 693–702. 25 indexed citations
8.
Anemangely, Mohammad, Ahmad Ramezanzadeh, & Behzad Tokhmechi. (2017). Shear wave travel time estimation from petrophysical logs using ANFIS-PSO algorithm: A case study from Ab-Teymour Oilfield. Journal of Natural Gas Science and Engineering. 38. 373–387. 85 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.

Explore authors with similar magnitude of impact

Breakdown of academic impact, for papers by Ahmad Ramezanzadeh Breakdown of academic impact, for papers by Atif Ismail Breakdown of academic impact, for papers by Makoto Naoi Breakdown of academic impact, for papers by Olalere Oloruntobi Breakdown of academic impact, for papers by Mohammad Islam Miah Breakdown of academic impact, for papers by Jin Yang Breakdown of academic impact, for papers by M. Młynarczuk Breakdown of academic impact, for papers by Ruizhi Zhong Breakdown of academic impact, for papers by Tron Golder Kristiansen Breakdown of academic impact, for papers by Ramin Soltanmohammadi
Rankless by CCL
2026