Qamar Yasin

1.5k total citations
57 papers, 1.2k citations indexed

About

Qamar Yasin is a scholar working on Mechanical Engineering, Mechanics of Materials and Ocean Engineering. According to data from OpenAlex, Qamar Yasin has authored 57 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 40 papers in Mechanical Engineering, 39 papers in Mechanics of Materials and 32 papers in Ocean Engineering. Recurrent topics in Qamar Yasin's work include Hydraulic Fracturing and Reservoir Analysis (39 papers), Hydrocarbon exploration and reservoir analysis (35 papers) and Seismic Imaging and Inversion Techniques (22 papers). Qamar Yasin is often cited by papers focused on Hydraulic Fracturing and Reservoir Analysis (39 papers), Hydrocarbon exploration and reservoir analysis (35 papers) and Seismic Imaging and Inversion Techniques (22 papers). Qamar Yasin collaborates with scholars based in China, Pakistan and Canada. Qamar Yasin's co-authors include Qizhen Du, Ghulam Mohyuddin Sohail, Atif Ismail, Hung Vo Thanh, Kang‐Kun Lee, Watheq J. Al‐Mudhafar, Naser Golsanami, Perveiz Khalid, Umar Ashraf and Bo Liu and has published in prestigious journals such as SHILAP Revista de lepidopterología, Scientific Reports and Applied Energy.

In The Last Decade

Qamar Yasin

56 papers receiving 1.2k citations

Peers

Qamar Yasin
Xiaojiao Pang China
Lei Gong China
Zhibo He China
Xuqiang Fan China
Hongyan Yu China
Naser Golsanami China
Piroska Lorinczi United Kingdom
Xiaojiao Pang China
Qamar Yasin
Citations per year, relative to Qamar Yasin Qamar Yasin (= 1×) peers Xiaojiao Pang

Countries citing papers authored by Qamar Yasin

Since Specialization
Citations

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

Fields of papers citing papers by Qamar Yasin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Qamar Yasin

This figure shows the co-authorship network connecting the top 25 collaborators of Qamar Yasin. A scholar is included among the top collaborators of Qamar Yasin 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 Qamar Yasin. Qamar Yasin 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.
Liu, Bo, Y. Ma, Qamar Yasin, et al.. (2025). Characterization of lacustrine shale oil reservoirs based on a hybrid deep learning model: A data-driven approach to predict lithofacies, vitrinite reflectance, and TOC. Marine and Petroleum Geology. 174. 107309–107309. 6 indexed citations
2.
Yasin, Qamar, Bo Liu, Mengdi Sun, et al.. (2025). Digital core modeling for multimineral segmentation of lacustrine shale oil using FE-SEM and KiU-Net. Fuel. 398. 135474–135474. 2 indexed citations
3.
Awan, Rizwan Sarwar, et al.. (2025). Paleoenvironmental conditions and key drivers of organic matter accumulation in the early cretaceous Talhar Shale, Lower Indus Basin, Pakistan. Journal of Asian Earth Sciences. 292. 106716–106716. 1 indexed citations
4.
Saleem, Muhammad Shoaib, et al.. (2025). Multiple machine learning algorithms for lithofacies prediction in the deltaic depositional system of the lower Goru Formation, Lower Indus Basin, Pakistan. Scientific Reports. 15(1). 34933–34933. 1 indexed citations
5.
Rehman, Khaista, et al.. (2024). A reappraisal of Mesozoic-Cenozoic sequence stratigraphy in Offshore Indus Basin, Pakistan. Kuwait Journal of Science. 52(1). 100338–100338. 1 indexed citations
6.
7.
Liu, Bo, Qamar Yasin, Mengdi Sun, et al.. (2024). An improved convolutional architecture for quantitative characterization of pore networks in fine-grained rocks using FIB-SEM. International Journal of Coal Geology. 295. 104625–104625. 10 indexed citations
8.
Yasin, Qamar, Ali Gholami, Mariusz Majdański, Bo Liu, & Naser Golsanami. (2023). Seismic characterization of geologically complex geothermal reservoirs by combining structure-oriented filtering and attributes analysis. Geothermics. 112. 102749–102749. 7 indexed citations
9.
Sohail, Ghulam Mohyuddin, Qamar Yasin, Ahmed E. Radwan, & Muhammad Zaka Emad. (2023). Estimating hardness and Young's modulus of shale using drill cuttings: Implications for hydraulic fracturing in shale gas reservoir development. Gas Science and Engineering. 118. 205116–205116. 15 indexed citations
10.
Liu, Bo, Qamar Yasin, Ghulam Mohyuddin Sohail, et al.. (2023). Seismic characterization of fault and fractures in deep buried carbonate reservoirs using CNN-LSTM based deep neural networks. Geoenergy Science and Engineering. 229. 212126–212126. 12 indexed citations
11.
Yasin, Qamar, Bo Liu, Mengdi Sun, et al.. (2023). Automatic pore structure analysis in organic-rich shale using FIB-SEM and attention U-Net. Fuel. 358. 130161–130161. 24 indexed citations
12.
Ismail, Atif, et al.. (2023). Identification of natural fractures in shale gas reservoirs using fracture signature function and machine learning models. SHILAP Revista de lepidopterología. 4. 100069–100069. 7 indexed citations
13.
Yasin, Qamar, et al.. (2022). Evaluation of Neoproterozoic source rock potential in SE Pakistan and adjacent Bikaner–Nagaur Basin India. Scientific Reports. 12(1). 11102–11102. 9 indexed citations
14.
Liu, Bo, Yi Wang, Shansi Tian, et al.. (2022). Impact of thermal maturity on the diagenesis and porosity of lacustrine oil-prone shales: Insights from natural shale samples with thermal maturation in the oil generation window. International Journal of Coal Geology. 261. 104079–104079. 68 indexed citations
15.
Ding, Yan, Meng Cui, Fei Zhao, et al.. (2021). A Novel Neural Network for Seismic Anisotropy and Fracture Porosity Measurements in Carbonate Reservoirs. Arabian Journal for Science and Engineering. 47(6). 7219–7241. 11 indexed citations
16.
Sohail, Ghulam Mohyuddin, Chris Hawkes, & Qamar Yasin. (2020). An integrated petrophysical and geomechanical characterization of Sembar Shale in the Lower Indus Basin, Pakistan, using well logs and seismic data. Journal of Natural Gas Science and Engineering. 78. 103327–103327. 31 indexed citations
17.
Zhang, Qiang, Qamar Yasin, Naser Golsanami, & Qizhen Du. (2020). Prediction of Reservoir Quality from Log-Core and Seismic Inversion Analysis with an Artificial Neural Network: A Case Study from the Sawan Gas Field, Pakistan. Energies. 13(2). 486–486. 53 indexed citations
18.
Yasin, Qamar, et al.. (2020). Application of machine learning tool to predict the porosity of clastic depositional system, Indus Basin, Pakistan. Journal of Petroleum Science and Engineering. 197. 107975–107975. 49 indexed citations
19.
Zhao, Qiang, et al.. (2019). Quaternion-based sparse tight frame for multicomponent signal recovery. Geophysics. 85(2). V143–V156. 3 indexed citations
20.

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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