Akhil Datta‐Gupta

11.5k total citations
330 papers, 6.8k citations indexed

About

Akhil Datta‐Gupta is a scholar working on Ocean Engineering, Mechanical Engineering and Environmental Engineering. According to data from OpenAlex, Akhil Datta‐Gupta has authored 330 papers receiving a total of 6.8k indexed citations (citations by other indexed papers that have themselves been cited), including 284 papers in Ocean Engineering, 238 papers in Mechanical Engineering and 84 papers in Environmental Engineering. Recurrent topics in Akhil Datta‐Gupta's work include Reservoir Engineering and Simulation Methods (278 papers), Hydraulic Fracturing and Reservoir Analysis (236 papers) and Seismic Imaging and Inversion Techniques (78 papers). Akhil Datta‐Gupta is often cited by papers focused on Reservoir Engineering and Simulation Methods (278 papers), Hydraulic Fracturing and Reservoir Analysis (236 papers) and Seismic Imaging and Inversion Techniques (78 papers). Akhil Datta‐Gupta collaborates with scholars based in United States, Netherlands and United Kingdom. Akhil Datta‐Gupta's co-authors include Micháel J. King, D. W. Vasco, Seongsik Yoon, Ahmed H. Alhuthali, Changdong Yang, Hao Cheng, Yalchin Efendiev, Sang‐Heon Lee, Jiang Xie and Tsubasa Onishi and has published in prestigious journals such as Technometrics, Water Resources Research and Fuel.

In The Last Decade

Akhil Datta‐Gupta

321 papers receiving 6.3k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Akhil Datta‐Gupta United States 43 5.7k 4.9k 1.6k 1.3k 942 330 6.8k
Roland N. Horne United States 45 5.4k 1.0× 5.3k 1.1× 1.7k 1.0× 1.3k 1.1× 1.8k 1.9× 363 7.9k
Albert C. Reynolds United States 54 9.7k 1.7× 7.8k 1.6× 2.0k 1.2× 1.7k 1.4× 646 0.7× 260 10.8k
Hossein Kazemi United States 36 4.9k 0.9× 5.0k 1.0× 1.5k 0.9× 828 0.7× 2.5k 2.6× 247 6.8k
Stephan K. Matthäi Australia 38 1.9k 0.3× 1.8k 0.4× 1.5k 0.9× 954 0.8× 1.6k 1.7× 136 4.0k
D. W. Vasco United States 40 2.0k 0.4× 1.7k 0.4× 1.6k 1.0× 2.7k 2.2× 748 0.8× 164 4.6k
Khalid Aziz United States 47 6.6k 1.2× 6.0k 1.2× 1.3k 0.8× 516 0.4× 1.2k 1.3× 242 10.0k
Erik H. Saenger Germany 34 2.4k 0.4× 1.2k 0.2× 324 0.2× 2.8k 2.3× 1.6k 1.7× 166 4.5k
J. Jaime Gómez‐Hernández Spain 38 1.8k 0.3× 920 0.2× 3.7k 2.2× 1.1k 0.9× 339 0.4× 140 4.9k
John Killough United States 32 2.5k 0.4× 2.2k 0.5× 658 0.4× 414 0.3× 1.4k 1.5× 161 3.4k
T. A. Blasingame United States 41 4.4k 0.8× 4.5k 0.9× 586 0.4× 484 0.4× 2.1k 2.3× 206 5.4k

Countries citing papers authored by Akhil Datta‐Gupta

Since Specialization
Citations

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

Fields of papers citing papers by Akhil Datta‐Gupta

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Akhil Datta‐Gupta. 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 Akhil Datta‐Gupta. The network helps show where Akhil Datta‐Gupta may publish in the future.

Co-authorship network of co-authors of Akhil Datta‐Gupta

This figure shows the co-authorship network connecting the top 25 collaborators of Akhil Datta‐Gupta. A scholar is included among the top collaborators of Akhil Datta‐Gupta 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 Akhil Datta‐Gupta. Akhil Datta‐Gupta 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.
Nagao, M., Akhil Datta‐Gupta, Tsubasa Onishi, & Sathish Sankaran. (2024). Physics Informed Machine Learning for Reservoir Connectivity Identification and Robust Production Forecasting. SPE Journal. 29(9). 4527–4541. 7 indexed citations
2.
Nagao, M., et al.. (2024). An efficient deep learning-based workflow for real-time CO2 plume visualization in saline aquifer using distributed pressure and temperature measurements. Geoenergy Science and Engineering. 239. 212990–212990. 6 indexed citations
3.
Chen, Hongquan, et al.. (2023). High Resolution Modeling of Pore Pressure Change, Fault Slip Potential and Induced Seismicity in the Fort Worth Basin. SPE Western Regional Meeting. 1 indexed citations
4.
Chen, Hongquan, et al.. (2021). Machine learning based rate optimization under geologic uncertainty. Journal of Petroleum Science and Engineering. 207. 109116–109116. 28 indexed citations
5.
Datta‐Gupta, Akhil, et al.. (2019). Multi-resolution Grid Connectivity-Based Reparameterization for Effective Subsurface Model Calibration. Transport in Porous Media. 129(1). 149–177. 2 indexed citations
6.
Zhang, Zheng, Hye Young Jung, Akhil Datta‐Gupta, & Mojdeh Delshad. (2019). History Matching and Optimal Design of Chemically Enhanced Oil Recovery Using Multi-Objective Optimization. SPE Reservoir Simulation Conference. 3 indexed citations
7.
Gao, Kai, et al.. (2012). Streamline-based integration of time-lapse seismic and production data into petroleum reservoir models. Geophysics. 77(6). M73–M87. 14 indexed citations
8.
Kippe, Vegard, et al.. (2008). Multiscale-Streamline Simulation and Dynamic Data Integration for High-Resolution Subsurface Models. Water Resources Research. 1 indexed citations
9.
Alhuthali, Ahmed H., et al.. (2007). Optimal Waterflood Management Using Rate Control. SPE Reservoir Evaluation & Engineering. 10(5). 539–551. 102 indexed citations
10.
Alhuthali, Ahmed H., et al.. (2006). Optimal Waterflood Management Using Rate Control. Proceedings of SPE Annual Technical Conference and Exhibition. 8 indexed citations
11.
Vasco, D. W., et al.. (2004). Seismic imaging of reservoir flow properties: Time-lapse amplitude changes. Geophysics. 69(6). 1425–1442. 58 indexed citations
12.
13.
Datta‐Gupta, Akhil, et al.. (2004). Streamline-Based Production Data Integration in Naturally Fractured Reservoirs. Proceedings of SPE Annual Technical Conference and Exhibition. 1 indexed citations
14.
Cheng, Hao, et al.. (2003). A Comparison of Travel-Time and Amplitude Matching for Field-Scale Production Data Integration: Sensitivity, Non-Linearity and Practical Implications. Proceedings of SPE Annual Technical Conference and Exhibition. 1 indexed citations
15.
Lee, Sang‐Heon, Adel Malallah, Akhil Datta‐Gupta, & David Higdon. (2002). Multiscale Data Integration Using Markov Random Fields. SPE Reservoir Evaluation & Engineering. 5(1). 68–78. 16 indexed citations
16.
Vasco, D. W. & Akhil Datta‐Gupta. (2001). Asymptotics, streamlines, and reservoir modeling: A pathway to production tomography. The Leading Edge. 20(10). 1164–1171. 7 indexed citations
17.
Wu, Zhan & Akhil Datta‐Gupta. (2001). Rapid History Matching Using a Generalized Travel Time Inversion Method. Proceedings of SPE Reservoir Simulation Symposium. 1 indexed citations
18.
Datta‐Gupta, Akhil & D. W. Vasco. (2001). Production tomography merges geophysics with reservoir engineering. Oil & gas journal. 99(23). 2 indexed citations
19.
Datta‐Gupta, Akhil, et al.. (2000). Streamlines, ray tracing and production tomography: generalization to compressible flow. Petroleum Geoscience. 7. 54 indexed citations
20.
Majer, Ernest L., Akhil Datta‐Gupta, D. W. Vasco, et al.. (1996). Utilizing crosswell, single well and pressure transient tests for characterizing fractured gas reservoirs. The Leading Edge. 15(8). 951–956. 9 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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