Lukas Mosser

943 total citations · 1 hit paper
19 papers, 637 citations indexed

About

Lukas Mosser is a scholar working on Ocean Engineering, Geophysics and Mechanical Engineering. According to data from OpenAlex, Lukas Mosser has authored 19 papers receiving a total of 637 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Ocean Engineering, 12 papers in Geophysics and 8 papers in Mechanical Engineering. Recurrent topics in Lukas Mosser's work include Seismic Imaging and Inversion Techniques (11 papers), Reservoir Engineering and Simulation Methods (10 papers) and Hydraulic Fracturing and Reservoir Analysis (7 papers). Lukas Mosser is often cited by papers focused on Seismic Imaging and Inversion Techniques (11 papers), Reservoir Engineering and Simulation Methods (10 papers) and Hydraulic Fracturing and Reservoir Analysis (7 papers). Lukas Mosser collaborates with scholars based in United Kingdom, Norway and Austria. Lukas Mosser's co-authors include Martin J. Blunt, Olivier Dubrule, Nigel P. Brandon, Samuel J. Cooper, Ehsan Zabihi Naeini, Jesper Dramsch, Gregor T. Baechle, O.P. Wennberg, Stephan K. Matthäi and Peder Aursand and has published in prestigious journals such as Geophysics, Geological Society London Special Publications and npj Computational Materials.

In The Last Decade

Lukas Mosser

19 papers receiving 620 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Reconstruction of three-dimensional porous media using generative adversarial neural networks

2017 388 citations Lukas Mosser, Olivier Dubrule et al. Physical review. E profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Lukas Mosser United Kingdom	8	280	190	169	147	142	19	637
Javier E. Santos United States	15	321 1.1×	89 0.5×	228 1.3×	46 0.3×	166 1.2×	57	659
Junxi Feng China	13	265 0.9×	146 0.8×	113 0.7×	284 1.9×	238 1.7×	15	684
Yibo Wang China	17	219 0.8×	412 2.2×	243 1.4×	45 0.3×	233 1.6×	103	843
Sébastien Leclaire Canada	17	154 0.6×	92 0.5×	353 2.1×	99 0.7×	72 0.5×	44	1.5k
Ronghua Peng China	14	243 0.9×	365 1.9×	86 0.5×	42 0.3×	56 0.4×	53	621
C. Manwart Germany	7	300 1.1×	57 0.3×	132 0.8×	55 0.4×	257 1.8×	8	620
Qizhi He United States	16	96 0.3×	70 0.4×	145 0.9×	17 0.1×	267 1.9×	39	1.0k
Zuyuan Liu China	13	282 1.0×	75 0.4×	101 0.6×	16 0.1×	96 0.7×	78	610
Jinlong Fu United Kingdom	10	145 0.5×	27 0.1×	114 0.7×	48 0.3×	150 1.1×	22	477

Countries citing papers authored by Lukas Mosser

Since Specialization

Citations

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

Fields of papers citing papers by Lukas Mosser

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Lukas Mosser

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

All Works

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19 of 19 papers shown

Mosser, Lukas, et al.. (2024). Exploration Robot Chat: Uncovering Decades of Exploration Knowledge and Data with Conversational Large Language Models. 5 indexed citations

Mosser, Lukas. (2023). Deep Diffusion Models for Facies Modeling. 1–5. 1 indexed citations

Mosser, Lukas & Ehsan Zabihi Naeini. (2022). A comprehensive study of calibration and uncertainty quantification for Bayesian convolutional neural networks — An application to seismic data. Geophysics. 87(4). IM157–IM176. 15 indexed citations

Mosser, Lukas, et al.. (2022). Interpretation of deep neural networks for carbonate thin section classification. Second International Meeting for Applied Geoscience & Energy. 371–375. 2 indexed citations

Mosser, Lukas, et al.. (2021). 3D Seismic Based Reservoir Property Prediction Using Deep Convolutional Neural Networks. 1–5. 3 indexed citations

Mosser, Lukas, et al.. (2021). Deep Bayesian Neural Networks for Fault Identification and Uncertainty Quantification. 1–5. 1 indexed citations

Mosser, Lukas, et al.. (2020). Stochastic reconstruction of periodic, three-dimensional multi-phase electrode microstructures using generative adversarial networks.. arXiv (Cornell University). 1 indexed citations

Mosser, Lukas, et al.. (2020). Uncertainty quantification for deep learning in geoscience applications. 1–3. 2 indexed citations

Mosser, Lukas, et al.. (2020). Deep Bayesian Neural Networks for Fault Identification and Uncertainty Quantification. 1–5. 10 indexed citations

10.

Mosser, Lukas, et al.. (2020). Pores for thought: generative adversarial networks for stochastic reconstruction of 3D multi-phase electrode microstructures with periodic boundaries. npj Computational Materials. 6(1). 124 indexed citations

11.

Mosser, Lukas, et al.. (2019). Investigating the AVO Signature of a North Sea Oil-Field Using Pseudo-Wells and Unsupervised Deep Learning. 81st EAGE Conference and Exhibition 2019. 1–5. 2 indexed citations

12.

Mosser, Lukas, Olivier Dubrule, & Martin J. Blunt. (2019). Deep Stochastic Inversion. 1–5. 1 indexed citations

13.

Mosser, Lukas, et al.. (2019). Probabilistic Seismic Interpretation Using Bayesian Neural Networks. 81st EAGE Conference and Exhibition 2019. 1–5. 12 indexed citations

14.

Mosser, Lukas, Olivier Dubrule, & Martin J. Blunt. (2019). Deep Stochastic Inversion. 81st EAGE Conference and Exhibition 2019. 1–5. 1 indexed citations

15.

Mosser, Lukas, Olivier Dubrule, & Martin J. Blunt. (2018). Conditioning of Generative Adversarial Networks for Pore and Reservoir Scale Models. Proceedings. 21 indexed citations

16.

Mosser, Lukas, et al.. (2018). Rapid Seismic Domain Transfer: Seismic Velocity Inversion and Modeling Using Deep Generative Neural Networks. Proceedings. 39 indexed citations

17.

Mosser, Lukas, Olivier Dubrule, & Martin J. Blunt. (2017). Reconstruction of three-dimensional porous media using generative adversarial neural networks. Physical review. E. 96(4). 43309–43309. 388 indexed citations breakdown →

18.

Wennberg, O.P., et al.. (2017). Well-data-based discrete fracture and matrix modelling and flow-based upscaling of multilayer carbonate reservoir horizons. Geological Society London Special Publications. 459(1). 191–210. 8 indexed citations

19.

Mosser, Lukas. (2013). Mapping Geo-Cellular Models to Unstructured Simulation Grids. SPE Annual Technical Conference and Exhibition. 1 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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