Publications

Name indicates student advisees or post-docs.

Peer-reviewed publications

• Wei, X., J. Sun, and M. K. Sen, 2024, Reconstruction of multiple salt bodies using trans-dimensional Monte Carlo gravity inversion: IEEE Transactions on Geoscience and Remote Sensing, vol. 62, pp. 1-16, Art no. 5911016, doi: 10.1109/TGRS.2024.3382106

• Wei, X., J. Sun, and M. K. Sen, 2024,3D Monte Carlo geometry inversion using gravity data: Geophysics, 89(3), G29-G44, https://doi.org/10.1190/geo2023-0498.1

• Hu, Y., X. Wei, X. Wu, J. Sun, Y. Huang, and J. Chen, 2024, Three-dimensional cooperative inversion of airborne magnetic and gravity gradient data using deep learning techniques, Geophysics, 89(1), WB67-WB79, https://library.seg.org/doi/10.1190/geo2023-0225.1

• Sun, J., and Fournier, D., 2024, Understanding total variation regularization: Why can it recover dipping structures?: Geophysical Prospecting, 72, 424–434,  https://doi.org/10.1111/1365-2478.13417

• Wei, X., J. Sun, and M. K. Sen, 2023, Quantifying uncertainty of salt body shapes recovered from gravity data using trans-dimensional Markov chain Monte Carlo sampling: Geophys. J. Int., 232(3), 1957-1978,  https://doi.org/10.1093/gji/ggac430

• Wei, X., K. Li, and J. Sun, 2023, Mapping critical mineral resources using airborne geophysics, 3D joint inversion and geology differentiation: A case study of a buried niobium deposit in the Elk Creek carbonatite, Nebraska, USA, Geophysical Prospecting, 71, 1247-1266 , https://doi.org/10.1111/1365-2478.13280

• Hu, Y, X. Wei, X. Wu, J. Sun, J. Chen, Y. Huang and J. Chen, 2023, A deep learning enhanced framework for multi-physics joint inversion: Geophysics, 88(1), K13-K26, https://doi.org/10.1190/geo2021-0589.1

• Wei, X., and J. Sun, 2022, 3D probabilistic geology differentiation based on airborne geophysics, mixed Lp norm joint inversion and physical property measurements, Geophysics, 87(4), K19-K33, https://doi.org/10.1190/geo2021-0833.1.

• Li, X., and J. Sun, 2022, Toward a better understanding of the recoverability of physical property relationships from geophysical inversions of multiple potential-field datasets: Geophys. J. Int., 230(3), 1489-1507, https://doi.org/10.1093/gji/ggac130.

• Wei, X., and J. Sun, 2021, Uncertainty analysis of 3D potential-field deterministic inversion using mixed Lp norms: Geophysics, 86(6), https://doi.org/10.1190/geo2020-0672.1 .

• Sun, J., and X. Wei, 2021, Recovering sparse models in 3D potential-field inversion without bound dependence or staircasing problems  using a mixed Lp-norm regularization, Geophysical Prospecting, 69, 901-910 , https://doi.org/10.1111/1365-2478.13063

• Nurindrawati, F. D., and J. Sun, 2020, Predicting total magnetization directions using convolutional neural networks: Journal of Geophysical Research: Solid Earth, https://doi.org/10.1029/2020JB019675

• Sun, J., A. Melo, J. D. Kim, and X. Wei, 2020, Unveiling the 3D undercover structure of the Precambrian intrusive complex by integrating airborne magnetic and gravity gradient data into 3D quasi-geology model building: Interpretation, 8(4), SS15-SS29, https://doi.org/10.1190/int-2019-0273.1

• Bernier, C., Y. Wang, M. Estes, R. Lei, B. Jia, S. Wang, and J. Sun, 2019, Clustering surface ozone diurnal cycles to understand the impact of circulation patterns in Houston, TX: Journal of Geophysical Research: Atmospheres, 124, 13,457-13,474. https://doi.org/10.1029/2019JD031725

• Sun, J., and Y. Li, 2019, Magnetization clustering inversion Part II: Assessing the uncertainty of recovered magnetization directions: Geophysics, 84(4), J17-J29. https://doi.org/10.1190/geo2018-0480.1 

• Sun, J., and Y. Li, 2018, Magnetization clustering inversion Part I: Building an automated numerical optimization algorithm: Geophysics, 83(5), J61-J73.  https://doi.org/10.1190/geo2017-0844.1 

• Melo, A., J. Sun and Y. Li, 2017, Geophysical inversions applied to 3D geology characterization of an iron oxide copper gold  deposit in Brazil: Geophysics, 82(5), K1-K13. (link)

• Sun, J., and Y. Li, 2017, Joint inversion of multiple geophysical and petrophysical data using generalized fuzzy clustering algorithms: Geophys. J. Int., 208(2), 1201-1216. (link)

• Li, Y., and J. Sun, 2016, 3D magnetization inversion using fuzzy c-means clustering with application to geology differentiation: Geophysics, 81(5), J61-J78. (link)

• Sun, J., and Y. Li, 2016, Joint inversion of multiple geophysical data using guided fuzzy c-means clustering: Geophysics, 81(3), ID37-ID57. (link)

• Sun, J., and Y. Li, 2015, Multidomain petrophysically constrained inversion and geology differentiation using guided fuzzy c-means clustering: Geophysics, 80(4), ID1-ID18. (link)

• Sun, J., and Y. Li, 2014, Adaptive Lp inversion for simultaneous recovery of both blocky and smooth features in a geophysical model:  Geophys. J. Int., 197(2), 882-899. (link)

Non-peer-reviewed publications

• Li, Y., J. Sun, S. Li, and M. Leão‐Santos, 2021, A paradigm shift in magnetic data interpretation: Increased value through magnetization inversions: The Leading Edge, 40(2), 89-98. https://doi.org/10.1190/tle40020089.1

• Sun, J., D. Colombo, Y. Li, and J. Shragge, 2020, GEOPHYSICS introduces new section on multiphysics and joint inversion: The Leading Edge, 39(10), 753-754. https://doi.org/10.1190/tle39100753.1

• Li, Y., A. Melo, C. Martinez, and J. Sun, 2019, Geology differentiation: A new frontier in quantitative geophysical interpretation in mineral exploration: The Leading Edge, 38(1), pp. 60-66. https://doi.org/10.1190/tle38010060.1

• Nurindrawati, F. D., and J. Sun, 2019, A machine learning approach to predicting magnetization directions: GSH Journal, 10(2), 27-30. https://cloud.3dissue.com/190951/191368/223577/Oct2019Volume10No2/index.html

Expanded Conference Abstracts

• Wei, X., J. Sun, and M. K. Sen, 2022, Trans-dimensional Bayesian gravity inversion and uncertainty analysis for salt reconstruction: SEG Technical Program Expanded Abstracts: 1145-1149, Houston, US. https://doi.org/10.1190/image2022-3746659.1

• Li, K. H., X. Wei, and J. Sun, 2021, Geophysical characterization of a buried niobium and rare earth element deposit using 3D joint inversion and geology differentiation: A case study on the Elk Creek Carbonatite: SEG Technical Program Expanded Abstracts: 1256-1260, Denver, US. https://doi.org/10.1190/segam2021-3585069.1 

• Wei, X., and J. Sun, 2021, Uncertainty analysis of 3D geophysical inversion using airborne gravity gradient data conditioned on rock sample measurements: SEG Technical Program Expanded Abstracts: 921-925, Denver, US. https://doi.org/10.1190/segam2021-3586552.1 

• Wei, X., and J. Sun, 2021, 3D probabilistic geology differentiation using mixed Lp norm joint inversion constrained by petrophysical information: SEG Technical Program Expanded Abstracts: 1231-1235, Denver, US. https://doi.org/10.1190/segam2021-3586619.1 

• Li, X., and J. Sun, 2021, Understanding the recoverability of physical property relationships from geophysical inversions of multiple potential-field datasets: SEG Technical Program Expanded Abstracts: 1236-1240, Denver, US. https://doi.org/10.1190/segam2021-3594791.1

• Hu, Y., X. Wei, X. Wu, J. Sun, J. Chen, Y. Huang and J. Chen, 2021, Deep learning enhanced multi-physics joint inversion: SEG Technical Program Expanded Abstracts, 1721-1725,  Denver, US. https://doi.org/10.1190/segam2021-3583667.1 

• Sun, J., A. Melo, J. D. Kim and X. Wei, 2020, Characterizing a Precambrian intrusive complex by integrating potential field data into 3D quasi-geology model building: 90th Annual International Meeting, SEG Expanded Abstracts, 28.  pp. 1374-1378, Houston, US. https://doi.org/10.1190/segam2020-3428385.1

• Wei, X.., and J. Sun, 2020, Quantifying uncertainties of deterministic geophysical inversions using mixed Lp norms: 90th Annual International Meeting, SEG Expanded Abstracts, 27.  pp. 1404-1408, Houston, US. https://doi.org/10.1190/segam2020-3420227.1

• Wei, X., and J. Sun, 2020, Uncertainty analysis of joint inversion using mixed Lp norm regularization: 90th Annual International Meeting, SEG Expanded Abstracts, 26.  pp. 925-929, Houston, US. https://doi.org/10.1190/segam2020-3428359.1

• Kim, J. D., and J. Sun, 2020, Regional scale mineral exploration through joint inversion and geology differentiation based on multi-physics geoscientific Data: 90th Annual International Meeting, SEG Expanded Abstracts, pp. 1379-1383, Houston, US. https://doi.org/10.1190/segam2020-3428427.1 

• Nurindrawati, F. D., and J. Sun, 2020, Improving the accuracy of convolutional neural networks in predicting magnetization directions: 90th Annual International Meeting, SEG Expanded Abstracts, pp. 1369-1373, Houston, US. https://doi.org/10.1190/segam2020-3426827.1

• Li, Y., J. Sun and J. Capriotti, 2020, Integration of multiphysics data sets for subsurface imaging through petrophysical data and a fuzzy c-means formalism, 82nd EAGE Conference and Exhibition, Amsterdam, The Netherlands.

• Nurindrawati, F. D., and J. Sun, 2019, Estimating total magnetization directions using convolutional neural networks: 89th Annual International Meeting, SEG Expanded Abstracts,  pp. 2163-2167, San Antonio, US. https://doi.org/10.1190/segam2019-3216857.1

• Sun, J., and Y. Li, 2019, Advances in 3D magnetization clustering inversion: Numerical strategies and uncertainty analysis: International Workshop on Gravity, Electrical & Magnetic Methods and their Applications, Xi’an, China, 19-22 May. https://doi.org/10.1190/GEM2019-118.1

• Sun, J., and Y. Li, 2018, An automated optimization algorithm for magnetization clustering inversion: 88th Annual International Meeting, SEG Expanded Abstracts, pp. 1410-1414, Anaheim, US. https://doi.org/10.1190/segam2018-2997039.1

• Sun, J., and Y. Li, 2017, Assessing the uncertainty of magnetization directions from clustering inversion and its effect on geology differentiation: 87th Annual International Meeting, SEG Expanded Abstracts, accepted. (link)

• Sun, J., and Y. Li, 2017, Integration of geophysical and petrophysical data through joint inversion, in Proceedings of Exploration 17: Sixth Decennial International Conference on Mineral Exploration, accepted.

• Sun, J., and Y. Li, 2016, Joint clustering inversion of gravity and magnetic data applied to the imaging of a gabbro intrusion: 86th Annual International Meeting, SEG Expanded Abstracts, 2175-2179, Dallas, US. (link)

• Li, Y., and J. Sun, 2016, Geology differentiation with uncertainty estimation using inverted magnetization directions: 86th Annual International Meeting, SEG Expanded Abstracts, 2159-2164, Dallas, US. (link)

• Rapstine, T., J. Sun, and Y. Li, 2016, Integrating a spatial salt likelihood map and prior petrophysical data into a gravity gradiometry inversion through fuzzy c-means clustering: 86th Annual International Meeting, SEG Expanded Abstracts, 1622-1626, Dallas, US. (link)

• Sun, J., and Y. Li, 2015, Advancing the understanding of petrophysical data through joint inversion: A sulfide deposit example from Bathurst Mining Camp: 85th Annual International Meeting, SEG Expanded Abstracts, 2017-2021, New Orleans, US. (link)

• Melo, A. T., J. Sun, and Y. Li, 2015, Geophysical inversions applied to geological differentiation and deposit characterization: A case study at an IOCG deposit in Carajás Mineral Province, Brazil: 85th Annual International Meeting, SEG Expanded Abstracts, 2012-2016, New Orleans, US. (link)

• Li, Y., and J. Sun, 2015, Towards geology differentiation using magnetization inversions: International workshop on gravity, electrical & magnetic methods and their application, 350-353, Chengdu, China. (link)

• Sun, J., and Y. Li, 2014, Exploration of a sulfide deposit using joint inversion of magnetic and induced polarization data: 84th Annual International Meeting, SEG Expanded Abstracts, 1780-1784, Denver, US. (link)

• Li, Y., and J. Sun, 2014, Total magnetization vector inversion using guided fuzzy c-means clustering: 84th Annual International Meeting, SEG Expanded Abstracts, 1285-1290, Denver, US. (link)

• Sun, J., and Y. Li, 2013, A general framework for joint inversion with petrophysical information as constraints: 83rd Annual International Meeting, SEG Expanded Abstracts, 3093-3097, Houston, US. (link)

• Sun, J., and Y. Li, 2013, Petrophysically constrained geophysical inversion using Parzen window density estimation: 83rd Annual International Meeting, SEG Expanded Abstracts, 3051-3056, Houston, US. (link)

• Sun, J., and Y. Li, 2012, Joint inversion of multiple geophysical data: A petrophysical approach using guided fuzzy c-means clustering: 82nd Annual International Meeting, SEG Expanded Abstracts, 1-5, Las Vegas, US. (link)

• Sun, J., Y. Li, and M. Nabighian, 2012, Lithology differentiation based on inversion of full waveform induced polarization data from Newmont Distributed IP Data Acquisition System (NEWDAS): 82nd Annual International Meeting, SEG Expanded Abstracts, 1-5, Las Vegas, US. (link)

• Sun, J., and Y. Li, 2012, Joint inversion of seismic traveltimes and gravity data using petrophysical constraints with application to lithology differentiation: 22nd ASEG International Geophysical Conference and Exhibition, 1-4, Brisbane, Australia. (link)

• Sun, J., and Y. Li, 2011, Geophysical inversion using petrophysical constraints with application to lithology differentiation: 81st Annual International Meeting, SEG Expanded Abstracts, 30, 2644-2648, San Antonio, US. (link)

• Sun, J., and Y. Li, 2011, Geophysical inversion using petrophysical constraints with application to lithology differentiation: 12th International Congress of the Brazilian Geophysical Society & EXPOGEF, Rio de Janeiro, Brazil, 15–18 August 2011: pp. 861-866. (link)

• Sun, J., and Y. Li, 2010, Adaptive Lp inversion to recover both blocky and smooth features: 80th Annual International Meeting, SEG Expanded Abstracts, 29, 4297-4301, Denver, US. (link)

• Sun, J., and Y. Li, 2010, Inversion of surface and borehole gravity with thresholding and density constraints: 80th Annual International Meeting, SEG Expanded Abstracts, 29, 1798-1803, Denver, US. (link)

Conference Abstracts

• Wei, X., J. Sun, and M. Sen, 2022, A Bayesian framework for uncertainty analysis of anomalous body shapes using gravity data, AGU Fall Meeting Abstracts, NG35B-0469.

• Wei, X., and J. Sun, 2021, Building 3D probabilistic geology differentiation models using mixed Lp norm joint inversion, airborne geophysics and petrophysical information, AGU Fall Meeting Abstracts, NG25A-0485, https://ui.adsabs.harvard.edu/abs/2021AGUFMNG25A0485W/abstract.

• Wei, X., and J. Sun, 2021, Analyzing uncertainty of 3D inversion using airborne geophysical data conditioned on petrophysical measurements, AGU Fall Meeting Abstracts, NS35C-0373, https://ui.adsabs.harvard.edu/abs/2021AGUFMNS35C0373W/abstract

• Li, X., and J. Sun, 2021, Investigating the Recoverability of Density-Susceptibility Relationships from Geophysical Inversions, AGU Fall Meeting Abstracts, NS24A-02, https://ui.adsabs.harvard.edu/abs/2021AGUFMNS24A..02L/abstract

• Sun, J., R. Mehta, and D. Yang, 2021, Mapping River Salinization Using Airborne Electromagnetic Data and Unsupervised Machine Learning, AGU Fall Meeting Abstracts, IN42B-06, https://ui.adsabs.harvard.edu/abs/2021AGUFMIN42B..06S/abstract

• Li, K. H., and J. Sun, 2021, Characterizing a buried niobium deposit using airborne geophysics, joint inversion, and geology differentiation, NS24A-05, https://ui.adsabs.harvard.edu/abs/2021AGUFMNS24A..05L/abstract.

• Kim, J. D., and J. Sun, 2019, Cross-gradient Joint Inversion of the QUEST data in Central British Columbia for regional scale mineral exploration:  AGU Fall Meeting Abstracts, NS23B-0839, https://ui.adsabs.harvard.edu/abs/2019AGUFMNS23B0839K

• Li, K. H., Wei, X., and J. Sun, 2019, Geophysical Characterization of the Elk Creek Carbonatite (Southeastern Nebraska) using Joint Inversion of Airborne Gravity Gradiometry and Magnetic Data: 8.     AGU Fall Meeting Abstracts, NS43D-0866, https://ui.adsabs.harvard.edu/abs/2019AGUFMNS43D0866L

• Nurindrawati, F. D., and J. Sun, 2019, Predicting magnetization direction using convolutional neural networks: 7.     AGU Fall Meeting Abstracts, GP42A-09, https://ui.adsabs.harvard.edu/abs/2019AGUFMGP42A..09N

• Bernier, C., Y. Wang, M. Estes, R. Lei, B. Jia, S. Wang, and J. Sun, 2019, Clustering surface ozone diurnal cycles to understand the impact of circulation patterns in Houston, TX: 6.     AGU Fall Meeting Abstracts, A21G-2650, https://ui.adsabs.harvard.edu/abs/2019AGUFM.A21G2650B

• Sun, J., and W. W. Sager, 2019, Interpreting marine magnetic anomaly of Ori Massif in the northwest Pacific Ocean using magnetization clustering inversion: 2nd International Conference on Machine Learning in Solid Earth Geoscience, Santa Fe, United States, Mar. 18-22.

• Sun, J., Y. Zhang, and A. Li, 2018, Accelerating USArray data processing using ensemble learning: Machine Learning in Solid Earth Geoscience Workshop, Santa Fe, United States, Feb. 20-13.

• Irons, T., J. Sun, N. Moodie, R. Krahenbuhl, Y. Li, B. McPherson, and W. Ampomah, 2017, Monitoring carbon sequestration using charged wellbore controlled source electromagnetics and integrated reservoir models: AIChE Annual Meeting, Minneapolis, MN, United States, Oct. 29-Nov. 3rd.

• Sun, J., and Y. Li, 2017, 3D magnetization vector inversion based on fuzzy clustering: inversion algorithm, uncertainty analysis and application to geology differentiation: American Geophysical Union (AGU) Fall Meeting, New Orleans, United States, Abstract #NS33A-0037, https://ui.adsabs.harvard.edu/abs/2017AGUFMNS33A0037S

• Sun, J., and Y. Li, 2012, A new joint inversion strategy using a priori petrophysical  information as constraints: American Geophysical Union (AGU) Fall Meeting, San Francisco, United States, Abstract #NS34A-05, 1.     https://ui.adsabs.harvard.edu/abs/2012AGUFMNS34A..05S