Gravity, Electrical, Magnetic, Electromagnetic Research at SUSTech


Wang, R., D. Yang, Y. Chen, and C, Ren, 2023, Lighting up a 1 km fault near a hydraulic fracturing well using a machine learning-based picker: Seismological Research Letters, 94, no.4, 1836-1847.


Wang, K., and D. Yang, 2023, Joint inversion with petrophysical constraints using indicator functions and the extended alternating direction method of multipliers: Geophysics, 88, no.1, R49-R64.


Cheng, M., D. Yang, and Q. Luo, 2023, Interpreting surface large-loop time-domain electromagnetic data for deep mineral exploration using 3D forward modeling and inversion: Minerals, 13, no.1, 34.


吴雯,王猛,杨迪琨,陈默,任林彬, 2022, 页岩气水力压裂分布式微弱电场监测技术初探:物探与化探,46,no.3,557-562,http:.//


Chen, T., and D. Yang, 2022, Modeling and inversion of airborne and semi-airborne transient electromagnetic data with inexact transmitter and receiver geometries: Remote Sensing, Vol. 14, No. 915.


Chen, T., and D. Yang, 2022, Potential field data interpolation by Taylor series expansion: Geophysics, Vol. 87, No.2, P. G15-G27.


Hu, Y., D. Yang, Y. Li, Z. Wang, and Y. Lu, 2022, 3-D numerical study on controlled source electromagnetic monitoring of hydraulic fracturing fluid with the effect of steel-cased wells: IEEE Transactions on Geoscience and Remote Sensing, Vol. 60, P. 1-10, Art No. 4504210. 


Chen, T., and D. Yang, 2022, Gravity gradient tensors derived from radial component of gravity vector using Taylor series expansion: Geophysical Journal International, Vol. 228, No. 1, P. 412-431.


Li, Y., and D. Yang, 2021, Electrical imaging of hydraulic fracturing fluid using steel-cased wells and a deep-learning method, Geophysics, 86(4): E315-E332.


Bedrosian, P. A., G. Schwarz, K. Selway, P. Wawrzyniak, D. Yang, 2021, Special issue "Studies on electromagnetic induction in the Earth: recent advances and future directions": Earth, Planets and Space, Vol. 73, No. 1, P. 1-3.


Yang, D., D. Fournier, S. Kang, and D. W. Oldenburg, 2019, Deep mineral exploration using multi-scale electromagnetic geophysics: the Lalor massive sulphide deposit case study. Canadian Journal of Earth Sciences,  Vol. 56, No. 5, P.544-555.


Yang, D., and D. Oldenburg, 2018, Electric field data in inductive source electromagnetic surveys, Geophysical Prospecting, Vol. 66, No. 1, P. 207-225.


Yang, D., and D. Oldenburg, 2017, 3D inversion of total magnetic intensity data for time-domain EM at the Lalor massive sulphide deposit, Exploration Geophysics, Vol. 48, No. 2, P. 110-123.


Yang, D., and D. Oldenburg, 2016, Survey decomposition: A scalable framework for 3D controlled source electromagnetic inversion, Geophysics, Vol. 81, No. 2, P. E69-E87.


Yang, D., D. Oldenburg, and E. Haber, 2014, 3-D inversion of airborne electromagnetic data parallelized and accelerated by local mesh and adaptive soundings, Geophysical Journal International, Vol. 196, No. 3, P. 1492-1507.


Yang, D., and D. Oldenburg, 2012, Three-dimensional inversion of airborne time-domain electromagnetic data with applications to a porphyry deposit, Geophysics, Vol. 77, No. 2, P. B23-B34.


Dai, M., X. Hu, H. Wu, L. Jiang, and D. Yang, 2009, Inversion of surface nuclear magnetic resonance for groundwater exploration, Chinese Journal of Geophysics, Vol. 52, No. 5, P. 1166-1173.


Zhao, L., J. Geng, S. Zhang, D. Yang, 2008, 1-D controlled source electromagnetic forward modeling for marine gas hydrates studies, Applied Geophysics, Vol. 5, No. 2, P. 121-126.


Yang, D., and X. Hu, 2008, Inversion of noisy data by probabilistic methodology, Chinese Journal of Geophysics, Vol. 51, No. 3, P. 901-907. (in Chinese)


Yang, D., and X. Hu, 2007, The development of electromagnetic method for groundwater exploration, Chinese Journal of Engineering Geophysics, Vol. 4, No. 5, P. 495-500. (in Chinese)


Hu, X., D. Yang, S. Liu, and Z. Hu, 2006, The developing trends of environmental and engineering geophysics: Review of the 2nd International Conference on Environmental and Engineering Geophysics, Progress in Geophysics, Vol. 21, No. 2, P. 598-604. (in Chinese)


Zhang, R., X. Hu, D. Yang, X. Hao, and M. Dai, 2006, Review of development of surface nuclear magnetic resonance, Progress in Geophysics, Vol. 21, No. 1, P. 284-289. (in Chinese)



Journal Articles