Naser Golsanami is Associate Professor in the College of Mining and Safety Engineering of Shandong University of Science and Technology. Naser received his Ph.D. from China University of Petroleum (East China) (UPC) in July 2018. He is establisher of the “Scientific Research and Publication Center” of UPC. Naser is the winner of the “Talented Young Scientists Program” of the Ministry of Science and Technology of the People’s Republic of China in 2018. He has taken an active role in Geological and Petroleum Engineering projects funded by both governmental and private sectors of the industry for which the total founding reaches up to $0.5M. While serving as the reviewer of more than 15 peer-reviewed SCI journals including FUEL, International Journal of Energy Research, Energy & Fuels, Journal of Petroleum Science and Engineering etc., his research publications have mainly focused on digital rock technology, rock physics, data mining, and geological formation evaluation via nuclear magnetic resonance technique. He has also been involved in rock physics studies of unconventional coalbed methane reservoirs. Currently, Naser is engaged in characterizing the mechanical behavior as well as pore structural features of natural gas hydrate reservoirs using rock engineering approach, digital rock physics, as well as deep learning convolutional neural networks.

Ph.D. in Geological Resources and Geological Engineering from China University of Petroleum (East China), China, 2014-2018.

Master of Science in Petroleum Exploration Engineering from Sahand University of Technology (SUT), Iran, 2009-2011.

Bachelor of Science in Mining Exploration Engineering from Sahand University of Technology (SUT), Iran, 2005-2009.

Research Interests:

Digital Rocks and Rock Physics

Natural Gas Hydrates and Unconventional Resources

Reservoir Geomechanics and Rock Mechanics

2D NMR (Nuclear Magnetic Resonance)

Data Mining and Machine Learning

Publications:

1. Golsanami, N., Sun, J., Liu, Y., Yan, W., Lianjun, C., Jiang, L., Dong, H., Zong, C., Wang, H., 2019. Distinguishing fractures from matrix pores based on the practical application of rock physics inversion and NMR data: A case study from an unconventional coal reservoir in China. J. Nat. Gas Sci. Eng. 65, 145–167. https://doi.org/10.1016/j.jngse.2019.03.006

2. Yan, W., Sun, J., Golsanami, N., Li, M., Cui, L., Dong, H., Sun, Y., 2019a. Evaluation of wettabilities and pores in tight oil reservoirs by a new experimental design. Fuel 252, 272–280. https://doi.org/10.1016/J.FUEL.2019.04.130

3. Golsanami, N., Sun, J., Zhang, Z., 2016. A review on the applications of the nuclear magnetic resonance (NMR) technology for investigating fractures. J. Appl. Geophys. 133, 30–38. https://doi.org/10.1016/j.jappgeo.2016.07.026

4. Golsanami, N., Kadkhodaie-Ilkhchi, A., Erfani, A., 2015. Synthesis of capillary pressure curves from post-stack seismic data with the use of intelligent estimators: A case study from the Iranian part of the South Pars gas field, Persian Gulf Basin. J. Appl. Geophys. 112, 215–225. https://doi.org/10.1016/j.jappgeo.2014.11.013

5. Golsanami, N., Kadkhodaie-Ilkhchi, A., Sharghi, Y., Zeinali, M., 2014. Estimating NMR T2 distribution data from well log data with the use of a committee machine approach: A case study from the Asmari formation in the Zagros Basin, Iran. J. Pet. Sci. Eng. 114, 38–51. https://doi.org/10.1016/j.petrol.2013.12.003

6. Dong, H., Sun, J., Zhu, J., Liu, L., Lin, Z., Golsanami, N., Cui, L., Yan, W., 2019b. Developing a new hydrate saturation calculation model for hydrate-bearing sediments. Fuel. https://doi.org/10.1016/j.fuel.2019.03.038

7.Dong, H., Sun, J., Cui, L., Golsanami, N., Weichao, Y., 2019a. Characteristics of the pore structure of natural gas hydrate reservoir in the Qilian Mountain Permafrost, Northwest China. J. Appl. Geophys. https://doi.org/10.1016/j.jappgeo.2019.03.005

8.Eslami, M., Kadkhodaie-ilkhchi, A., Sharghi, Y., Golsanami, N., 2013. Construction of synthetic capillary pressure curves from the joint use of NMR log data and conventional well logs. J. Pet. Sci. Eng. 111, 50–58. https://doi.org/10.1016/j.petrol.2013.10.010

9.Dong, H., Sun, J., Golsanami, N., Cui, L., Jiang, L., Yan, G., Yan, W., Li, Y., 2018. A method to construct high-precision complex pore digital rock. J. Geophys. Eng. 15, 2695–2703. https://doi.org/10.1088/1742-2140/aae04e

10.Yan, W., Sun, J., Zhang, J., Golsanami, N., Hao, S., 2017. A novel method for estimation of remaining oil saturations in water-flooded layers. Interpretation 5, SB9–SB23. https://doi.org/10.1190/INT-2016-0074.1

11.Golsanami, N., Sun, J., 2017. Developing a new technique for estimating NMR T1 and T2 relaxations, in: 79th EAGE Conference and Exhibition 2017. Paris, France, https://doi.org/10.3997/2214-4609.201700926

12. Golsanami, N., Sun, J., 2017a. Application of rock physics inversion for porosity determination in coalbed methane reservoirs: A case study from Qinshui basin in China, in: CGS/SEG International Geophysical Conference, Qingdao, China, 17-20 April 2017. Society of Exploration Geophysicists and Chinese Petroleum Society, pp. 1217–1220. https://doi.org/10.1190/IGC2017-309

13.Golsanami, N., Sun, J., 2017b. Developing a new technique for estimating NMR T1 and T2 relaxations, in: CGS/SEG International Geophysical Conference, Qingdao, China, 17-20 April 2017. Society of Exploration Geophysicists and Chinese Petroleum Society, pp. 1202–1205. https://doi.org/10.1190/IGC2017-305

Address:

No. 323, J4 Building, College of Mining and Safety Engineering, Qingdao Campus, Shandong University of Science and Technology (No. 575, Qianwan Gang Street, Huangdao District, Qingdao, Shandong, China, Zip code: 266590)

Tel: (+86) 532-86057548

E-mail: golsanami_naser@sdust.edu.cn