Biblio

Found 1732 results
2019
A. Quintanilla‐Terminel, Dillman, A. , Pec, M. , Diedrich, G. , and Kohlstedt, D. L. , Radial melt segregation during extrusion of partially molten rocks, Geochemistry, Geophysics, Geosystems, 2019.
Z. Xu, Mikesell, T. , Gribler, G. , and Mordret, A. , Rayleigh-wave multicomponent crosscorrelation-based source strength distribution inversion. Part 1: Theory and numerical examples, Geophysical Journal International, 2019.
P. Bharadwaj, Redshift of An Earthquake. 2019.
A. Pahlavan, Stone, H. A. , McKinley, G. H. , and Juanes, R. , Restoring universality to the pinch-off of a bubble, Proceedings of the National Academy of Sciences, 2019.
A. Scarinci, Fehler, M. , and Marzouk, Y. , Robust Bayesian moment tensor inversion using Transport-Lagrangian distances, in SEG Technical Program Expanded Abstracts 2019, San Antonio, Texas, 2019.
Z. Fang, Seimic inversion in the framework of modern optimization. 2019.
N. Nakata, Gualtieri, L. , and Fichtner, A. , Seismic Ambient Noise, 1st ed. Cambridge University Press, 2019.
N. Nakata and Nishima, K. , Seismic Ambient Noise: Body Wave Exploration, 1st ed., Cambridge University Press, 2019, pp. 239 - 266.
A. Fournier, Clerget, C. - H. , Bharadwaj, P. , and Merciu, I. , A seismoelectric inverse problem with well-log data and borehole-confined acquisition, in SEG Annual Meeting 2019, 2019.
A. Fournier, Clerget, C. - H. , Bharadwaj, P. , Merciu, A. , and Skar, G. , A seismoelectric inverse problem with well-log data and borehole-confined acquisition, in SEG Technical Program Expanded Abstracts 2019, San Antonio, Texas, 2019.
C. H. Clerget, Seismo-electric measurement for drilling look-ahead. 2019.
N. You, Li, Y. , and Cheng, A. , Shale anisotropy model building based on deep neural networks, in SEG Technical Program Expanded Abstracts 2019, San Antonio, Texas, 2019.
N. Gu, Wang, K. , Gao, J. , Ding, N. , Yao, H. , and Zhang, H. , Shallow Crustal Structure of the Tanlu Fault Zone Near Chao Lake in Eastern China by Direct Surface Wave Tomography from Local Dense Array Ambient Noise Analysis, Pure and Applied Geophysics, vol. 176, no. 3, pp. 1193 - 1206, 2019.
B. Primkulov, Signatures of fluid-fluid displacement in porous media. 2019.
B. Primkulov, Pahlavan, A. A. , Fu, X. , Zhao, B. , MacMinn, C. W. , and Juanes, R. , Signatures of fluid–fluid displacement in porous media: wettability, patterns and pressures, Journal of Fluid Mechanics, vol. 875, p. R4, 2019.
R. Ibanáñez, Scheuer, A. , Abisset-Chavanne, E. , Chinesta, F. , Huerta, A. , and Keunings, R. , A simple microstructural viscoelastic model for flowing foams, International Journal of Material Forming, vol. 12, no. 2, pp. 295 - 306, 2019.
Y. Li, Yang, J. , Cheng, A. , and Cheng, J. , Simulating kinematics of P- and S-wave scattering using scalar wave equations, in SEG Technical Program Expanded Abstracts 2019, San Antonio, Texas, 2019.
H. O. Ghaffari, Griffith, W. A. , and Pec, M. , Solitonic State in Microscopic Dynamic Failures, Scientific Reports, 2019.
D. Kalafat and Görgün, E. , Source characteristics and b-values of the Tuz Gölü Fault Zone in Central Anatolia, Turkey, Journal of Asian Earth Sciences, vol. 179, pp. 337 - 349, 2019.
X. Chen, Pennington, C. , Ng, R. , Nakata, N. , and Zhang, J. , Source parameter analysis of microseismicity during hydraulic fracture: Pinning stress distributions within fracture zone, in SEG Technical Program Expanded Abstracts 2019, San Antonio, Texas, 2019.
T. Xing, Zhu, W. , French, M. , and Belzer, B. , Stabilizing Effect of High Pore Fluid Pressure on Slip Behaviors of Gouge‐bearing Faults, Journal of Geophysical Research: Solid Earth, 2019.
P. K. Kang, Lei, Q. , Dentz, M. , and Juanes, R. , Stress‐Induced Anomalous Transport in Natural Fracture Networks, Water Resources Research, no. 55, pp. 4163-4185, 2019.
N. Nakata, Towards high-resolution seismic imaging and monitoring using ambient noise, machine learning, and microseismic events. 2019.
M. Ranganathan, Understanding ice flow through computational methods. 2019.
J. Montgomery, Understanding shale gas and tight oil productivity with machine learning. 2019.

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