Results 81 to 90 of about 101,769 (259)

Tau-p mapping and interpretation of seismic reflection data from the western Isles region of Scotland [PDF]

, 1982
Seismic data are conventionally recorded, processed and displayed in the X-T domain, where X is the source-receiver. offset and T is the two-way traveltime.
Lambert, Mark E.
core  

Advancing mine pillar design: Evaluating traditional methods and integrating AI for enhanced stability of pillars in the Great Dyke, Zimbabwe

Deep Underground Science and Engineering, EarlyView.
B1 is bord width 1, B2 is bord width 2, L is the pillar length, W is the pillar width, red color and letter A represent the pillars, and white color and number 1 represent excavated areas. Pstress is the average pillar stress; σv is the vertical component of the virgin stress, MPa; and e is the areal extraction ratio. e = B o B o + B P ${\rm{e}}=\frac{{
Tawanda Zvarivadza, Hendrik Grobler, Peter Apata Olubambi, Moshood Onifade, Manoj Khandelwal   +4 more
wiley   +1 more source

Adaptive SVD Denoising in Time Domain and Frequency Domain

Applied Sciences
In seismic data processing, noise not only affects velocity analysis and seismic migration, but also causes potential risks in post-stack processing because of the artifacts.
Meixuan Ren, Enli Zhang, Qiang Kang, Long Chen, Min Zhang, Lei Gao   +5 more
doaj   +1 more source

Replication Data for: The geometry of the subducted slab beneath Sumatra revealed by regional and teleseismic traveltime tomography

, 2020
Seismic data used in Liu et al. (2020).
Tong, Ping
core   +1 more source

Research progress and current status of dynamic wave propagation characteristics in rock mass: A review

Deep Underground Science and Engineering, EarlyView.
This review elucidates the velocity–dispersion–attenuation coupling mechanisms of wave propagation in rock masses, compares six representative models, and reveals how pressure, temperature, mineral composition, and anisotropy jointly control dynamic responses in complex geological media.
Jiajun Shu, Tao Li, Ruiqi Yuan, Yue Li, Bingni Wu, Bo Liu, Zhengding Deng, Galindo Rubén, Fausto Molina‐Gómez   +8 more
wiley   +1 more source

Combined Gravimetric-Seismic Moho Model of Tibet

Geosciences, 2018
Substantial progress has been achieved over the last four decades to better understand a deep structure in the Himalayas and Tibet. Nevertheless, the remoteness of this part of the world still considerably limits the use of seismic data.
Alexey Baranov, Mohammad Bagherbandi, Robert Tenzer   +2 more
doaj   +1 more source

Seismic analysis and design of tunnels within fault ground: A review

Deep Underground Science and Engineering, EarlyView.
The research methods of seismic response of tunnels within fault ground, including field investigations, analytical solutions, physical experiments, and numerical simulations, and seismic countermeasures are discussed. The present study examines the shortcomings and limitations of the current research and design, and puts forward proposals for future ...
Xingda Wang, Yujing Jiang, Xuepeng Zhang, Yuyong Jiao, Ningbo Li, Xiao Wang, Bo Li   +6 more
wiley   +1 more source

Thermal‐induced fracture evolution and acoustic signature of Beishan granite: Insights into tensile strength of barrier system for high‐level radioactive waste disposal

Deep Underground Science and Engineering, EarlyView.
The tensile strength of granite, a proposed host for nuclear waste, degrades severely above 400°C. We link this to specific microcracking patterns captured by acoustic emission, establishing a scientific basis for assessing repository safety under thermal load.
Wei Zeng, Shijie Li, Xiaozhao Li, Zhen Huang, Shangtong Yang, Wentao Xu, Biao Wang, Yun Wu   +7 more
wiley   +1 more source

Measuring the Fractal Properties of Reservoirs for Use in Modeling CCUS Potential

Earth and Space Science
The injection of CO2 underground into reservoirs for carbon capture and underground storage (CCUS) is highly sensitive to heterogeneity and anisotropy. Although conventional geological modeling cannot take explicit account of heterogeneity or anisotropy ...
Mehdi Yaghoobpour, Paul W. J. Glover, Piroska Lorinczi, Wei Wei   +3 more
doaj   +1 more source

Probabilistic prediction of rate‐dependent rock strength using natural gradient boosting and Gaussian process regression

Deep Underground Science and Engineering, EarlyView.
Probabilistic natural gradient boosting and Gaussian process regression models accurately predict rate‐dependent rock strength across lithologies. Static strength and strain rate dominate, while geometric factors have minimal influence, enabling interpretable and uncertainty‐aware predictions for dynamic geomechanical applications. Abstract The dynamic
Hadi Fathipour‐Azar
wiley   +1 more source