Zobrazeno 1 - 10
of 89
pro vyhledávání: '"Umair bin Waheed"'
Publikováno v:
Earth and Space Science, Vol 10, Iss 12, Pp n/a-n/a (2023)
Abstract An accurate and trustworthy first break picking plays a key role in static correction calculations, velocity analysis, and deconvolution. First break traveltimes picking accuracy ensures correct and reliable seismic data processing results.
Externí odkaz:
https://doaj.org/article/e0125ee94e2e498ab34c04f0f39a97fb
Publikováno v:
Scientific Reports, Vol 13, Iss 1, Pp 1-16 (2023)
Abstract Global traveltime modeling is an essential component of modern seismological studies with a whole gamut of applications ranging from earthquake source localization to seismic velocity inversion. Emerging acquisition technologies like distrib
Externí odkaz:
https://doaj.org/article/7acb1762292a4436ba8dd1811432f4d8
Publikováno v:
Frontiers in Earth Science, Vol 11 (2023)
Incorporating anisotropy is crucial for accurately modeling seismic wave propagation. However, numerical solutions are susceptible to dispersion artifacts, and they often require considerable computational resources. Moreover, their accuracy is depen
Externí odkaz:
https://doaj.org/article/aef3f5fc3a3c45ef804f0dc299060ba4
Publikováno v:
Frontiers in Big Data, Vol 6 (2023)
We have developed a Recurrent Neural Network (RNN)-based phase picker for data obtained from a local seismic monitoring array specifically designated for induced seismicity analysis. The proposed algorithm was rigorously tested using real-world data
Externí odkaz:
https://doaj.org/article/b3460dd4df164cad87da822fa4322fa3
Publikováno v:
Artificial Intelligence in Geosciences, Vol 2, Iss , Pp 11-19 (2021)
Solving the wave equation is one of the most (if not the most) fundamental problems we face as we try to illuminate the Earth using recorded seismic data. The Helmholtz equation provides wavefield solutions that are dimensionally reduced, per frequen
Externí odkaz:
https://doaj.org/article/03744c6e9e7e4243899072e73a4dc012
Autor:
Denis Anikiev, Umair bin Waheed, František Staněk, Dmitry Alexandrov, Qi Hao, Naveed Iqbal, Leo Eisner
Publikováno v:
Frontiers in Earth Science, Vol 10 (2022)
Location of earthquakes is a primary task in seismology and microseismic monitoring, essential for almost any further analysis. Earthquake hypocenters can be determined by the inversion of arrival times of seismic waves observed at seismic stations,
Externí odkaz:
https://doaj.org/article/88521945a3e64095ad17e9c8d4fd07d2
Publikováno v:
Sensors, Vol 21, Iss 23, p 8080 (2021)
Automatic detection of low-magnitude earthquakes has become an increasingly important research topic in recent years due to a sharp increase in induced seismicity around the globe. The detection of low-magnitude seismic events is essential for micros
Externí odkaz:
https://doaj.org/article/db9c7f2cf02c4c9aa03a3476940b1e5c
Publikováno v:
Applied Sciences, Vol 11, Iss 16, p 7736 (2021)
Ichnological analysis, particularly assessing bioturbation index, provides critical parameters for characterizing many oil and gas reservoirs. It provides information on reservoir quality, paleodepositional conditions, redox conditions, and more. How
Externí odkaz:
https://doaj.org/article/655014b35f454904bc68832c8a6b0ee6
Autor:
Khalid L. Alsamadony, Ertugrul U. Yildirim, Guenther Glatz, Umair Bin Waheed, Sherif M. Hanafy
Publikováno v:
Sensors, Vol 21, Iss 5, p 1921 (2021)
Deep neural networks have received considerable attention in clinical imaging, particularly with respect to the reduction of radiation risk. Lowering the radiation dose by reducing the photon flux inevitably results in the degradation of the scanned
Externí odkaz:
https://doaj.org/article/5884539836634a4db1ed0d8fcc8bfc9b
Publikováno v:
Applied Sciences, Vol 11, Iss 3, p 982 (2021)
The accuracy of computed traveltimes in a velocity model plays a crucial role in localization of microseismic events. The conventional approach usually utilizes robust fast sweeping or fast marching methods to solve the eikonal equation numerically w
Externí odkaz:
https://doaj.org/article/a05f47066fc04ca7974cf753a990a054