Semantic Scholar Open Access 2022 6 sitasi

Modelling of seismic assessment for large geological systems

I. Movchan A. Yakovleva V. Frid A. Movchan Zilya I. Shaygallyamova

Abstrak

A new approach to seismic analysis has been introduced and demonstrated for a sequence of recent seismic events recorded in the Blackpool region of Lancashire, UK. The seismic activity, induced by an industrial hydraulic fracturing at a depth exceeding 2 km, had the extent of registered surface elastic vibrations reaching a distance exceeding 15 km. The analysis is based on the study of elastic fields, three-dimensional extrapolations of the landscape and the novel reconstruction of a three-dimensional digital model of seismic map boundaries and vertical profiles. The verification of the proposed approach is carried out via the comparison with published data of the Blackpool seismic events, combined with the new spectral analysis linked to the identified regions of seismic activity. The latter was accompanied by a finite-element simulation of vibrations for an elastic layer of variable thickness, approximating the test region. The analysis and numerical modelling have demonstrated consistency with the dynamic nature of structural stratification of the geological systems, and in addition, the predictive nature of the modelling work was demonstrated by the comparison of the model eigenmodes with the published parameters of registered earthquakes in the Blackpool area. This article is part of the theme issue ‘Wave generation and transmission in multi-scale complex media and structured metamaterials (part 1)’.

Topik & Kata Kunci

Penulis (5)

I

I. Movchan

A

A. Yakovleva

V

V. Frid

A

A. Movchan

Z

Zilya I. Shaygallyamova

Format Sitasi

Movchan, I., Yakovleva, A., Frid, V., Movchan, A., Shaygallyamova, Z.I. (2022). Modelling of seismic assessment for large geological systems. https://doi.org/10.1098/rsta.2021.0393

Akses Cepat

Lihat di Sumber doi.org/10.1098/rsta.2021.0393
Informasi Jurnal
Tahun Terbit
2022
Bahasa
en
Total Sitasi
Sumber Database
Semantic Scholar
DOI
10.1098/rsta.2021.0393
Akses
Open Access ✓