Fracture detection from Azimuth-dependent seismic inversion in joint time–frequency domain

Abstract Detection of fracture properties can be implemented using azimuth-dependent seismic inversion for optimal model parameters in time or frequency domain. Considering the respective potentials for sensitivities of inversion resolution and anti-noise performance in time and frequency domain, we...

Descripción completa

Guardado en:

Detalles Bibliográficos
Autores principales:	Xinpeng Pan, Dazhou Zhang, Pengfei Zhang
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/fc137dc98ab14d4bb8af070b247cca51
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

id	oai:doaj.org-article:fc137dc98ab14d4bb8af070b247cca51
record_format	dspace
spelling	oai:doaj.org-article:fc137dc98ab14d4bb8af070b247cca512021-12-02T14:12:45ZFracture detection from Azimuth-dependent seismic inversion in joint time–frequency domain10.1038/s41598-020-80021-w2045-2322https://doaj.org/article/fc137dc98ab14d4bb8af070b247cca512021-01-01T00:00:00Zhttps://doi.org/10.1038/s41598-020-80021-whttps://doaj.org/toc/2045-2322Abstract Detection of fracture properties can be implemented using azimuth-dependent seismic inversion for optimal model parameters in time or frequency domain. Considering the respective potentials for sensitivities of inversion resolution and anti-noise performance in time and frequency domain, we propose a more robust azimuth-dependent seismic inversion method to achieve fracture detection by combining the Bayesian inference and joint time–frequency-domain inversion theory. Both Cauchy Sparse and low-frequency constraint regularizations are introduced to reduce multi-solvability of model space and improve inversion reliability of model parameters. Synthetic data examples demonstrate that the frequency bandwidth of inversion result is almost the same for time, frequency and joint time–frequency domain inversion in seismic dominant frequency band using the noise-free data, but the frequency bandwidth in joint time–frequency domain is larger than that in time and frequency domains using low- signal-to-noise-ratio (SNR) data. The results of cross-correlation coefficients validate that the joint time–frequency-domain inversion retains both the excellent characteristics of high resolution in frequency-domain inversion and the advantage of strong anti-noise ability in time-domain inversion. A field data example further demonstrates that our proposed inversion approach in joint time–frequency domain may provide a more stable technique for fracture detection in fractured reservoirs.Xinpeng PanDazhou ZhangPengfei ZhangNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-15 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Xinpeng Pan Dazhou Zhang Pengfei Zhang Fracture detection from Azimuth-dependent seismic inversion in joint time–frequency domain
description	Abstract Detection of fracture properties can be implemented using azimuth-dependent seismic inversion for optimal model parameters in time or frequency domain. Considering the respective potentials for sensitivities of inversion resolution and anti-noise performance in time and frequency domain, we propose a more robust azimuth-dependent seismic inversion method to achieve fracture detection by combining the Bayesian inference and joint time–frequency-domain inversion theory. Both Cauchy Sparse and low-frequency constraint regularizations are introduced to reduce multi-solvability of model space and improve inversion reliability of model parameters. Synthetic data examples demonstrate that the frequency bandwidth of inversion result is almost the same for time, frequency and joint time–frequency domain inversion in seismic dominant frequency band using the noise-free data, but the frequency bandwidth in joint time–frequency domain is larger than that in time and frequency domains using low- signal-to-noise-ratio (SNR) data. The results of cross-correlation coefficients validate that the joint time–frequency-domain inversion retains both the excellent characteristics of high resolution in frequency-domain inversion and the advantage of strong anti-noise ability in time-domain inversion. A field data example further demonstrates that our proposed inversion approach in joint time–frequency domain may provide a more stable technique for fracture detection in fractured reservoirs.
format	article
author	Xinpeng Pan Dazhou Zhang Pengfei Zhang
author_facet	Xinpeng Pan Dazhou Zhang Pengfei Zhang
author_sort	Xinpeng Pan
title	Fracture detection from Azimuth-dependent seismic inversion in joint time–frequency domain
title_short	Fracture detection from Azimuth-dependent seismic inversion in joint time–frequency domain
title_full	Fracture detection from Azimuth-dependent seismic inversion in joint time–frequency domain
title_fullStr	Fracture detection from Azimuth-dependent seismic inversion in joint time–frequency domain
title_full_unstemmed	Fracture detection from Azimuth-dependent seismic inversion in joint time–frequency domain
title_sort	fracture detection from azimuth-dependent seismic inversion in joint time–frequency domain
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/fc137dc98ab14d4bb8af070b247cca51
work_keys_str_mv	AT xinpengpan fracturedetectionfromazimuthdependentseismicinversioninjointtimefrequencydomain AT dazhouzhang fracturedetectionfromazimuthdependentseismicinversioninjointtimefrequencydomain AT pengfeizhang fracturedetectionfromazimuthdependentseismicinversioninjointtimefrequencydomain
_version_	1718391823391522816

Fracture detection from Azimuth-dependent seismic inversion in joint time–frequency domain

Ejemplares similares