Deep Learning for Seismic Inverse Problems: Toward the Acceleration of Geophysical Analysis Workflows

Amir Adler; Mauricio Araya-Polo; Tomaso Poggio

doi:10.1109/MSP.2020.3037429

Deep Learning for Seismic Inverse Problems: Toward the Acceleration of Geophysical Analysis Workflows

Amir Adler
, Mauricio Araya-Polo
, Tomaso Poggio

نتاج البحث: نشر في مجلة › مقالة › مراجعة النظراء

146 اقتباسات (Scopus)

ملخص

Seismic inversion is a fundamental tool in geophysical analysis, providing a window into Earth. In particular, it enables the reconstruction of large-scale subsurface Earth models for hydrocarbon exploration, mining, earthquake analysis, shallow hazard assessment, and other geophysical tasks.

اللغة الأصلية	الإنجليزيّة
رقم المقال	9363496
الصفحات (من إلى)	89-119
عدد الصفحات	31
دورية	IEEE Signal Processing Magazine
مستوى الصوت	38
رقم الإصدار	2
المعرِّفات الرقمية للأشياء	https://doi.org/10.1109/MSP.2020.3037429
حالة النشر	نُشِر - مارس 2021
منشور خارجيًا	نعم

الوصول إلى المستند

10.1109/MSP.2020.3037429

الملفات والروابط الأخرى

Link to publication in Scopus

قم بذكر هذا

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title = "Deep Learning for Seismic Inverse Problems: Toward the Acceleration of Geophysical Analysis Workflows",

abstract = "Seismic inversion is a fundamental tool in geophysical analysis, providing a window into Earth. In particular, it enables the reconstruction of large-scale subsurface Earth models for hydrocarbon exploration, mining, earthquake analysis, shallow hazard assessment, and other geophysical tasks.",

author = "Amir Adler and Mauricio Araya-Polo and Tomaso Poggio",

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year = "2021",

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doi = "10.1109/MSP.2020.3037429",

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AU - Araya-Polo, Mauricio

AU - Poggio, Tomaso

PY - 2021/3

Y1 - 2021/3

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AB - Seismic inversion is a fundamental tool in geophysical analysis, providing a window into Earth. In particular, it enables the reconstruction of large-scale subsurface Earth models for hydrocarbon exploration, mining, earthquake analysis, shallow hazard assessment, and other geophysical tasks.

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DO - 10.1109/MSP.2020.3037429

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AN - SCOPUS:85102044463

SN - 1053-5888

VL - 38

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JO - IEEE Signal Processing Magazine

JF - IEEE Signal Processing Magazine

IS - 2

M1 - 9363496

ER -

Deep Learning for Seismic Inverse Problems: Toward the Acceleration of Geophysical Analysis Workflows

ملخص

الوصول إلى المستند

الملفات والروابط الأخرى

بصمة

قم بذكر هذا