Integrated kinematic time-lapse inversion workflow leveraging full-waveform inversion and machine learning-Reference-Cited by-同舟云学术

Integrated kinematic time-lapse inversion workflow leveraging full-waveform inversion and machine learning

Published:2019-12 Issue:12 Volume:38 Page:943-948
ISSN:1070-485X
Container-title:The Leading Edge
language:en
Short-container-title:The Leading Edge

Author:

Maharramov Musa¹,Willemsen Bram²,Routh Partha S.¹,Peacock Emily F.¹,Froneberger Mark²,Robinson Alana P.²,Bear Glenn W.³,Lazaratos Spyros K.²

Affiliation:

1. ExxonMobil Upstream Research Company, Spring, Texas, USA.

2. ExxonMobil Upstream Integrated Solutions Company, Spring, Texas, USA.

3. ExxonMobil Services and Technology, Bangalore, India.

Abstract

We demonstrate that a workflow combining emergent time-lapse full-waveform inversion (FWI) and machine learning technologies can address the demand for faster time-lapse processing and analysis. During the first stage of our proposed workflow, we invert long-wavelength velocity changes using a tomographically enhanced version of multiparameter simultaneous reflection FWI with model-difference regularization. Short-wavelength changes are inverted during the second stage of the workflow by a specialized high-resolution image-difference tomography algorithm using a neural network. We discuss application areas for each component of the workflow and show the results of a West Africa case study.

Publisher

Society of Exploration Geophysicists

Subject

Geology,Geophysics

Link

https://library.seg.org/doi/pdf/10.1190/tle38120943.1

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