Next Article in Journal
Modeling the Natural Drainage Network of the Grand River in Southern Ontario: Agriculture May Increase Total Channel Length of Low-Order Streams
Previous Article in Journal
Advances in Snow Hydrology Using a Combined Approach of GNSS In Situ Stations, Hydrological Modelling and Earth Observation—A Case Study in Canada
Previous Article in Special Issue
High-Resolution Seismic Data Deconvolution by A0 Algorithm
Article Menu
Issue 1 (January) cover image

Export Article

Open AccessArticle

Constrained Full Waveform Inversion for Borehole Multicomponent Seismic Data

1
Skolkovo Institute of Science and Technology, Moscow 121205, Russia
2
Department of Geosciences and Environment, University of Cergy-Pontoise, 95000 Neuville-sur-Oise, France
*
Author to whom correspondence should be addressed.
Geosciences 2019, 9(1), 45; https://doi.org/10.3390/geosciences9010045
Received: 2 December 2018 / Revised: 25 December 2018 / Accepted: 25 December 2018 / Published: 16 January 2019
(This article belongs to the Special Issue Numerical Methods of Geophysical Fields Inversion)
  |  
PDF [6862 KB, uploaded 16 January 2019]
  |  

Abstract

Full-waveform inversion for borehole seismic data is an ill-posed problem and constraining the problem is crucial. Constraints can be imposed on the data and model space through covariance matrices. Usually, they are set to a diagonal matrix. For the data space, signal polarization information can be used to evaluate the data uncertainties. The inversion forces the synthetic data to fit the polarization of observed data. A synthetic inversion for a 2D-2C data estimating a 1D elastic model shows a clear improvement, especially at the level of the receivers. For the model space, horizontal and vertical spatial correlations using a Laplace distribution can be used to fill the model space covariance matrix. This approach reduces the degree of freedom of the inverse problem, which can be quantitatively evaluated. Strong horizontal spatial correlation distances favor a tabular geological model whenever it does not contradict the data. The relaxation of the spatial correlation distances from large to small during the iterative inversion process allows the recovery of geological objects of the same size, which regularizes the inverse problem. Synthetic constrained and unconstrained inversions for 2D-2C crosswell data show the clear improvement of the inversion results when constraints are used. View Full-Text
Keywords: constrained inversion; elastic full waveform inversion; multicomponent seismic data; borehole seismic constrained inversion; elastic full waveform inversion; multicomponent seismic data; borehole seismic
Figures

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
SciFeed

Share & Cite This Article

MDPI and ACS Style

Charara, M.; Barnes, C. Constrained Full Waveform Inversion for Borehole Multicomponent Seismic Data. Geosciences 2019, 9, 45.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Geosciences EISSN 2076-3263 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top