Constrained waveform inversion for automatic salt flooding

Author:

Esser Ernie12,Guasch Lluís13,Herrmann Felix J.12,Warner Mike13

Affiliation:

1. Sub Salt Solutions Limited, London.

2. The University of British Columbia, Vancouver.

3. Imperial College London.

Abstract

Given appropriate data acquisition, processing to remove nonprimary arrivals, and use of an accurate migration algorithm, it is the quality of the subsurface velocity model that typically controls the quality of imaging that can be obtained from salt-affected seismic data. Full-waveform inversion has the potential to improve the accuracy, resolution, repeatability, and speed with which such velocity models can be generated, but, in the absence of an accurate starting model, that potential is difficult to realize in practice. Presented are successful inversion results, obtained from synthetic subsalt models, using a robust full-waveform inversion code that includes constraints upon the set of allowable earth models. These constraints include limitations on the total variation of the velocity of the model and, most significantly, on the asymmetric variation of velocity with depth such that negative velocity excursions are limited. During the iteration, these constraints are relaxed progressively so that the final model is driven principally by the seismic data, but the constraints act to steer the inversion path away from local minima in its early stages. This methodology is applied to portions of the 2004 BP benchmark and Phase I SEAM salt models, recovering an accurate model of the salt body, including its base and flanks, and an accurate model of the subsalt velocity structure, starting from one-dimensional velocity models that are severely cycle skipped. This approach removes entirely the requirement to pick salt boundaries from migrated seismic data, and acts as a form of automatic salt and sediment flooding during full-waveform inversion.

Publisher

Society of Exploration Geophysicists

Subject

Geology,Geophysics

Reference5 articles.

1. Billette, F. J., and S. Brandsberg-Dahl, 2005, The 2004 BP velocity benchmark: 67th EAGE Annual International Conference and Exhibition, Extended Abstracts.

2. Esser, E., L. Guasch, T. van Leeuwen, A. Y. Aravkin, and F. J. Herrmann, 2015, Total variation regularization strategies in full waveform inversion for improving robustness to noise, limited data and poor initializations: Technical Report TR-EOAS-2015-5, 06 2015. https://www.slim.eos.ubc.ca/Publications/Public/TechReport/2015/esser2015tvwri/esser2015tvwri.html, accessed 16 February 2016.

3. Fehler, M., and P. J. Keliher, 2011, Model Development, Chapter 2, 15–50, http://dx.doi.org/10.1190/1.9781560802945.ch2.

4. Guo, Z., and M. V. de Hoop, 2013, Shape optimization and level set method in full waveform inversion with 3d body reconstruction: 83rd Annual International Meeting, SEG, Expanded Abstracts, 1079–1083, http://dx.doi.org/10.1190/segam2013-1057.1.

5. Nonlinear total variation based noise removal algorithms

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