Elastic full-waveform inversion with probabilistic petrophysical model constraints

Geophysics ◽  
2020 ◽  
Vol 85 (2) ◽  
pp. R101-R111 ◽  
Author(s):  
Odette Aragao ◽  
Paul Sava

Full-waveform inversion (FWI) based on the minimization of data residuals may not enhance our understanding of the subsurface and can at times lead to misleading subsurface models. Additionally, unconstrained multiparameter FWI may also lead to models that do not represent realistic lithology for independently derived parameters. We have developed a method for elastic FWI that explicitly imposes petrophysical restrictions to guide models toward realistic and feasible lithology, that is, to subsurface models consistent with the seismic data and with the underlying petrophysics. We exploit petrophysical information, such as that provided by well logs, to constrain the inversion and to avoid implausible models. We achieve this goal by confining the inverted models to a feasible region defined by a probability density function instead of imposing lithologic facies as a function of position. Inside this feasible petrophysical regime, the inverted models do not need to obey a specific trend, that is, we do not link the parameters with explicit and potentially inaccurate petrophysical relations. Instead, we define a petrophysical basin of attraction that confines models to a feasible region validated by regional lithologic and petrophysical information. We find through elastic models that incorporating probabilistic petrophysical constraints into the inversion objective function leads to models that are superior to models obtained either without constraints or with approximate analytic constraints. In addition, we discover that these constraints can help in mitigating common issues affecting elastic FWI, such as the artifacts produced by interparameter crosstalk and limited acquisition coverage.

Geophysics ◽  
2016 ◽  
Vol 81 (2) ◽  
pp. R29-R44 ◽  
Author(s):  
Qingchen Zhang ◽  
Hui Zhou ◽  
Qingqing Li ◽  
Hanming Chen ◽  
Jie Wang

Accurate estimation of source wavelet is crucial in a successful full-waveform inversion (FWI); however, it cannot be guaranteed in the case of real seismic data. We have developed time-domain source-independent elastic FWI using the convolution-based objective function that was originally developed for acoustic FWI. We have applied a new time window on the reference traces in the objective function to suppress the noises induced by the convolution and crosscorrelation operations. Also, we have adopted [Formula: see text]-, Huber-, and hybrid-norm objective functions to improve the antinoise ability of our algorithm. We implemented a multiscale inversion strategy to conduct the tests with a quasi-Newton limited-memory Broyden-Fletcher-Goldfarb-Shanno (L-BFGS) method to reduce the sensitivity to initial models and to improve the quality of inversion results. Synthetic tests verified that the new added time window can not only improve the inversion results, but also accelerate the convergence rate. Our method can be implemented successfully without a priori knowledge or accurate estimation of the source wavelet and can be more robust to Gaussian and spike noises, even for a Dirac wavelet. Finally, we applied our method to real seismic data. The similarity between the observed and modeled seismic data, the higher resolution of the migration image, and flatter common image gathers corresponding to the inverted models proved the relevance of our algorithm.


2017 ◽  
Vol 5 (3) ◽  
pp. SO1-SO10 ◽  
Author(s):  
Kai Lu ◽  
Jing Li ◽  
Bowen Guo ◽  
Lei Fu ◽  
Gerard Schuster

Full-waveform inversion of seismic data is often plagued by cycle-skipping problems such that an iterative optimization method often gets stuck in a local minimum. To avoid this problem, we simplify the objective function so that the iterative solution can quickly converge to a solution in the vicinity of the global minimum. The objective function is simplified by only using parsimonious and important portions of the data, which are defined as skeletonized data. We have developed a mostly nonmathematical tutorial that explains the theory of wave-equation inversion of skeletonized data. We also demonstrate its effectiveness with examples.


Author(s):  
Ehsan Jamali Hondori ◽  
Chen Guo ◽  
Hitoshi Mikada ◽  
Jin-Oh Park

AbstractFull-waveform inversion (FWI) of limited-offset marine seismic data is a challenging task due to the lack of refracted energy and diving waves from the shallow sediments, which are fundamentally required to update the long-wavelength background velocity model in a tomographic fashion. When these events are absent, a reliable initial velocity model is necessary to ensure that the observed and simulated waveforms kinematically fit within an error of less than half a wavelength to protect the FWI iterative local optimization scheme from cycle skipping. We use a migration-based velocity analysis (MVA) method, including a combination of the layer-stripping approach and iterations of Kirchhoff prestack depth migration (KPSDM), to build an accurate initial velocity model for the FWI application on 2D seismic data with a maximum offset of 5.8 km. The data are acquired in the Japan Trench subduction zone, and we focus on the area where the shallow sediments overlying a highly reflective basement on top of the Cretaceous erosional unconformity are severely faulted and deformed. Despite the limited offsets available in the seismic data, our carefully designed workflow for data preconditioning, initial model building, and waveform inversion provides a velocity model that could improve the depth images down to almost 3.5 km. We present several quality control measures to assess the reliability of the resulting FWI model, including ray path illuminations, sensitivity kernels, reverse time migration (RTM) images, and KPSDM common image gathers. A direct comparison between the FWI and MVA velocity profiles reveals a sharp boundary at the Cretaceous basement interface, a feature that could not be observed in the MVA velocity model. The normal faults caused by the basal erosion of the upper plate in the study area reach the seafloor with evident subsidence of the shallow strata, implying that the faults are active.


2019 ◽  
Vol 16 (6) ◽  
pp. 1017-1031 ◽  
Author(s):  
Yong Hu ◽  
Liguo Han ◽  
Rushan Wu ◽  
Yongzhong Xu

Abstract Full Waveform Inversion (FWI) is based on the least squares algorithm to minimize the difference between the synthetic and observed data, which is a promising technique for high-resolution velocity inversion. However, the FWI method is characterized by strong model dependence, because the ultra-low-frequency components in the field seismic data are usually not available. In this work, to reduce the model dependence of the FWI method, we introduce a Weighted Local Correlation-phase based FWI method (WLCFWI), which emphasizes the correlation phase between the synthetic and observed data in the time-frequency domain. The local correlation-phase misfit function combines the advantages of phase and normalized correlation function, and has an enormous potential for reducing the model dependence and improving FWI results. Besides, in the correlation-phase misfit function, the amplitude information is treated as a weighting factor, which emphasizes the phase similarity between synthetic and observed data. Numerical examples and the analysis of the misfit function show that the WLCFWI method has a strong ability to reduce model dependence, even if the seismic data are devoid of low-frequency components and contain strong Gaussian noise.


2013 ◽  
Vol 56 (5) ◽  
pp. 685-703
Author(s):  
DONG Liang-Guo ◽  
CHI Ben-Xin ◽  
TAO Ji-Xia ◽  
LIU Yu-Zhu

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