Reducing seismic reflector distortion beneath gas clouds in the Malay Basin using full-wavefield imaging approaches

2020 ◽  
Vol 39 (8) ◽  
pp. 591a1-591a8
Author(s):  
Ahmad Riza Ghazali ◽  
Muhammad Hafizal Mad Zahir ◽  
Muhammad Faizal Abdul Rahim ◽  
Kefeng Xin ◽  
Farah Syazana Dzulkefli ◽  
...  
Keyword(s):  
Seismic Imaging ◽  
Waveform Inversion ◽  
Implementation Strategies ◽  
Effective Medium ◽  
Full Waveform ◽  
Seismic Image ◽  
Inversion Techniques ◽  
Gas Cloud ◽  
Complex Transmission

A seismic example from the Malay Basin is presented, demonstrating improved seismic imaging beneath gas clouds using full-wavefield imaging approaches. Overall imaging concepts, synthetic examples, and field implementation strategies are discussed, and results that tie with well information are presented. Seismic imaging beneath gas clouds using the full-wavefield redatuming technique improves the image by estimating the waveform transmission operators via equivalent-medium representation of the overburden from the gas cloud reflection response for use in a form of multidimensional deconvolution of the wavefield. The other example shown uses the full-wavefield migration seismic imaging technique, which utilizes primaries and higher-order multiples as signals to improve the reflectivity estimation in imaging. The demonstrated full-wavefield imaging approach uses information carried by the gas cloud reflection response to correct seismic image distortion. Removing the internal multiple using conventional demultiple processing in the gas cloud area will also remove the valuable information of the subsurface that it carries. Such multiples must be preserved for this method to be successful. The information is translated into transmission operators that are estimated by simulating the reflection response through an effective medium of the gas cloud overburden. The effective medium is obtained via nonlinear full-waveform inversion techniques from the reflections of the gas cloud overburden area. Finally, a deconvolutional process removes the transmission operators from the gas cloud reflections and recovers the underlying reflectors. Full-wavefield imaging can reconstruct the amplitudes of the reflection response below a gas cloud overburden zone so that the complex transmission imprint on the area underneath is removed properly. The Malay Basin field case study shows that implementation of this approach can provide a reliable amplitude image of the subsurface affected by gas clouds, calibrated and verified by the well information.

Downscaling seismic tomography models

2021 ◽  
Author(s):  
Navid Hedjazian ◽  
Thomas Bodin ◽  
Yann Capdeville
Keyword(s):  
Seismic Imaging ◽  
Waveform Inversion ◽  
Effective Medium ◽  
Scale Model ◽  
Multiscale Approach ◽  
Full Waveform Inversion ◽  
Fine Scale ◽  
Full Waveform ◽  
Macro Scale ◽  
Scale Models

<p>Seismic imaging techniques such as elastic full waveform inversion (FWI) have their spatial resolution limited by the maximum frequency present in the observed waveforms. Scales smaller than a fraction of the minimum wavelength cannot be resolved, only a smoothed version of the true underlying medium can be recovered. Application of FWI to media containing small and strong heterogeneities therefore remains problematic. This smooth tomographic image is related to the effective elastic properties, which can be exposed with the homogenization theory of wave propagation. We study how this theory can be used in the FWI context. The seismic imaging problem is broken down in a two-stage multiscale approach. In the first step, called homogenized full waveform inversion (HFWI), observed waveforms are inverted for a macro-scale, fully anisotropic effective medium, smooth at the scale of the shortest wavelength present in the wavefield. The solution being an effective medium, it is difficult to directly interpret it. It requires a second step, called downscaling, where the macro-scale image is used as data, and the goal is to recover micro-scale parameters. All the information contained in the waveforms is extracted in the HFWI step. The solution of the downscaling step is highly non-unique as many fine-scale models may share the same long wavelength effective properties. We therefore rely on the introduction of external a priori information. In this step, the forward theory is the homogenization itself. It is computationally cheap, allowing to consider geological models with more complexity.</p><p>In a first approach to downscaling, the ensemble of potential fine-scale models is described with an object-based parametrization, and explored with a MCMC algorithm. We illustrate the method with a synthetic cavity detection problem. In a second approach, the prior information is introduced by the means of a training image, and the fine-scale model is recovered with a multi-point statistics algorithm. We apply this method on a subsurface synthetic problem, where the goal is to recover geological facies.</p><p> </p>

A new parameter set for anisotropic multiparameter full-waveform inversion and application to a North Sea data set

Geophysics ◽  
2016 ◽  
Vol 81 (4) ◽  
pp. U25-U38 ◽  
Author(s):  
Nuno V. da Silva ◽  
Andrew Ratcliffe ◽  
Vetle Vinje ◽  
Graham Conroy
Keyword(s):  
North Sea ◽  
Waveform Inversion ◽  
Real Data ◽  
Model Parameters ◽  
Full Waveform Inversion ◽  
Radiation Patterns ◽  
Data Set ◽  
Full Waveform ◽  
Seismic Image ◽  
Central North Sea

Parameterization lies at the center of anisotropic full-waveform inversion (FWI) with multiparameter updates. This is because FWI aims to update the long and short wavelengths of the perturbations. Thus, it is important that the parameterization accommodates this. Recently, there has been an intensive effort to determine the optimal parameterization, centering the fundamental discussion mainly on the analysis of radiation patterns for each one of these parameterizations, and aiming to determine which is best suited for multiparameter inversion. We have developed a new parameterization in the scope of FWI, based on the concept of kinematically equivalent media, as originally proposed in other areas of seismic data analysis. Our analysis is also based on radiation patterns, as well as the relation between the perturbation of this set of parameters and perturbation in traveltime. The radiation pattern reveals that this parameterization combines some of the characteristics of parameterizations with one velocity and two Thomsen’s parameters and parameterizations using two velocities and one Thomsen’s parameter. The study of perturbation of traveltime with perturbation of model parameters shows that the new parameterization is less ambiguous when relating these quantities in comparison with other more commonly used parameterizations. We have concluded that our new parameterization is well-suited for inverting diving waves, which are of paramount importance to carry out practical FWI successfully. We have demonstrated that the new parameterization produces good inversion results with synthetic and real data examples. In the latter case of the real data example from the Central North Sea, the inverted models show good agreement with the geologic structures, leading to an improvement of the seismic image and flatness of the common image gathers.

Time-lapse full waveform inversion based on curvelet transform: Case study of CO2 storage monitoring

2021 ◽  
Vol 110 ◽  
pp. 103417
Author(s):  
Dong Li ◽  
Suping Peng ◽  
Xingguo Huang ◽  
Yinling Guo ◽  
Yongxu Lu ◽  
...  
Keyword(s):  
Co2 Storage ◽  
Waveform Inversion ◽  
Curvelet Transform ◽  
Time Lapse ◽  
Full Waveform Inversion ◽  
Full Waveform

Reflection Full Waveform Inversion of Walkaway VSP – Abu Dhabi Case Study

2020 ◽  
Author(s):  
A. Shigematsu ◽  
Y. Nakamura ◽  
A. Kato ◽  
T. Mouri ◽  
G. Sakata ◽  
...  
Keyword(s):  
Waveform Inversion ◽  
Abu Dhabi ◽  
Full Waveform Inversion ◽  
Full Waveform ◽  
Walkaway Vsp

Full-waveform inversion for full-wavefield imaging: Decades in the making

2021 ◽  
Vol 40 (5) ◽  
pp. 324-334
Author(s):  
Rongxin Huang ◽  
Zhigang Zhang ◽  
Zedong Wu ◽  
Zhiyuan Wei ◽  
Jiawei Mei ◽  
...  
Keyword(s):  
Model Building ◽  
Seismic Imaging ◽  
Structural Information ◽  
Waveform Inversion ◽  
Velocity Model ◽  
Data Sets ◽  
Full Waveform Inversion ◽  
Data Types ◽  
Velocity Models ◽  
Full Waveform

Seismic imaging using full-wavefield data that includes primary reflections, transmitted waves, and their multiples has been the holy grail for generations of geophysicists. To be able to use the full-wavefield data effectively requires a forward-modeling process to generate full-wavefield data, an inversion scheme to minimize the difference between modeled and recorded data, and, more importantly, an accurate velocity model to correctly propagate and collapse energy of different wave modes. All of these elements have been embedded in the framework of full-waveform inversion (FWI) since it was proposed three decades ago. However, for a long time, the application of FWI did not find its way into the domain of full-wavefield imaging, mostly owing to the lack of data sets with good constraints to ensure the convergence of inversion, the required compute power to handle large data sets and extend the inversion frequency to the bandwidth needed for imaging, and, most significantly, stable FWI algorithms that could work with different data types in different geologic settings. Recently, with the advancement of high-performance computing and progress in FWI algorithms at tackling issues such as cycle skipping and amplitude mismatch, FWI has found success using different data types in a variety of geologic settings, providing some of the most accurate velocity models for generating significantly improved migration images. Here, we take a step further to modify the FWI workflow to output the subsurface image or reflectivity directly, potentially eliminating the need to go through the time-consuming conventional seismic imaging process that involves preprocessing, velocity model building, and migration. Compared with a conventional migration image, the reflectivity image directly output from FWI often provides additional structural information with better illumination and higher signal-to-noise ratio naturally as a result of many iterations of least-squares fitting of the full-wavefield data.

Sign in / Sign up

Export Citation Format

Share Document