Information on elastic parameters obtained from the amplitudes of reflected waves

Dębski, Wojciech; Tarantola, Albert

doi:10.1190/1.1443877

Cited by 98 publications

(44 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…As previously pointed out in Section 2.3 and 3.3, the uncertainty (shown by the error bar) of Z p or Z s is less than that of density. The reason is that the density is poorly resolved by P-waves seismic data (Debski and Tarantola, 1995;Igel et al, 1996), but the inverted average density statistically approximates the true density model. rjMCMC.…”

Section: Synthetic Case Studymentioning

confidence: 99%

Seismic inversion and uncertainty analysis using a transdimensional Markov chain Monte Carlo method

Zhu

Gibson

2016

SEG Technical Program Expanded Abstracts 2016

View full text Add to dashboard Cite

We use a transdimensional inversion algorithm, reversible jump MCMC (rjMCMC), in the seismic waveform inversion of post-stack and prestack data to characterize reservoir properties such as seismic wave velocity, density as well as impedance and then estimate uncertainty. Each seismic trace is inverted independently based on a layered earth model. The model dimensionality is defined as the number of the layers multiplied with the number of model parameters per layer. The rjMCMC is able to infer the number of model parameters from data itself by allowing it to vary in the iterative inversion process, converge to proper parameterization and prevent underparameterization and overparameterization. We also use rjMCMC to enhance uncertainty estimation since it can transdimensionally sample different model spaces of different dimensionalities and can prevent a biased sampling in only one space which may have a different dimensionality than that of the true model space. An ensemble of solutions from difference spaces can statistically reduce the bias for parameter estimation and uncertainty quantification. Inversion uncertainty is comprised of property uncertainty and location uncertainty. Our study revealed that the inversion uncertainty is correlated with the discontinuity of property in such a way that 1) a smaller discontinuity will induce a lower uncertainty in property at the discontinuity but also a higher uncertainty of the location of that discontinuity and 2) a larger discontinuity will induce a higher uncertainty in property at the discontinuity but also a higher ''certainty'' of the location of that discontinuity. Therefore, there is a trade-off between the property uncertainty and the location uncertainty. To our surprise, there is a lot of hidden information in the uncertainty result that we can actually take advantage of due to this trade-off effect. On the basis of our study ii using rjMCMC, we propose to use the inversion uncertainty as a novel attribute in an optimistic way to characterize the magnitude and the location of subsurface discontinuities and reflectors. important it is to estimate the uncertainty, and I used another method for two years but it turned out that method was unsuccessful for solving my research problems because it couldn't answer the question for uncertainty assessment. This is one of the biggest mistakes that I have ever made because I wasn't aware of the importance of my advisor's words and questions. Indeed, research is not always successful and smooth and I did encounter failures, but I didn't give up.

show abstract

Section: Synthetic Case Studymentioning

confidence: 99%

Seismic inversion and uncertainty analysis using a transdimensional Markov chain Monte Carlo method

Zhu

Gibson

2016

SEG Technical Program Expanded Abstracts 2016

View full text Add to dashboard Cite

show abstract

“…The reason is the low sensitivity of the seismic velocity and density to variations in fluid saturation (Castagna and Backus, 1993;Debski and Tarantola, 1995;Plessix and Bork, 2000). A porosity greater than 30% is required to have a significant velocity difference between a water-and hydrocarbon-saturated reservoir.…”

Section: Introduction To the Csem Methodsmentioning

confidence: 99%

Controlled-source electromagnetics for reservoir monitoring on land

Wirianto¹

2012

Geophysics

View full text Add to dashboard Cite

“…In marine reflection seismic data, the presence of only one propagation mode impedes the opportunity to obtain independent estimates of P-wave (Vp) and S-wave velocity (Vs) (Jin et al, 1992;Igel et al, 1996); on the other hand, density is strongly coupled with P-wave velocity at narrow reflection angle; the two parameters can't be effectively resolved and in fact yield a posterior reconstruction of the P-impedance model (Tarantola, 1986;Operto et al, 2013). Here we choose to parametrise the reflectivity of the earth model as a distribution of P-impedance, Poisson's ratio and density (Debski & Tarantola, 1995;Igel et al, 1996), super-imposed to a long-wavelength P-wave velocity model that controls the wavefield kinematic (Tarantola, 1986;Jannane, 1989).…”

Section: A Strategy For the Multi-parameter Problemmentioning

confidence: 99%

“…Debski & Tarantola, 1995;Jannane, 1989;Igel et al, 1996). We conduct a sensitivity analysis on a simple homogeneous model with a low impedance 50 cm thick layer, whose density is changed at constant impedance, as a function of the maximum reflection angle at the target.…”

Section: Sensitivity To Constant-impedance Density Variationsmentioning

confidence: 99%

Pre-stack full waveform inversion of ultra-high-frequency marine seismic reflection data

Provenzano

Vardy

Henstock

2017

Geophysical Journal International

View full text Add to dashboard Cite

SUMMARYThe full waveform inversion (FWI) of seismic reflection data aims to reconstruct a detailed physical properties model of the subsurface, fitting both the amplitude and traveltime of the reflections generated at physical discontinuities in the propagation medium. Unlike reservoirscale seismic exploration, where seismic inversion is a widely adopted remote characterisation tool, ultra high frequency (UHF, 0.2-4.0 kHz) multi-channel marine reflection seismology is still most often limited to a qualitative interpretation of the reflections' architecture. Here we propose an elastic full waveform inversion methodology, custom-tailored for pre-stack UHF marine data in vertically heterogeneous media to obtain a decimetric-scale distribution of Pimpedance, density and Poisson's ratio within the shallow sub-seabed sediments. We address the deterministic multi-parameter inversion in a sequential fashion. The complex trace instantaneous phase is first inverted for the P-wave velocity to make-up for the lack of low-frequency in the data and reduce the non-linearity of the problem. This is followed by a short-offset Pimpedance optimisation and a further step of full offset range Poisson's ratio inversion. Provided that the seismogram contains wide reflection angles (> 40 degrees), we show that it is possible to invert for density and decompose a-posteriori the relative contribution of P-wave velocity and density to the P-impedance. A broad range of synthetic tests is used to prove the potential of the methodology and highlights sensitivity issues specific to UHF seismic. An example application to real data is also presented. In the real case, trace normalisation is applied to minimise the systematic error deriving from an inaccurate source wavelet estimation. G. Provenzano et al.The inverted model for the top 15 meters of the sub-seabed agrees with the local lithological information and core-log data. Thus we can obtain a detailed remote characterisation of the shallow sediments using a multi-channel sub-bottom profiler within a reasonable computing cost and with minimal pre-processing. This has the potential to reduce the need of extensive geotechnical coring campaigns.

show abstract

Information on elastic parameters obtained from the amplitudes of reflected waves

Cited by 98 publications

References 0 publications

Seismic inversion and uncertainty analysis using a transdimensional Markov chain Monte Carlo method

Seismic inversion and uncertainty analysis using a transdimensional Markov chain Monte Carlo method

Controlled-source electromagnetics for reservoir monitoring on land

Pre-stack full waveform inversion of ultra-high-frequency marine seismic reflection data

Contact Info

Product

Resources

About