Reduced amplitude and distorted dispersion of seismic waves caused by attenuation, especially strong attenuation, always degrades the resolution of migrated images. To improve image resolution, we evaluated a methodology of compensating for attenuation (∼1∕Q) effects in reverse-time migration (Q-RTM). The Q-RTM approach worked by mitigating the amplitude attenuation and phase dispersion effects in source and receiver wavefields. Source and receiver wavefields were extrapolated using a previously published time-domain viscoacoustic wave equation that offered separated amplitude attenuation and phase dispersion operators. In our Q-RTM implementation, therefore, attenuation- and dispersion-compensated operators were constructed by reversing the sign of attenuation operator and leaving the sign of dispersion operator unchanged, respectively. Further, we designed a low-pass filter for attenuation and dispersion operators to stabilize the compensating procedure. Finally, we tested the Q-RTM approach on a simple layer model and the more realistic BP gas chimney model. Numerical results demonstrated that the Q-RTM approach produced higher resolution images with improved amplitude and phase compared to the noncompensated RTM, particularly beneath high-attenuation zones.

Q-compensated reverse-time migration

Model-based Water-layer Demultiple

Strong subsurface attenuation leads to distortion of amplitudes and phases of seismic waves propagating inside the earth. The amplitude and the dispersion losses from attenuation are often compensated for during prestack depth migration. However, most attenuation compensation or Q-compensation migration algorithms require an estimate of the background Q model. We have developed a wave-equation gradient optimization method that inverts for the subsurface Q distribution by minimizing a skeletonized misfit function e, where e is the sum of the squared differences between the observed and the predicted peak/centroid-frequency shifts of the early arrivals. The gradient is computed by migrating the observed traces weighted by the frequency shift residuals. The background Q model is perturbed until the predicted and the observed traces have the same peak frequencies or the same centroid frequencies. Numerical tests determined that an improved accuracy of the Q model by wave-equation Q tomography leads to...

/pdf/wave-equation-q-tomography-1st5zkxjmo.pdf

Wave-equation Q tomography

The calculation of the gradient in full-waveform inversion (FWI) usually involves crosscorrelating the forward-propagated source wavefield and the back-propagated data residual wavefield at...

https://library.seg.org/doi/pdf/10.1190/geo2017-0469.1

Accelerating full-waveform inversion with attenuation compensation

We have developed a theory of viscoelastic reverse time migration (RTM). The main feature of viscoelastic RTM is a compensation for P- and S-wave attenuation effects in seismic images during migration. The forward modeling engine is based on a viscoelastic wave equation involving fractional Laplacians. Because of the decoupled attenuation property, wave propagation can be simulated in three scenarios, i.e., only the amplitude loss effect, only the phase dispersion effect, or both effects simultaneously. This separation brings practical flexibility to studying attenuation effects on wave propagation and imaging. The backward modeling operator is constructed by reversing the sign of first-order time derivative amplitude loss operators. Synthetic examples determine the ability of viscoelastic RTM to illuminate degraded areas and shadow zones caused by attenuation. Numerical experiments also reveal that Q-compensated imaging is noticeably more accurate in kinematics and dynamics than elastic imaging i...

Viscoelastic reverse time migration with attenuation compensation

Summary Surface related multiple elimination (SRME) method is known to have difficulties in attenuating shallow water multiples Particularly, for water-layer related multiples in very shallow water environment such as seabeach-shallow water areas because the primary water-bottom reflection that is required by SRME for predicting the multiples is not recorded due to near offset gap Thus, in these situations, predictive deconvolution in either x-t or tau-p domain is often used in processing workflow to suppress this kind of multiples However, deconvolution also attenuates primary events that have a periodicity close to that of the waterlayer In this case study, we present a two-step processing workflow for removing free-surface multiples Firstly, we use a multi-channel prediction filter estimated from the multiples for attenuating water-layer related multiples Secondly, we apply SRME for suppressing other surface multiples generated by sub-surfaces underneath the waterbottom We demonstrate that this workflow provides an optimal suppression of free-surface multiples on marine data that have been recorded in the Bohai Sea offshore eastern China

Surface multiple attenuation in seabeach-shallow water, case study on data from the Bohai Sea

Summary The presence of gas, both as shallow pockets and as commercial reservoirs, has long been recognized as a significant problem in imaging seismic data. In this paper we describe how we successfully applied Q tomography and Q-PSDM technology to compensate the phase, frequency and amplitude loss due to shallow absorption, thus improving structure imaging and potentially accurate AVO/DHI analysis underneath shallow gas.

Compensating attenuation due to shallow gas through Q tomography and Q-PSDM, a case study in Brazil

Multiples due to shallow water are observed in seismic data acquired in various places such as the Gippsland Basin of Australia. These short period multiple reflections often pose problems to the interpretation of geological structures. They are not easily handled by conventional surface-related multiple elimination (SRME) methods because the recorded primary waterbottom reflection, which is required by SRME, is often indistinct in shallow water situations due to the near offset gap. Hence, predictive deconvolution in the x-t or ?-p domain is frequently used for attenuating shallow water multiples. However, besides multiples, deconvolution also attenuates primary events that have a periodicity which is close to that of the water-layer. In this paper, we present a workflow that involves first attenuating short-period water-layer related multiples (WLRMs) ? a process that we term shallow water demultiple (SWD); and then suppressing other longperiod free surface multiples using conventional SRME. SWD is a wavefield-consistent method that first makes use of WLRMs in the data to reconstruct the missing water-bottom primary reflection and then uses the reflection for predicting shallow WLRMs. It is data driven and takes into account the spatial varying nature of subsurface structures. Since the WLRM model predicted by SWD has similar amplitude and phase as the input data, very short matching filters, which are not possible if deconvolution is used, can be utilised in the adaptive subtraction process. We demonstrate, through real-data examples, that our workflow provides an optimal multiple attenuation solution in shallow water environment in comparison with conventional methods such as ?-p deconvolution or SRME alone.

https://www.tandfonline.com/doi/pdf/10.1081/22020586.2010.12041899

Joe Zhou

Papers

Surface multiple attenuation in seabeach-shallow water, case study on data from the Bohai Sea

Compensating attenuation due to shallow gas through Q tomography and Q-PSDM, a case study in Brazil

Shallow Water Demultiple

FWI-Guided Q Tomography and Q-PSDM for Imaging in the Presence of Complex Gas Clouds, A Case Study From Offshore Malaysia

Orthorhombic Velocity Model Building and Imaging of Luda Field with WAZ OBC Data