Barry Hung

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

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.

3‐D tomographic Q inversion for compensating frequency dependent attenuation and dispersion

Following our previous work on Amplitude Tomography that deals with amplitudes alone, we extend our effort to include the compensation of bandwidth and phase of seismic signals that are distorted by seismic attenuation. Our new approach involves utilizing tomographic inversion for estimating the quality factor (Q) from prestack depth migrated common image gathers. By filtering the seismic data into different frequency bands and measuring the effect of attenuation on amplitudes in each band, the frequency dependent effect, which was ignored in our previous work, of attenuation is fully taken into account, allowing Q to be estimated from our tomographic method. By using the estimated Q volume in one of the migration methods that incorporates Q in the traveltime computation, we demonstrate, through examples, that our workflow provides an optimal compensation solution that resolves amplitude and bandwidth distortions due to seismic attenuation.

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

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.

Seismic trace interpolation using the pyramid transform

We present a new method called the pyramid transform for seismic trace interpolation. The pyramid transform is a resampling of data in the f-x-y domain that gives rise to frequency dependent spatial grids with a relationship that the sampling interval is inversely proportional to the frequency. Such transformation is reversible for wavefields. Using prediction filter, we demonstrate that seismic trace interpolation in the pyramid domain is more robust in the presence of noise and conflicting dips than interpolation in the conventional f-x-y domain.

3-D Tomographic Amplitude Inversion for Compensating Transmission Losses in the Overburden

A tomographic inversion approach using prestack depth migrated common image gathers is utilized to compensate reflection data for amplitude loss caused by transmission anomalies in the overburden. The approach has the advantage of estimating transmission losses from anywhere within the overburden using the actual seismic raypaths. Examples show that the method can mitigate amplitude attenuation caused by transmission anomalies and should be considered as one of the processes for amplitude preserving processing that is important for AVO analysis when transmission anomalies are present.

Interferometric OBC Surface Related Multiple Attenuation

Surface-related multiples in Ocean Bottom Cable (OBC) data cannot be removed by directly applying standard SRME, which requires sources and receivers that are surface consistent. The ray paths needed for a complete surface-multiple prediction can be achieved by combining streamer and OBC data. The combination allows fully data driven SRME to be extended to OBC data. However, streamer data is not always available. In this paper, we demonstrate that the required data to predict surface-related multiples in OBC data can be constructed using inter-source and inter-receiver interferometry, and the multiples can then be predicted similarly as in SRME. The work flow does not require knowing any subsurface information.

3D tomographic amplitude inversion for compensating amplitude attenuation

Introduction Spatial variations in the transmission properties of the overburden cause seismic amplitude distortions on deeper horizons and hence pose problems to the AVO analysis. One of the common causes of these transmission anomalies is gas within shallow sediment. This induces anomalous amplitude decay in zones beneath the gas anomaly, often making the identification and interpretation of deeper reflectors difficult. This in turn affects the ability to accurately predict reservoir properties. Thus, there is a need to compensate the amplitude loss caused by this kind of transmission anomalies.

3‐D tomographic amplitude inversion for compensating amplitude attenuation due to shallow gas

A tomographic inversion approach using prestack depth migrated common image gathers is utilized to compensate reflection data for amplitude loss caused by transmission anomalies, such as shallow gas, in the overburden. The approach has the advantage of estimating transmission losses from anywhere within the overburden using the actual seismic raypaths. Examples show that the method can mitigate amplitude attenuation caused by transmission anomalies and should be considered as one of the processes for amplitude preserving processing that is important for AVO analysis when transmission anomalies are present.