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Thrust complex imaging in the Timor Trough suffers from the fault shadows due to strong lateral velocity variation. We demonstrate a new workflow to tackle this. Broadband seismic data were acquired with high signal-to-noise ratio of low frequency. With broadband input, full waveform inversion (FWI) derived better velocity model at the shallow water thrust area where the reflection tomography has limitation. Compared to conventional tomography which has difficulty in addressing the sharp velocity boundary properly, fault constrained tomography (FCT) uses the interpreted fault planes as constraint for inversion and benefits from better low frequency penetration in the severe fault shadows. Broadband seismic and depth imaging with FWI and FCT make a step change over the thrust complex areas.

Receiver deghosting algorithms assuming a flat sea surface may be sub-optimal in the case of significant sea surface datum variations. We propose a method that begins by using the seismic data to calculate a sea surface profile. The sea surface profile is then provided to a modified linear Radon inversion scheme to model the receiver ghost. We compare receiver deghosting results using a flat sea surface datum and a variable sea surface datum on a marine dataset acquired in the North Sea. We show that receiver deghosting using a variable sea surface may improve wavefield separation; specifically, the clarity of the shallow reflectors is improved at the higher frequencies.

We introduce an inversion-driven free surface multiple modelling scheme based on multi-order Green’s functions. The approach optionally combines surface related multiple modelling with source designature and receiver deghosting. We demonstrate the effectiveness of the approach for peg-leg multiple suppression as well as highlighting the benefits of combined receiver deghosting and demultiple. In addition we show how the use of multiples can provide uplift for cable interpolation.

Ghost wavefield elimination is pivotal for improving the bandwidth and image resolution for marine seismic data. Synhronized multi-level source arrays, which aim to synchronize the primary wavefield and desynchronize the source ghost, can greatly attenuate the source ghost wavefield during acquistion. However, even with this advanced source design, some source deghosting is still needed and can be achieved using a 3D joint source inversion algorithm. We demonstrate that the joint source inversion method can properly and effectively eliminate residual source ghost in the synchronized multi-level source streamer data using both 2D synthetic data and 3D real data examples.

Time-lapse (4D) inversions deal with changes in seismic amplitudes and travel-times. This analysis is performed on migrated seismic images, which represent the spatial and time-lapse variability of the medium’s reflectivity. 4D reservoir analysis methods such as inversion and warping need to follow the structure of the data. Since migration effectively rotates the wavelet so that it is normal to the imaged reflectors, the traditional 1D (vertical) convolutional approach, used in 4D inversions to date, does not honour this directivity. For this reason we recently introduced a wave equation based method which provides an effective platform for structurally image consistent reservoir analysis. This must be used in processes such as wavelet extraction, inversion, warping and 4D time-strain inversion. In this paper, we show a data example from the 4D Baobab, comparing warping results for time-shifts and time-strains with a 1D convolutional and the new image consistent warping approach.

RTM surface offset gathers (SOG) contain subsalt events spanning the entire offset range (i.e., longer usable curvatures for tomography). RTM SOGs also have more reliable residual curvatures because each offset and azimuth group is migrated independently and does not interfere with the neighboring ones. RTM SOGs are more beneficial for full azimuth (FAZ) and ultra-long offset data.

We designed and implemented a practical and comprehensive workflow to mitigate missing source wavelet information and waveforms with vast spatial variation for land dynamite surveys and addressed the common challenges of acoustic-FWI application on land surveys during field data preparation.

The prediction of porosity is essential for the identification of productive hydrocarbon reservoirs in oil and gas exploration. Numerous useful technologies have been developed for porosity prediction in the subsurface, such as multiple attribute analysis, kriging, and cokriging. Kriging allows us to create spatial maps from point information such as well log measurements of porosity. Cokriging combines well log measurements of porosity with seismic attributes recorded between the wells to improve the estimation accuracy of the overall map. However, the traditional cokriging for porosity estimation is limited to only one seismic attribute. To introduce more geological information and improve the accuracy of prediction, we develop a new cokriging system that extends traditional cokriging to two secondary variables. In this study, our new cokriging system is applied to the Blackfoot seismic data from Alberta, and the final estimated map is shown to be an improvement over kriging and traditional single attribute cokriging. To show this improvement, "leave-one-out" cross-validation is employed to evaluate the accuracy of porosity prediction with kriging, traditional cokriging, and our new approach. Compared to kriging and traditional cokriging, an improved porosity map, with higher lateral geological resolution and smaller variance of estimation error, was achieved using the new cokriging system. We believe that the new approach can be considered for porosity prediction in any area of sparse well control.

In 4D land and especially for Permanent Reservoir Monitoring (PRM), changes of the subsurface induce unwanted signal variations that interfere with the 4D signal recorded from the reservoir. A three-month PRM pilot was carried out for Shell on the Peace River heavy oil field in Alberta, Canada in 2009. During this period, reservoir production was monitored using active buried sources and buried receivers. We took advantage of this continuous seismic recording to extract surface waves from recorded ambient noise using cross-correlation techniques. Surface wave tomography is then applied to produce daily time-lapse surface wave velocity maps that monitor velocity variations within the shallow subsurface. We provide an image of the shallow subsurface velocities showing generally higher values in the southern part of the area. This pattern correlates fairly well with the known presence of swamp (muskeg) in the area and the wells pad location. Calendar observation of velocity maps shows stronger variation at low frequencies with good spatial coherence. In the case of PRM and continuous seismic monitoring, these findings could help to discriminate, at least qualitatively, contributions due to shallow subsurface variations from actual reservoir 4D variations.