Commonly fitted by an ellipse, AVOAz is actually better approximated using limaçons. The article begins by reviewing the properties of the original limaçon, then explains how they can apply to AVOAz and finally illustrates how limaçons can help with the interpretation of anisotropy on real data.
Low-frequency seismic data are crucial for the success of full waveform inversion (FWI) used in velocity model building. Marine acquisition technologies have evolved to increase low-frequency seismic signals. However, significant low-frequency noise, often caused by water flowing across the streamers, still alters the signal-to-noise ratio. We propose to use an algorithm based on a dipole sparse tau-p inversion to attenuate low-frequency and high-dip noise. When applied to synthetic and real data sets, this method provides clean low-frequency input data to enhance the performance of FWI.
Ocean bottom node (OBN) data by nature have a broader bandwidth; however, the presence of source-side ghosts can reduce the useful frequency range and therefore damage seismic resolution. We demonstrate the benefits of 3D deghosting for OBN data from the Gulf of Mexico (GOM). By effectively removing ghost energy using 3D deghosting, images with a wider spectrum and a better signal-to-noise ratio (S/N) can be achieved. We also applied 3D angle-dependent source deghosting and designature to further increase the bandwidth.
Migration Velocity Analysis in the subsurface-domain measures velocity errors via (extended) image-domain residuals with respect to an ideal reference image and then updates the velocity model in order to minimize those residuals.Because of the similarity between images with similar extension parameter (shot number, offset, incidence angle, etc.), image-warping definitely represents a robust approach to compute image residuals in different subsurface domains, however the robustness of the tomographic inversion depends directly on the selected domain even more than the quality of the estimated perturbation.
Over recent years, many authors have proposed to compensate the absorption loss effects inside of the imaging process through the use of an attenuation model. This is more particularly necessary in the presence of strong attenuations anomalies. Q tomography has been developed for estimating this attenuation model but is generally limited to estimating attenuation in predefined anomalies. In this paper, we show how we managed to reveal automatically shallow gas pockets on the complex offshore Brunei dataset by using a high-resolution volumetric Q tomography. A key component of our approach is the estimation of effective attenuation in the pre-stack data domain through accurate picking of the frequency peak. Finally we used the Q-model to compensate for absorption in the imaging process.
In this paper we discuss a workflow to update low frequency models in time-lapse inversion studies. In this workflow we invert the base seismic survey and the difference between base and monitor survey in two separate inversion runs. The production effects are picked on the output of the difference inversion and this information is used to update the low frequency model in the time lapse sense. This approach is applied to time lapse seismic data from a heavy oil field where steam injection is being used for enhanced oil recovery. The inversion results are compared with other available information from the field and a good match can be observed.
This paper highlights compelling imaging improvements achieved through modern high-end reprocessing in Gippsland Basin. The area of study, largely represented by the Bass Canyon, has strong exploration potential but is high risk. The major challenges in this region are related to geologic complexity and a seismic imaging limitation, i.e.: a) extensive velocity anomalies leading to velocity uncertainties and false structural closures that increase drilling risk; b) strong noise interference and limited imaging clarity that affects AVO analysis. By integrating the modern techniques of 3D deghosting, full waveform inversion (FWI) and least-square Q pre-stack depth migration (LSQPSDM), the newly reprocessed data yields substantial added value over legacy datasets, resulting in an improved understanding of the subsurface geology and clearer prospect mapping. This reprocessing approach demonstrates that even in basins that are considered mature that new ideas and technology can change long-held perceptions and rejuvenate exploration interest.
The Santos basin is known to contain strong internal multiples that pose a major challenge for the imaging of pre-salt reservoirs. Artifacts generated by incorrectly imaged internal multiples can affect model building, interpretation, and ultimately contaminate amplitudes in the pre-salt reservoirs. We examine four different pre-salt fields from the Santos basin, present our prediction and subtraction strategy, and detail our observations and learnings for each one of the fields in the context of internal multiples.
We propose a post-migration 3D Q compensation process in the depth domain that is accurate for complex geological structures, accommodates complex Q models, and also provides flexibility in noise handling and spectral control that is critical to AVA recovery.