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This paper describes a successful reservoir characterization workflow where geostatistical inversion was first carried out to characterize caves and vugs, and then azimuthal inversion was used to obtain fractures strike and density. It improves the precision of reservoir prediction, and effectively characterizes the distribution of all kinds of reservoir including caves, vugs, fractures strike and density in the carbonate reservoirs. The predictions are well matched against the reservoir information from a newly drilled well.

We present a method to estimate and correct the phase of broadband seismic data in the low-frequency range using the tomography velocity model as an analogy for subsurface geology. The high-resolution velocity model is obtained from travel-time tomography and therefore has minimal influence from seismic amplitude and phase in the low-frequency range. We derive a phase-correction operator by matching between seismic data and zero-phase synthetics that are built based on a realization of reflectivity obtained from the tomographic inversion. We discuss the robustness of the method with synthetic data and show real data examples demonstrating improved well-tie and impedance inversion results.

In recent years there has been tremendous progress in the resolution and accuracy that can be obtained in seismic images. Several techniques are now available to achieve a high-definition final image. In the Cap-Boujdour dataset from offshore Morocco, the imaging is challenging due to a highly faulted geological setting and the presence of gas hydrates in the shallow overburden. The final image resolution beneath these absorptive bodies is poor if we do not compensate for the resulting attenuation. This case study illustrates how a combination of sophisticated velocity update technologies, such as full waveform inversion and the latest tomography developments, together with Q-prestack depth migration, can achieve high-resolution seismic imaging.

This study is concerned with testing the application of Automated Mineralogy (AM), specifically QEMSCAN, to identify and quantify microplastic particles within a solid heterogeneous specimen, as an initial assessment of how this technique may be utilised in microplastic research and environmental monitoring. It utilises a novel sample preparation method and makes significant alterations to standard QEMSCAN operating parameters to analyse model samples of known composition. This paper outlines initial results and highlights the key challenges in applying QEMSCAN to this area, suggesting potential solutions for future development of the technique.

A continuing concern regarding presalt carbonate reservoirs offshore Brazil is how to derive accurate quantitative estimates of reservoir properties. It is challenging to understand the link between the facies model and the variation in elastic properties, recover a reliable model of elastic properties from seismic, estimate porosities and permeabilities to use in reservoir simulations, and ultimately close the loop in integrated geology and engineering workflows. This case study describes our use of geostatistical inversion as a tool to unlock reservoir properties. We show how the integration of diverse information from various sources and at different scales is used to produce a meaningful range of probabilistic realizations of this Brazilian deepwater presalt reservoir.

Short-period multiple attenuation is often challenging as the multiple generators are typically not sufficiently well recorded as primary events for SRME to be successful. Model-based approaches have traditionally been used to circumvent this problem but may only model multiples generated by key events such as the waterbottom. Deconvolution-based alternatives offer the possibility to model multiples from more short-period multiple generators, but in practice many acquisition geometries are not well suited to higher-dimensional deconvolution implementations. We discuss a wave-equation deconvolution approach (WEDecon) which derives its prediction operator in the image domain. The image is then used to predict multiples which are subtracted from the data. We highlight the flexibility of WEDecon using data examples from towed-streamer, OBN and land geometries. The WEDecon approach has been successful at significantly reducing levels of residual multiple present in all these data types. We acknowledge, however, that short-period multiple attenuation is still a challenging topic and that further work is necessary in this area.

The absorption effect caused by the anelastic nature of earth leads to attenuation of amplitudes and distortion of phases for seismic wave. The so-called Q factor has to be compensated for correct imaging. We propose least square Q-Kirchhoff migration (LSQPSDM) in which absorption is incorporated into Kirchhoff modeling operator and Q compensation is achieved naturally via inversion with proper sparse constraints. With better illumination and Q compensation, fault imaging is naturally enhanced through the proposed least square Q-Kirchhoff migration. The proposed LSQPSDM approach has been applied to a synthetic data and a field dataset from NWS Australia. Better fault imaging and SNR are obtained comparing to conventional Q migration.

CGG has undertaken a multi-phase, multi-year data enhancement and acquisition project, commencing with a major basin-scale reprocessing initiative (ReGeneration) and culminating in the completion of a new 3D acquisition and imaging project, completed in 2021. The new survey has provided expanded data coverage from the inboard shallow water areas, throughout the Central Deep, and into the previously unexplored deepwater areas. Preliminary interpretation of the final data processed with CGG’s latest proprietary imaging technology has yielded a number of key insights which further enhance understanding of paleo-depositional environments and prospectivity of the deepwater areas. The new data is already unlocking previously unseen depositional elements, with strong implications for petroleum system understanding.

Seismic imaging in the Kwanza Basin has historically proven to be challenging owing to its complex geology and the presence of deep pre-salt targets. CGG has recently re-imaged its Kwanza Basin multi-client data portfolio to benefit from new insights made possible by advanced proprietary imaging techniques that have already been proven in other pre-salt basins. This newly re-processed data will enable interpreters to produce meaningful interpretations in a largely under-explored basin.