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Up-down deconvolution remains a powerful tool for the processing of ocean-bottom node data through its ability to efficiently attenuate free-surface multiples along with the source ghost and signature. Practical receiver-domain implementations in the frequency-wavenumber domain, however, assume layer-cake geology and can leave residual multiples from dipping multiple generators. Using synthetic and real data examples, we examine the layer-cake limitations of receiver-domain up-down deconvolution and propose the use of a wave-equation deconvolution residual demultiple approach. In contrast to many multiple attenuation approaches, the proposed flow does not require any adaptive subtraction for either the up-down deconvolution or the wave-equation deconvolution demultiple steps.

The near surface in the Middle East is characterized by the presence of very shallow fast carbonates and anhydrites interleaved by slow-velocity clastic layers, resulting in sharp velocity inversions. We present here examples from two case studies in the Sultanate of Oman using Multi-Wave Inversion to retrieve the near-surface velocity model.

Over the past 35 years, geothermal projects have been developed in Upper Rhine Graben (URG) to exploit deep geothermal energy. Below a couple of kilometers of sediment, the deep target consists of granitic basement, highly fractured and hydro-thermally altered, having a high reservoir potential. In order to better understand large scale faulting and ensure viability of future geothermal projects, 3D seismic survey are acquired in the French part of the URG during summer 2018. This paper will present how the most recent seismic imaging sequence is designed in order to first process the acquired data and then build a depth velocity model allowing accurate positioning of the faulting.

The Humbly Grove field is a unique example of an onshore UK field with two co-existing revenue streams; seasonal gas storage and enhanced oil recovery. As with other gas storage facilities, Humbly Grove operates under strict safety legislation. The license to operate is dependent on a robust safety case. This was developed with an integrated approach to reservoir monitoring and modeling which combines a range of geoscience expertise to understand the behavior and safe limits for gas storage. CGG's involvement since 2012 has included reservoir modelling and flow simulation as the Operator's subsurface team. Safety monitoring, contracted to Durham University, involved ground and satellite based sensing and geomechanics.

While full waveform inversion (FWI) has imposed itself as a privileged velocity model building tool in areas investigated by diving waves, it is still penalized by its sensitivity to cycle skipping. Among the various strategies proposed to mitigate the problem, optimal transport (OT) FWI appears as one of the most successful industrial solutions. In order to illustrate this status we review a set of marine and land applications of multi-dimensional (in data space, not to be confused with the velocity model dimensionality) OT-FWI. Compared to classical FWI, we confirm a relaxed sensitivity to cycle skipping with in addition an update that goes deeper in the model (areas investigated by reflections) and an improved structural consistency.

The source-over-streamer configuration has been designed to improve pre-processing of the seismic data leading to high-resolution imaging. It also leads to new residual moveout information, unique in its high quality and density. By adding a front source to the original design, long offset information is now available for full waveform inversion velocity update. The combination the reflection information from the clean common imaged gather and the diving wave from the long offset allows a high-resolution anisotropic model to be obtained.

We have implemented 3D faults as discontinuity surfaces, of finite extent, in the RLM-3D inversion regularization, and used the scheme during both 3D cooperative and cross-gradient joint inversions of geothermal MT and gravity data, firstly for synthetic model, and then for the Sorik Marapi graben. Through integrated, quantitative modeling of multiple geophysical data types over geothermal fields, now including faults as sharp discontinuities, we facilitate geologically and structurally reliable multi-property 3D earth models that consistently explain the observations of all geophysical dataset.

Recent years have seen growing interest in improved shallow resolution images of the subsurface. This has led to ever more innovative acquisition approaches, each tailored to individual geological settings. We focus on a towed streamer acquisition in the Barents Sea which deployed five sources above the streamers for high definition imaging, along with a single source towed behind the streamer vessel to acquire long offset data for full waveform inversion. Firstly we demonstrate how accurate deblending is a key processing step to uncover the potential of these data.

Deep convolutional neural networks (DCNNs) are growing their popularity in seismic data processing due to their previous achievements in signal and image processing. In this paper, we explore the link between DCNN and seismic processing. We use two examples to demonstrate the potential of the application of DCNNs to seismic processing. More importantly, we discuss challenges and issues to solve before deploying DCNNs to production, and suggest some directions of study.