Technical Content

Machine learning (ML) has garnered great attention within the field of seismic processing due to its vast achievements for quality and efficiency in the area of computer vision. Recent academic papers have demonstrated some potential for the use of machine learning in processing seismic ...

Time-lapse (4D) seismic surveys are devised to detect subsurface changes resulting from hydrocarbon production and fluid injection. Full-waveform inversion (FWI) of time-lapse seismic data has been reported to provide high-resolution estimates of 4D changes. However, successful applications of 4D FWI on field data have ...

The western part of the Gulf of Mexico (WGOM) is often characterized by large and complex salt and shale bodies, making it notoriously challenging to image deep subsalt targets, especially with only wide-azimuth towed-streamer (WATS) data available. In 2018, BHP acquired a large-scale sparse ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...