Technical Content

Illustration of how machine learning application is used for Seismic global QC and detailled clusterization of data for tailored processing. Data reduction with deep neural network shows great efficiency to limit memory issue.

Reprocessing of available seismic dataset using high-end processing technology was seen to be the most economical solution for search of deeper, pre-carbonate targets in a marginal field. The vintage data suffered from amplitude loss due to absorption by gas bodies and carbonate layers causing ...

We illustrate a new case study based on our land FWI workflow. We also demonstrate the impact of optimal transport (OT) FWI on the resulting velocity model, which aims to mitigate cycle skipping. We demonstrate how it corrects several localized failures with conventional FWI ...

Placing marine sources on the top of the seismic streamer spread improves resolution and reservoir inversion in shallow and intermediate depth targets. This is due to the abundance of near offset data and high level of illumination compared to conventional marine seismic. A drawback ...

Shallow stratigraphy in Southern Oman is characterized by the presence of a shallow anhydrite layer causing a strong velocity inversion which makes seismic imaging particularly tedious. This known shallow sharp velocity inversion cannot be easily captured with reflected waves based techniques or even acoustic ...

TopSeis unique setting creates both new benefits and challenges for processing and imaging which, once solved, offer an ideal high resolution picture of the underground. This paper define faced challenges and how processing needs to be optimized in order to obtain brand new geological ...

We discuss the survey planning and provide results from a marine acquisition conducted northwest of the Shetland Islands. The survey was designed to image multiple targets from shallow Tertiary and Cretaceous plays, through to complex fractured Devono-Carboniferous reservoirs. Marine acquisitions are typically conducted along ...

Gas absorption causes anelastic effects (described by the quality factor Q) and is a well-known source of amplitude loss and phase distortion in seismic data. Advances in our full waveform inversion technology mean it is now possible to compensate for phase distortion and amplitude ...

Seismic data must be optimally processed for accurate reservoir characterization, and therefore each step of the processing sequence should be carefully designed and assessed for AVA compliance and primary preservation. In this paper, we focus on the demultiple, a critical step as it can ...