Master the Uncertainty with Bayesian Approach - Case Study, Multi-Azimuth Depth Imaging Deep Water, Offshore Brazil

Interpretation in the depth domain is controversial. Sometimes, the problem comes with constantly changing models. Geologists have found that structures which have been focused come and go along with the model update. One of these tough imaging challenges occurs when a carbonate feature lies above a salt feature. Overcoming this carbonate feature is a good challenge to exploration today due to the high variation in velocity and the homogeneity of anisotropic character. Most of the current depth imaging processes faces uncertainty with an arbitrary  and  variables. This judgement of adequate volume and pattern of distribution remain controversial. With limited well information in the area, the depth model from the same seismic data could be non-unique. In consequence this uncertainty of the structure causes problems in deep water exploration. Repsol intelligently designed its proprietary multi-Azimuth acquisition in Campos basin, Offset Brazil. By using an advanced imaging study combining technologies of advanced grid based tomography and inversion tools with structure control and multi-discipline joint inversion processes, we achieved the goal of the imaging the structure with outstanding resolutions. The imaging results are confirmed by the latest well marker and the accuracy of production structure both approach the limit of resolution by inversion theory. This project sets an outstanding benchmark for computing resource utilization and demonstrates the benefit of advanced migration technologies and well-planned acquisition patterns.