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A Multi-Disciplinary Workflow to Achieve the Largest, Seamless, High-Quality Presalt Image in Santos Basin, Brazil


The Industry’s largest, seamless, high-quality Reverse Time Migration (RTM) seismic image over a

massive 34000 sq. km of Santos Basin, Brazil, has been produced by applying advanced imaging

techniques on various vintages of data. With the ever-shrinking turnaround time requirements for

seismic processing, having an effective cross-disciplinary cooperation is necessary to efficiently and

accurately image these large datasets. Understanding the response of a seismic image to velocity or

geological models, or imaging algorithms is critical for imaging the reservoir targets accurately.

Furthermore, minimizing the uncertainty associated with the resulting image is a prerequisite.

Additional challenges involved with the processing of large datasets are the High Performance

Computing (HPC) and Quality Control (QC) requirements. To ensure production of quality images in a

timely manner, real time analytics are needed to manage HPC throughput, disk utilization, and QC of

seismic images. This results in the need for workflows across multi-disciplinary teams efficiently

contributing to and creating the required seismic images. The use of such a workflow on a large seismic

dataset over the Santos Basin is outlined here.

Reservoir targets in the Santos Basin are mainly localized in presalt carbonate build-ups underneath the

Layered Evaporite Sequences (LES). A geological understanding of LES complexity and the differing

character of the post-salt carbonates layers, along with available well data, must be incorporated into

the geophysical velocity model building flow to produce a clear presalt image with a consistent reservoir

geometry. The decision-making process benefits from efficiently analyzing a large number of volumetric

datasets, generated for QC and constrained by geological and geophysical metrics. The goal throughout

the workflow was to use all available tools in a manner that promotes efficiency, improves quality and

reduces turnaround time. For example, to reduce the time required for an enormous amount of Base of

Salt (BOS) interpretation, a workflow using Full Waveform Inversion (FWI) was developed for a data-

driven, computer-based approach to salt velocity model building. The result of this multi-disciplinary

approach is evident in a very large-scale seismic dataset with enhanced presalt imaging, which can be

used for reservoir architecture analysis and exploration risks mitigation.