Future time-lapse broadband surveys should provide better reservoir monitoring resolution by extending the 4D signal bandwidth. In this paper, we will review the consequence of extending the signal bandwidth for the computation of 4D attributes, such as the repeatability measurement NRMS. The re-formulation of NRMS shows the sensitivity of the repeatability metric with regards to signal time-shift and signal bandwidth. Broadening the 4D signal bandwidth will result in an increase of the overall NRMS value for an equivalent seismic data with the same level on non-repeatable noise. To compare the quality of 4D seismic, regardless of bandwidth, we propose a new repeatability measure called CNRMS. The bandwidth Calibrated NRMS provides repeatability metric for any 4D seismic as it would be calculated with a reference signal bandwidth. In order to extend the 4D signal bandwidth without compromising the repeatability, we propose that upgoing pressure wavefields extracted from dual-sensor streamer are used for base and monitor surveys. It ensures the best possible broadband repeatability and highest 4D resolution.

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Velocity model building (VMB) is a time-consuming process involving several passes of migration and tomography. Martin and Bell (2019) proposed an automated stochastic approach that can accelerate the VMB turnaround. The method creates multiple random perturbations of the initial velocity model that are later inverted through tomography. The products of each individual perturbation are statistically combined and added to the starting model. This process is then repeated until a convergence criterion is met (flat gathers). In this abstract we will present an application of the Monte Carlo based VMB in the Campos Basin, Brazil. Additionally, we will demonstrate that the stochastic VMB produces velocity models, in accelerated turnaround, suitable for Full Waveform Inversion.

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