Since Kragh and Christie's 2002 seminal paper on repeatability, nrms and predictability (PRED) have been the most widely used metrics for analyzing 4D noise in time-lapse studies. However, their values and behavior are rather counterintuitive, and they invariably end up stagnating above 15% and 0.95, respectively, in repeated marine data of variable quality. Moreover, their respective variations with regards to measurable differences in data, acquisition, and processing are still poorly understood from a quantitative standpoint. With the objective of improving our assessment, interpretation, and understanding of time-lapse repeatability, this paper introduces an analytical formulation of the 4D problem from the perspective of perturbation theory, building on the preliminary works of Calvert and high-quality data from our latest time-lapse campaigns in Gulf of Guinea. This framework brings to light blatant problems with our current repeatability metrics, and proposes a complementary set of QCs and best practices to get more out of 4D data. The cornerstone of this effort is the introduction of the new signal-to-distortion ratio (SDR) attribute as a true, reliable indicator of time-lapse repeatability. It provides the essential common ground on which different acquisition technologies, deployment and processing strategies are to be compared.

You do not have access to this content, please speak to your institutional administrator if you feel you should have access.