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Towards a practical quantitative framework for repeated time-lapse seismic data interpretation

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Title: Towards a practical quantitative framework for repeated time-lapse seismic data interpretation
Authors: da Motta Pires, Paulo Roberto
Item Type: Thesis or dissertation
Abstract: Time-lapse seismic data, also referred to as 4D seismic, occupy a central position in reservoir management. This research pursues a practical, expedite framework to generate quantitative information even from noisy time-lapse seismic datasets, provided that they support consistent qualitative interpretations. The proposed method takes advantage of repeated time-lapse seismic data, which, however in a discrete fashion, can potentially capture the fluid flow dynamics in the reservoir. We reconstruct the continuous expansion of time-lapse seismic anomalies (visual delimitation of bright-spot regions) by performing the geometrical interpolation of their boundaries. Our method relies solely on the shapes of and on the extensions covered by these boundaries, minimising the importance of the magnitude of the time-lapse seismic signal. This interpolation employs the Fast-Marching Method and trajectory (pathline) tracing to estimate the anomaly boundary arrival times in the reservoir. Combined with the classic theory of immiscible displacement, these times generate quantitative information, namely water saturation maps, without resorting to rock-physics modelling or to time-consuming reservoir modelling workflows. Although we target real applications, we validate our method with a synthetic dataset, which realistically represents a waterflooded sandstone reservoir. The estimated water saturations reveal close agreement with their actual levels. These results render our method at least as accurate as well adjusted reservoir simulation models, though requiring significantly less data and only a fraction of the time spent in conventional history matching. We also discuss potential gains of our method if supported by additional reservoir information and if integrated to reservoir modelling routines.
Content Version: Open Access
Issue Date: Jan-2019
Date Awarded: Apr-2019
URI: http://hdl.handle.net/10044/1/73692
DOI: https://doi.org/10.25560/73692
Copyright Statement: Creative Commons Attribution NonCommercial NoDerivatives Licence
Supervisor: King, Peter
Sponsor/Funder: Petroleo Brasileiro, S.A.
Department: Earth Science & Engineering
Publisher: Imperial College London
Qualification Level: Doctoral
Qualification Name: Doctor of Philosophy (PhD)
Appears in Collections:Earth Science and Engineering PhD theses