Integrated Seismic Reservoir Characterization for Appraisal and Field Development Planning
R. Bastidas, Juan-Mauricio Florez, J.P. Blangy, E. Genova
Abstract
R. Bastidas, Juan-Mauricio Florez, J.P. Blangy, E. Genova
Abstract
Summary The use of seismic data for reservoir characterization faces important challenges related to its limited vertical resolution, its band-limited nature, and the uncertainties associated with the non-uniqueness of seismic interpretation. This paper documents a practical methodology and shows results from a case study from a field in the Perdido Foldbelt, GoM. The methodology starts from detailed facies analysis of core data, image and wireline logs, and links this facies analysis to the prediction of facies and petrophysical properties using seismic properties via a heuristic rock physics approach coupled with pre-stack seismic inversion. This quantitative seismic reservoir characterization method integrates and honours key inputs from wells and seismic data, as well as sedimentary geology. The method combines the high vertical resolution of log data with the dense spatial sampling of seismic data, to obtain the best possible representation of subsurface distribution of rock properties.
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Summary The use of seismic data for reservoir characterization faces important challenges related to its limited vertical resolution, its band-limited nature, and the uncertainties associated with the non-uniqueness of seismic interpretation. This paper documents a practical methodology and shows results from a case study from a field in the Perdido Foldbelt, GoM. The methodology starts from detailed facies analysis of core data, image and wireline logs, and links this facies analysis to the prediction of facies and petrophysical properties using seismic properties via a heuristic rock physics approach coupled with pre-stack seismic inversion. This quantitative seismic reservoir characterization method integrates and honours key inputs from wells and seismic data, as well as sedimentary geology. The method combines the high vertical resolution of log data with the dense spatial sampling of seismic data, to obtain the best possible representation of subsurface distribution of rock properties.
Key concepts: Geology, Seismic inversion, Reservoir modeling, Seismic to simulation, Petrophysics, Facies, Inversion (geology), Economic geology