--> ABSTRACT: A Case Study on Using Seismic Inversion, 90 Degree Phase Shifted Seismic Data and Geostatistical Simulation in the Bayu-Undan Field, by Joseph Gallagher, M. J. Raymondi, and D. Mayo; #90913(2000).
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ABSTRACT: A case study on using Previous HitseismicNext Hit inversion, 90 degree Previous HitphaseNext Hit shifted Previous HitseismicNext Hit data and geostatistical simulation in the Bayu-Undan Field

Gallagher, Joseph, M. J. Raymondi, and D. Mayo , Phillips Petroleum Co, Bartlesville, OK

A measure of the impedance variation can be obtained from the negative first derivative of the Previous HitseismicNext Hit trace or by applying to the zero Previous HitphaseNext Hit Previous HitseismicNext Hit section, a Previous HitphaseNext Hit shift of -90 degrees. In this paper, it is shown that this process can provide a quantitative measure of the high and low values of impedance along a Previous HitseismicNext Hit trace. Peaks on Previous HitseismicNext Hit trace processed in this way can be associated with intervals of increases in impedance while toughs on the trace can be associated with intervals of decreases in impedance. Previous HitSeismicNext Hit sections processed in this manner are compared to a sparse spike geostatistical-based inversion performed on the 3-D Previous HitseismicNext Hit data acquired over the Bayu-Undan field in the Timor Sea. The inversion encompassed the entire reservoir interval. Sonic and density logs from seven wells were used to geostatistically build a low frequency impedance model and an amplitude balance model. These models were applied to the sparse spike inversion in the frequency domain to generate absolute impedances for the inverted Previous HitseismicNext Hit traces. From the impedance and -90 Previous HitphaseNext Hit shifted Previous HitseismicNext Hit section and using gamma ray log calibration, it is shown that peaks in the Previous HitseismicTop trace are associated with higher impedance values and shale intervals while troughs are associated with lower impedance and sand intervals. The estimation of porosity in the sands using impedance/porosity correlation as soft data in a geostatistical simulation are also discussed.

AAPG Search and Discovery Article #90913©2000 AAPG International Conference and Exhibition, Bali, Indonesia