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7th Middle East Geosciences Conference and Exhibition
Manama, Bahrain
March 27-29, 2006
1 ENI E&P Division, San
Donato Milanese, 20097, Italy, phone: +39 0252063247, fax: +39 02 520 63891, [email protected]
2 ENI Oil Co.Ltd. Libyan Branch, Dahra Building, Tripoli, Libya
Objectives. 3D ZO Common-Reflection-Surface stack data can improve the structural image and optimize the
amplitude/phase control for quantitative seismic
reservoir characterization, even starting from a low S/N dataset. This data -
driven imaging method has been proven to accurately characterise events in the pre-stack domain. It takes advantage of
data redundancy, using an 8-parameters stacking surface instead of single stacking trajectory (velocity). Fold is dramatically
boosted, since traces lying in the projected Fresnel zone are used; therefore calculation robustness and reliability increase.
Additional information are also recovered, i.e. very detailed NMO velocities, geometrical spreading, projected Fresnel
zones.
Discussion. Processed log data from five wells were integrated to 100sqkm-sized seismic
dataset. Starting from
Petroacoustic approach, a
Seismic
-Lithology characterization of a giant oil field was achieved. High impedance sandstone
and soft sealing shale defines the reservoir sequence. Internal
seismic
response is semi -transparent, while sealing/reservoir
interface waveform varies according to both reservoir porosity and sealing shale type (dual nature). Initial analyses
ascertained the reliability of CRS data, the appropriate high S/N and its zero-phase condition. Model-based
seismic
inversion was used to solve the reflectivity ambiguity, estimating physical rock property cubes, and virtually increase the
resolution by removing the wavelet signature from CRS data. Results validation implied the inversion error estimate, also
performing “blind tests” on additional wells. Results encouraged to proceed towards an Acoustic Impedance calibration to
Effective Porosity. Neural-Network multi-
attribute
and Linear calibration of Acoustic Impedance transformed
seismic
into
Porosity volumes. Prediction accuracy ranges from 2-4 PU, upon the used technique.
Conclusions. 3D-CRS significantly increases the S/N and amplitude/phase consistency when compared to conventional
data; therefore it's a suitable input for reliable quantitative seismic
and reservoir characterization.