1887

Abstract

Summary

Pre-stack impedance inversion generally yields reliable P-impedance and S-impedance volumes. However, other volumes such as density, porosity and brittleness can also be extremely useful in characterizing a reservoir. The density volume output from pre-stack inversion can be improved with regards to the vertical resolution of the reservoir through multi-attribute transform and probabilistic neural network analysis. A porosity volume can be output from the P-impedance volume by applying a mathematical transformation of a linear relationship derived from well-log data (P-impedance and porosity curves). Similarly, a brittleness attribute can be derived by using a mathematical transform on the P- and S-impedance volumes. Once all these volumes are derived, it is important to suitably visualize the data so as to understand the reservoir better such that appropriate drilling targets can be selected. Some of the commonly used visualization techniques are 3D displays such as time or strata slices, but we try and perform reservoir visualization by producing geobodies for the sandstone in our broad zone of interest.

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/content/papers/10.3997/2214-4609.201801284
2018-06-11
2024-03-29
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References

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