Computer-implemented method employing nonlinear direct prestack seismic inversion for poisson impedance

Abstract

A computer-implemented method, and system implementing the method, are disclosed for computing a final model of elastic properties, using nonlinear direct prestack seismic inversion for poisson impedance. User inputs and earth-model data is obtained over points of incidence of a survey region, at various angles of incidence. Various models are then computed that serve for lithology identification and fluid discrimination and take part in preliminary seismic exploration and reservoir characterization. Therefore, further refinement of these models is required due to changes in burial depths, compaction and overburden pressure, as they provide limitations for reservoirs on porous media. The further refinement using nonlinear direct prestack seismic model is performed on a system computer, which produces a final model of elastic properties. This model can then be applied for lithology prediction and fluid detection to identify potential targets of oil and gas exploration and estimating spots in unconventional shale gas applications.

Description

technical field [0001] The present disclosure relates generally to computer-implemented methods and systems for lithology identification and fluid identification in the fields of seismic exploration and reservoir characterization. Background technique [0002] 1. General remarks [0003] Those of ordinary skill in the art are aware that lithology identification and fluid identification play an important role in seismic exploration and reservoir characterization. The definition of lithology identification and fluid identification is estimated using the weighted stacking method of pre-stack seismic data, which was first proposed by Smith, G. and Gidlow, P. in their study "Weighted stacking for rock property estimation and detection of gas: Geophysical Prospecting (1987)". Later, Goodway, B., T.Chen and J.Downton presented "Improved AVO fluid detection and lithology discrimination using Lamépetrophysical parameters: "λρ", "μρ" & "λ / μfluid stack" at the 67th International Annu...

AI Technical Summary

Problems solved by technology

However, most AVO inversion methods are an ill-posed problem because some methods require appropriate smoothing or filtering techniques to make the solution unique and stable

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