High-resolution reservoir characterization by 2-D model-driven seismic Bayesian inversion

An example from a Tertiary deltaic clinoform system in the North Sea

Conference paper (2008)

Authors

D. Tetyukhina Applied Geophysics and Petrophysics - CEG
S.M. Luthi Applied Geology - CEG
L.J. van Vliet Applied Sciences, ImPhys/Quantitative Imaging
C.P.A. Wapenaar , Applied Geophysics and Petrophysics - CEG
Research Group
Applied Geophysics and Petrophysics (CEG) (TU Delft)
Algorithm 2D Inversion Resolution Reservoir characterization
More Info
expand_more

Published Date

2008

Language

English

Reuse Rights

Other than for strictly personal use, it is not permitted to download, forward or distribute the text or part of it, without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license such as Creative Commons.

Faculty

Civil Engineering & Geosciences

Department

Geoscience and Engineering

Research Group

Applied Geophysics and Petrophysics

Abstract

In order to retrieve a high-resolution reservoir model from seismic and well data, an approach was developed based on an a priori layered model from well data, specifically the acoustic impedances derived from the sonic and density logs. The procedure consists of using a forward model of the well data as a priori information that is then iteratively matched with the seismic data using a Bayesian inversion process. The inversion is then extended to 2D, whereby the extrapolation is guided by a simple geometric envelope described with a small number of parameters. It is tested on a seismic data set containing a deltaic clinoform in the North Sea, whereby the clinoform geometry is parameterized by a sigmoid and used as prior information. In the subsequent optimization the clinoform geometry is further refined with a limited number of local knots to improve the match with the seismic data. This low-parameterization inversion approach thus uses geological shapes and well constraints to obtain a subsurface model than can have a substantially higher resolution than the seismic wavelength.