Honouring Prior Geological Information in Waveequation Based AVO Inversion

Dries Gisolf; Siddharth Sharma; Stefan Luthi

doi:10.3997/2214-4609.201700220

Honouring Prior Geological Information in Waveequation Based AVO Inversion

Dries Gisolf, Siddharth Sharma, Stefan Luthi

Applied Geology

Research output: Chapter in Book/Conference proceedings/Edited volume › Conference contribution › Scientific

Abstract

A method is presented to link prior geological information, from wells and interpretation, to full waveform inversion at reservoir scale. The method converts the layer-based prior information to grid-based property probability density distributions that are highly non-Gaussian and is based on Bayes' Rule. The likelihood function for the unconstrained inversion is based on the Hessian of the inversion kernel and the minimum residual energy in the objective function. Good results have been obtained from a synthetic case study based on a very realistic outcrop model (Book Cliffs,Utah). Also results from a real data case study will be shown.

Original language	English
Title of host publication	4th EAGE Exploration Workshop 2017
Subtitle of host publication	2-4 May 2017, Muscat, Oman
Number of pages	5
DOIs	https://doi.org/10.3997/2214-4609.201700220
Publication status	Published - 2017
Event	4th EAGE Exploration Workshop 2017 - Muscat, Oman Duration: 2 May 2017 → 4 May 2017 Conference number: 4 https://events.eage.org/en/2017/fourth-eage-exploration-workshop

Workshop

Workshop	4th EAGE Exploration Workshop 2017
Country/Territory	Oman
City	Muscat
Period	2/05/17 → 4/05/17
Internet address	https://events.eage.org/en/2017/fourth-eage-exploration-workshop

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10.3997/2214-4609.201700220

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@inproceedings{a426226919234f59914dd77c75bc27c4,

title = "Honouring Prior Geological Information in Waveequation Based AVO Inversion",

abstract = "A method is presented to link prior geological information, from wells and interpretation, to full waveform inversion at reservoir scale. The method converts the layer-based prior information to grid-based property probability density distributions that are highly non-Gaussian and is based on Bayes' Rule. The likelihood function for the unconstrained inversion is based on the Hessian of the inversion kernel and the minimum residual energy in the objective function. Good results have been obtained from a synthetic case study based on a very realistic outcrop model (Book Cliffs,Utah). Also results from a real data case study will be shown. ",

author = "Dries Gisolf and Siddharth Sharma and Stefan Luthi",

year = "2017",

doi = "10.3997/2214-4609.201700220",

language = "English",

booktitle = "4th EAGE Exploration Workshop 2017",

note = "4th EAGE Exploration Workshop 2017 ; Conference date: 02-05-2017 Through 04-05-2017",

url = "https://events.eage.org/en/2017/fourth-eage-exploration-workshop",

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TY - GEN

T1 - Honouring Prior Geological Information in Waveequation Based AVO Inversion

AU - Gisolf, Dries

AU - Sharma, Siddharth

AU - Luthi, Stefan

N1 - Conference code: 4

PY - 2017

Y1 - 2017

N2 - A method is presented to link prior geological information, from wells and interpretation, to full waveform inversion at reservoir scale. The method converts the layer-based prior information to grid-based property probability density distributions that are highly non-Gaussian and is based on Bayes' Rule. The likelihood function for the unconstrained inversion is based on the Hessian of the inversion kernel and the minimum residual energy in the objective function. Good results have been obtained from a synthetic case study based on a very realistic outcrop model (Book Cliffs,Utah). Also results from a real data case study will be shown.

AB - A method is presented to link prior geological information, from wells and interpretation, to full waveform inversion at reservoir scale. The method converts the layer-based prior information to grid-based property probability density distributions that are highly non-Gaussian and is based on Bayes' Rule. The likelihood function for the unconstrained inversion is based on the Hessian of the inversion kernel and the minimum residual energy in the objective function. Good results have been obtained from a synthetic case study based on a very realistic outcrop model (Book Cliffs,Utah). Also results from a real data case study will be shown.

U2 - 10.3997/2214-4609.201700220

DO - 10.3997/2214-4609.201700220

M3 - Conference contribution

BT - 4th EAGE Exploration Workshop 2017

T2 - 4th EAGE Exploration Workshop 2017

Y2 - 2 May 2017 through 4 May 2017

ER -

Honouring Prior Geological Information in Waveequation Based AVO Inversion

Abstract

Workshop

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