Sensitivity of constrained joint inversions to geological and petrophysical input data uncertainties with posterior geological analysis

Jeremie Giraud, Vitaliy Ogarko, Mark Lindsay, Evren Pakyuz-Charrier, Mark Jessell, Roland Martin

Research output: Contribution to journalArticle

Abstract

The integration of petrophysical data and probabilistic geological modelling in geophysical joint inversion is a powerful tool to solve exploration challenges. Models obtained from geologically and/or petrophysically constrained inversions are the result of complex interactions between correspondingly diverse data sets. Therefore, it is important to understand how non-geophysical input uncertainty impacts inverted models. In this paper, we propose to study the influence of uncertainty in geological and petrophysical measurements used to derive prior information and constraints onto geophysical inversion. Starting from geological field data from the Mansfield area (Victoria, Australia), we simulate low, medium and high uncertainty levels in geological measurements and petrophysical data, combined into a series of nine realistic case scenarios. This allows us to investigate the impact and propagation of uncertainty from non-geophysical measurements into geophysical inversion. We calculate misfit indicators and reconstruct lithological models a posteriori to analyse inversion results. We complement the examination of inverted models with topological analysis of lithological models in order to quantify the geological resemblance between the recovered and reference models. Our work reveals that the influence of uncertainty in geological measurements over the recovered lithological models is significantly stronger than it is for petrophysical data. Our posterior analysis indicates that intermediate petrophysical uncertainty provides optimum results.

Original languageEnglish
Pages (from-to)666-688
Number of pages23
JournalGeophysical Journal International
Volume218
Issue number1
DOIs
Publication statusPublished - Jul 2019

Cite this

@article{a8ec169a97f64799b90e5a7537e38bcd,
title = "Sensitivity of constrained joint inversions to geological and petrophysical input data uncertainties with posterior geological analysis",
abstract = "The integration of petrophysical data and probabilistic geological modelling in geophysical joint inversion is a powerful tool to solve exploration challenges. Models obtained from geologically and/or petrophysically constrained inversions are the result of complex interactions between correspondingly diverse data sets. Therefore, it is important to understand how non-geophysical input uncertainty impacts inverted models. In this paper, we propose to study the influence of uncertainty in geological and petrophysical measurements used to derive prior information and constraints onto geophysical inversion. Starting from geological field data from the Mansfield area (Victoria, Australia), we simulate low, medium and high uncertainty levels in geological measurements and petrophysical data, combined into a series of nine realistic case scenarios. This allows us to investigate the impact and propagation of uncertainty from non-geophysical measurements into geophysical inversion. We calculate misfit indicators and reconstruct lithological models a posteriori to analyse inversion results. We complement the examination of inverted models with topological analysis of lithological models in order to quantify the geological resemblance between the recovered and reference models. Our work reveals that the influence of uncertainty in geological measurements over the recovered lithological models is significantly stronger than it is for petrophysical data. Our posterior analysis indicates that intermediate petrophysical uncertainty provides optimum results.",
keywords = "Joint inversion, Persistence, memory, correlations, clustering, Statistical methods, TRAVEL-TIME TOMOGRAPHY, IMAGE-GUIDED INVERSION, GEOPHYSICAL-DATA, L-CURVE, ANISOTROPIC MEDIA, RESISTIVITY DATA, STRUCTURAL DATA, GRAVITY, MODELS, GRADIENT",
author = "Jeremie Giraud and Vitaliy Ogarko and Mark Lindsay and Evren Pakyuz-Charrier and Mark Jessell and Roland Martin",
year = "2019",
month = "7",
doi = "10.1093/gji/ggz152",
language = "English",
volume = "218",
pages = "666--688",
journal = "Geophysical Journal International",
issn = "0956-540X",
publisher = "Oxford University Press",
number = "1",

}

TY - JOUR

T1 - Sensitivity of constrained joint inversions to geological and petrophysical input data uncertainties with posterior geological analysis

AU - Giraud, Jeremie

AU - Ogarko, Vitaliy

AU - Lindsay, Mark

AU - Pakyuz-Charrier, Evren

AU - Jessell, Mark

AU - Martin, Roland

PY - 2019/7

Y1 - 2019/7

N2 - The integration of petrophysical data and probabilistic geological modelling in geophysical joint inversion is a powerful tool to solve exploration challenges. Models obtained from geologically and/or petrophysically constrained inversions are the result of complex interactions between correspondingly diverse data sets. Therefore, it is important to understand how non-geophysical input uncertainty impacts inverted models. In this paper, we propose to study the influence of uncertainty in geological and petrophysical measurements used to derive prior information and constraints onto geophysical inversion. Starting from geological field data from the Mansfield area (Victoria, Australia), we simulate low, medium and high uncertainty levels in geological measurements and petrophysical data, combined into a series of nine realistic case scenarios. This allows us to investigate the impact and propagation of uncertainty from non-geophysical measurements into geophysical inversion. We calculate misfit indicators and reconstruct lithological models a posteriori to analyse inversion results. We complement the examination of inverted models with topological analysis of lithological models in order to quantify the geological resemblance between the recovered and reference models. Our work reveals that the influence of uncertainty in geological measurements over the recovered lithological models is significantly stronger than it is for petrophysical data. Our posterior analysis indicates that intermediate petrophysical uncertainty provides optimum results.

AB - The integration of petrophysical data and probabilistic geological modelling in geophysical joint inversion is a powerful tool to solve exploration challenges. Models obtained from geologically and/or petrophysically constrained inversions are the result of complex interactions between correspondingly diverse data sets. Therefore, it is important to understand how non-geophysical input uncertainty impacts inverted models. In this paper, we propose to study the influence of uncertainty in geological and petrophysical measurements used to derive prior information and constraints onto geophysical inversion. Starting from geological field data from the Mansfield area (Victoria, Australia), we simulate low, medium and high uncertainty levels in geological measurements and petrophysical data, combined into a series of nine realistic case scenarios. This allows us to investigate the impact and propagation of uncertainty from non-geophysical measurements into geophysical inversion. We calculate misfit indicators and reconstruct lithological models a posteriori to analyse inversion results. We complement the examination of inverted models with topological analysis of lithological models in order to quantify the geological resemblance between the recovered and reference models. Our work reveals that the influence of uncertainty in geological measurements over the recovered lithological models is significantly stronger than it is for petrophysical data. Our posterior analysis indicates that intermediate petrophysical uncertainty provides optimum results.

KW - Joint inversion

KW - Persistence

KW - memory

KW - correlations

KW - clustering

KW - Statistical methods

KW - TRAVEL-TIME TOMOGRAPHY

KW - IMAGE-GUIDED INVERSION

KW - GEOPHYSICAL-DATA

KW - L-CURVE

KW - ANISOTROPIC MEDIA

KW - RESISTIVITY DATA

KW - STRUCTURAL DATA

KW - GRAVITY

KW - MODELS

KW - GRADIENT

U2 - 10.1093/gji/ggz152

DO - 10.1093/gji/ggz152

M3 - Article

VL - 218

SP - 666

EP - 688

JO - Geophysical Journal International

JF - Geophysical Journal International

SN - 0956-540X

IS - 1

ER -