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 language | English |
|---|---|
| Pages (from-to) | 666-688 |
| Number of pages | 23 |
| Journal | Geophysical Journal International |
| Volume | 218 |
| Issue number | 1 |
| DOIs | |
| Publication status | Published - Jul 2019 |
Cite this
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Sensitivity of constrained joint inversions to geological and petrophysical input data uncertainties with posterior geological analysis. / Giraud, Jeremie; Ogarko, Vitaliy; Lindsay, Mark; Pakyuz-Charrier, Evren; Jessell, Mark; Martin, Roland.
In: Geophysical Journal International, Vol. 218, No. 1, 07.2019, p. 666-688.Research output: Contribution to journal › Article
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 -