Uncertainty reduction in joint inversion using geologically conditioned petrophysical constraints
: Giraud, Jérémie; University of Western Australia, Centre for Exploration
Targeting
Pakyuz-Charrier, Evren; University of Western Australia, Centre for
Exploration Targeting
Jessell, Mark; University of Western Australia, Centre for Exploration
Targeting
Lindsay, Mark; University of Western Australia, Centre for Exploration
Targeting
Martin, Roland; Observatoire Midi-Pyrenees
Ogarko, Vitaliy; University of Western Australia, Centre for Exploration
Targeting
ABSTRACT
14 We introduce a joint geophysical inversion workflow that aims to improve subsurface
15 imaging and decrease uncertainty by integrating petrophysical constraints and geological
16 data. In this framework, probabilistic geological modeling is used as a source of information
17 to condition the petrophysical constraints spatially and to derive starting models. The
18 workflow then utilizes petrophysical measurements to constrain the values retrieved by
19 geophysical joint inversion. The different sources of constraints are integrated into a least20
square framework to capture and integrate information related to geophysical, petrophysical
21 and geological data. This allows us to quantify the posterior state of knowledge and to
22 calculate posterior statistical indicators. To test this workflow, using geological field data we
23 have generated a set of geological models, which we used to derive a probabilistic geological
24 model. In this synthetic case study, we show that the integration of geological information
25 and petrophysical constraints in geophysical joint inver-sion can reduce uncertainty and
26 improve imaging. In particular, the use of petrophysical constraints retrieves sharper
27 boundaries and better reproduces the statistics of the observed petrophysical measurements.
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This paper presented here as accepted for publication in Geophysics prior to copyediting and composition.
© 2017 Society of Exploration Geophysicists.
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28 The integration of probabilistic geological modeling permits more accurate retrieval of model
29 geometry, and better constrains the solution while still satisfying the statistics derived from
30 geological data. The analysis of statistical indicators at each step of the workflow shows that
31 1) the inversion methodology is effective when applied to complex geology, and 2) the
32 integration of prior information and constraints from geology and petrophysics significantly
33 improves the inversion results while decreasing uncertainty. Lastly, the analysis of
34 uncertainty to the integration of the conditioned petrophysical constraints also shows that, for
35 this example, the best results are obtained for joint inversion using petrophysical constraints
36 spatially conditioned by geological modeling.
Отправлено: 25.02.18 05:02. Заголовок: Uncertainty reduction in joint inversion using geologically conditioned petrophysical constraints
