Integration of geoscientific uncertainty into geophysical inversion by means of local gradient regularization

Abstract

Abstract. We introduce a workflow integrating geological modelling uncertainty information to constrain gravity inversions. We test and apply this approach to the Yerrida Basin (Western Australia), where we focus on prospective greenstone belts beneath sedimentary cover. Geological uncertainty information is extracted from the results of a probabilistic geological modelling process using geological field data and their inferred accuracy as inputs. The uncertainty information is utilized to locally adjust the weights of a minimum-structure gradient-based regularization function constraining geophysical inversion. Our results demonstrate that this technique allows geophysical inversion to update the model preferentially in geologically less certain areas. It also indicates that inverted models are consistent with both the probabilistic geological model and geophysical data of the area, reducing interpretation uncertainty. The interpretation of inverted models reveals that the recovered greenstone belts may be shallower and thinner than previously thought.

Towards plausible lithological classification from geophysical inversion: honouring geological principles in subsurface imaging

“…This inversion platform enables the use of a series of constraints as detailed in Martin et al (2018), Giraud et al (2019a, b). Constraints are enforced through a minimum-structure gradient regularization approach where weights vary locally accordingly with geological uncertainty (Giraud et al, 2019a). The cost function to minimize is given as…”

“…The values in diagonal matrix W s are determined from prior information. In the presented work, W s is obtained from geological modelling results and is a proxy for geological uncertainty The matrix W s is calculated following Giraud et al (2019a), who use the probabilistic geological modelling approach described in Pakyuz-Charrier et al (2018b, c, 2019. In the case of gravity inversion as presented here, the complete Bouguer anomaly of density contrast model m is calculated as the product of the Jacobian matrix G with model m. Therefore, we have g (m) = Gm.…”

“…It can be used to constrain inversion in a structural sense when integrated in W s as per Eq. (1) (Giraud et al, 2019a).…”

“…More detailed information about the usage of MCUE results in geophysical inversion can be found in Giraud et al (2017Giraud et al ( , 2019a.…”

“…Secondly, our aim is to complement inversion workflows by providing a general, automated method to derive a non-deterministic lithological interpretation of inversion results. Thirdly, we propose a real-world application based on a case study in the Yerrida Basin (Western Australia), where we build upon recent work by Giraud et al (2019a) and Lindsay et al (2018), who performed the geophysical inversion and geological modelling of data collected in the area, respectively.…”