How to computationally include regional interpretations into the seismic imaging process

Rashidifard, Mahtab1,3, Giraud, Jérémie1,3, Ogarko, Vitaliy1,2, Lindsay, Mark1,3 and Jessell, Mark1,3

1Centre of Exploration Targeting (School of Earth Sciences), University of Western Australia, 35 Stirling Highway, Crawly, WA, 6009, Australia; 2International Centre for Radio Astronomy Research (ICRAR), University of Western Australia, 7 Fairway, Crawly, WA 6009, Australia; 3Mineral Exploration Cooperative Research Centre, School of Earth Sciences, University of Western Australia, 35 Stirling Highway, WA Crawley 6009, Australia

Understanding the regional evolution of the Earth and subsurface processes is a key for mineral exploration. Crucial to this understanding is accounting for geoscience knowledge obtained from
integrated interpretation of geological and geophysical data. Reflection seismic data, although sparsely distributed due to the high cost of acquisition, is the only data that gives a high resolution image of the crust to reveal deep subsurface structures and the architectural complexity that may vector attention to minerally prospective regions. Without an iterative depth migration and a depth conversion step, seismic images remain in time domain and are totally data-driven. However, for reconstructing the architecture and history of the area it is necessary to have these images in depth. To obtain the depth of seismic events, depth correlations need to be applied to them from other sources of information. The limitation here is that existing depth conversion methods rely on borehole information which is rarely available for deep crust studies.

We introduce a new methodology which allows inclusion of deep regional interpretations from potential field and geological sources of information in depth migration of seismic data. This fast algorithm aims at reducing the ambiguity in time-to-depth conversion and reduce the time spent on depth migration of seismic data by numerically including geologists’ interpretations.

A modelling-ray approach, not dependent on borehole information and accounting for lateral variations in velocity models, is used for switching from a time-migrated to depth-converted domain. An imagery approach is used for the reverse process to move from a depth-migrated to a time-converted domain. On the other hand, primary geological models are directly used in potential field inversion algorithms without re-parametrization of the model using an existing generalized level-set algorithm. Integrating solutions of the Eikonal equation in the form of Hamilton-Jacobi for both potential-field level-set inversion and seismic migration leads to a simultaneous modelling through which seismic, potential field, and geological data mitigate each other’s limitations. An investigation of the proposed methodology and a proof-of-concept using a fairly advanced realistic synthetic dataset are presented.

The proposed workflow is a novel approach for questioning the geological meaning of the sparsely distributed seismic sections and to integrate them in a 3D volume following the regional geological data and potential field results. The primary outcome of this study is a step toward adding equal weight to geological data not only as primary models but also as additional quantitative information within geophysical modelling and seismic imaging algorithms.

Our results lead to a significant improvement in the final model consistency with available sparsely distributed data sets. As a result, seismic migration is influenced by complementary information from potential field inversion results while simultaneously respecting sparse seismic sections in the 3D model obtained from regional interpretation and potential field inversion.

obtained from regional interpretation and potential field inversion. We acknowledge the support of the MinEx CRC and the Loop: Enabling Stochastic 3D Geological Modelling (LP170100985) consortia. The work has been supported by the Mineral Exploration Cooperative Research Centre whose activities are funded by the Australian Government’s Cooperative Research Centre Programme. This is MinEx CRC Document 2020/44.


I completed my undergraduate and masters in petroleum exploration engineering. I started my Ph.D. at UWA (CET) as a minexCRC student focusing on data fusion methodologies for integrated inversion of geological and geophysical data. This presentation is part of my PhD project for integrating seismic and gravity with different coverage.

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