Solid Earth (Jun 2022)

3D high-resolution seismic imaging of the iron oxide deposits in Ludvika (Sweden) using full-waveform inversion and reverse time migration

  • B. Singh,
  • M. Malinowski,
  • M. Malinowski,
  • A. Górszczyk,
  • A. Górszczyk,
  • A. Malehmir,
  • S. Buske,
  • Ł. Sito,
  • P. Marsden

DOI
https://doi.org/10.5194/se-13-1065-2022
Journal volume & issue
Vol. 13
pp. 1065 – 1085

Abstract

Read online

A sparse 3D seismic survey was acquired over the Blötberget iron oxide deposits of the Ludvika Mines in south-central Sweden. The main aim of the survey was to delineate the deeper extension of the mineralisation and to better understand its 3D nature and associated fault systems for mine planning purposes. To obtain a high-quality seismic image in depth, we applied time-domain 3D acoustic full-waveform inversion (FWI) to build a high-resolution P-wave velocity model. This model was subsequently used for pre-stack depth imaging with reverse time migration (RTM) to produce the complementary reflectivity section. We developed a data preprocessing workflow and inversion strategy for the successful implementation of FWI in the hardrock environment. We obtained a high-fidelity velocity model using FWI and assessed its robustness. We extensively tested and optimised the parameters associated with the RTM method for subsequent depth imaging using different velocity models: a constant velocity model, a model built using first-arrival travel-time tomography and a velocity model derived by FWI. We compare our RTM results with a priori data available in the area. We conclude that, from all tested velocity models, the FWI velocity model in combination with the subsequent RTM step provided the most focussed image of the mineralisation and we successfully mapped its 3D geometrical nature. In particular, a major reflector interpreted as a cross-cutting fault, which is restricting the deeper extension of the mineralisation with depth, and several other fault structures which were earlier not imaged were also delineated. We believe that a thorough analysis of the depth images derived with the combined FWI–RTM approach that we present here can provide more details which will help with better estimation of areas with high mineralisation, better mine planning and safety measures.