In mineral exploration, increased interest towards deeper mineralizations makes seismic methods attractive. One of the critical steps in seismic processing workflows is the static correction, which is applied to correct the effect of the shallow, highly heterogeneous subsurface layers, and improve the imaging of deeper targets. We showed an effective approach to estimate the statics, based on the analysis of surface waves (groundroll) contained in the seismic reflection data, and we applied it to a legacy seismic line acquired at the iron-oxide mining site of Ludvika in Sweden. We applied surface-wave methods that were originally developed for hydrocarbon exploration, modified as a step-by-step workflow to suit the different geologic context of hardrock sites. The workflow starts with the detection of sharp lateral variations in the subsurface, the existence of which is common at hard-rock sites. Their location is subsequently used, to ensure that the dispersion curves extracted from the data are not affected by strong lateral variations of the subsurface properties. The dispersion curves are picked automatically, windowing the data and applying a wavefield transform. A pseudo-2D time-average S-wave velocity and time-average P-wave velocity profile are obtained directly from the dispersion curves, after inverting only a reference curve. The time-average P-wave velocity profile is then used for the direct estimation of the one-way traveltime, which provides the static corrections. The resulting P-wave statics from the field data were compared with statics computed through conventional P-wave tomography. Their difference was mostly negligible with more than 91% of the estimations being in agreement with the conventional statics, proving the effectiveness of the proposed workflow. The application of the statics obtained from surface waves provided a stacked section comparable with that obtained by applying tomostatics.

Surface-wave analysis for static corrections in mineral exploration: A case study from central Sweden

Da Col F.;
2020-01-01

Abstract

In mineral exploration, increased interest towards deeper mineralizations makes seismic methods attractive. One of the critical steps in seismic processing workflows is the static correction, which is applied to correct the effect of the shallow, highly heterogeneous subsurface layers, and improve the imaging of deeper targets. We showed an effective approach to estimate the statics, based on the analysis of surface waves (groundroll) contained in the seismic reflection data, and we applied it to a legacy seismic line acquired at the iron-oxide mining site of Ludvika in Sweden. We applied surface-wave methods that were originally developed for hydrocarbon exploration, modified as a step-by-step workflow to suit the different geologic context of hardrock sites. The workflow starts with the detection of sharp lateral variations in the subsurface, the existence of which is common at hard-rock sites. Their location is subsequently used, to ensure that the dispersion curves extracted from the data are not affected by strong lateral variations of the subsurface properties. The dispersion curves are picked automatically, windowing the data and applying a wavefield transform. A pseudo-2D time-average S-wave velocity and time-average P-wave velocity profile are obtained directly from the dispersion curves, after inverting only a reference curve. The time-average P-wave velocity profile is then used for the direct estimation of the one-way traveltime, which provides the static corrections. The resulting P-wave statics from the field data were compared with statics computed through conventional P-wave tomography. Their difference was mostly negligible with more than 91% of the estimations being in agreement with the conventional statics, proving the effectiveness of the proposed workflow. The application of the statics obtained from surface waves provided a stacked section comparable with that obtained by applying tomostatics.
2020
Mining; Statics; Surface waves
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14083/260
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