Abstract

Abstract. Galvanic distortions of magnetotelluric (MT) data, such as the static-shift effect, are a known problem that can lead to incorrect estimation of resistivities and erroneous modelling of geometries with resulting misinterpretation of subsurface electrical resistivity structure. A wide variety of approaches have been proposed to account for these galvanic distortions, some depending on the target area, with varying degrees of success. The natural laboratory for our study is a hydraulically permeable volume of conductive sediment at depth, the internal resistivity structure of which can be used to estimate reservoir viability for geothermal purposes; however, static-shift correction is required in order to ensure robust and precise modelling accuracy.We present here a possible method to employ frequency–domain electromagnetic data in order to correct static-shift effects, illustrated by a case study from Northern Ireland. In our survey area, airborne frequency domain electromagnetic (FDEM) data are regionally available with high spatial density. The spatial distributions of the derived static-shift corrections are analysed and applied to the uncorrected MT data prior to inversion. Two comparative inversion models are derived, one with and one without static-shift corrections, with instructive results. As expected from the one-dimensional analogy of static-shift correction, at shallow model depths, where the structure is controlled by a single local MT site, the correction of static-shift effects leads to vertical scaling of resistivity–thickness products in the model, with the corrected model showing improved correlation to existing borehole wireline resistivity data. In turn, as these vertical scalings are effectively independent of adjacent sites, lateral resistivity distributions are also affected, with up to half a decade of resistivity variation between the models estimated at depths down to 2000 m. Simple estimation of differences in bulk porosity, derived using Archie's Law, between the two models reinforces our conclusion that the suborder of magnitude resistivity contrasts induced by the correction of static shifts correspond to similar contrasts in estimated porosities, and hence, for purposes of reservoir investigation or similar cases requiring accurate absolute resistivity estimates, galvanic distortion correction, especially static-shift correction, is essential.

Highlights

  • The electrical resistivity of a volume of rock is highly sensitive to the presence of laterally and vertically varying amounts of electrically conductive fluids connected via pore spaces or fluid conduits

  • The upper portion of normal resistivity data covers the uppermost 250 m of the hole, including the Antrim Lava Group, Ulster White Limestone Formation, and the upper portion of the Lower Lias Group. These data provide relatively consistent resistivity estimates of ≈ 80 and ≈ 5 m for the UWLF and LLG sedimentary formations respectively, whereas estimates for the ALG vary from ≈ 5–80 m as it comprises a succession of tuffs and basalts

  • An approach for the correction of static-shift-type galvanic distortion in MT data utilising airborne frequency domain electromagnetic (FDEM) data has been tested that follows the use of time domain electromagnetic (TDEM) data in previous methods

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Summary

Introduction

The electrical resistivity of a volume of rock is highly sensitive to the presence of laterally and vertically varying amounts of electrically conductive fluids connected via pore spaces or fluid conduits. Drilling in the adjacent Magilligan Basin encountered Carboniferous formations at 1347 m total depth, the most basal formations confirmed within the Rathlin Basin are the Permian Enler Group (EG) sandstones and Early-Triassic Sherwood Sandstone Group sandstones (SSG). The upper portion of normal resistivity data covers the uppermost 250 m of the hole, including the Antrim Lava Group, Ulster White Limestone Formation, and the upper portion of the Lower Lias Group These data provide relatively consistent resistivity estimates of ≈ 80 and ≈ 5 m for the UWLF and LLG sedimentary formations respectively, whereas estimates for the ALG vary from ≈ 5–80 m as it comprises a succession of tuffs and basalts.

G Magnetotelluric sites
Electromagnetic methods
Magnetotelluric method
Frequency domain AEM method
Correction of static shifts
Findings
Conclusions
Full Text
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