Abstract

Seismic reflection, aeromagnetic, and gravity data along the 1.1 Ga Midcontinent Rift System reveal that the greatest thicknesses (15–22 km) of Keweenawan lavas are contained within asymmetric grabens bounded by what are now listric reverse faults, but which must have acted as normal growth faults during much of the volcanism (Chandler et al. 1989; Cannon et al. 1989; Cannon 1992; Thomas and Teskey 1994). This is particularly true of the Portage Lake Volcanics (PLV) and their equivalents which form the upper part of the Keweenawan volcanic sequence in the Lake Superior region. Although incomplete sections of what have historically been termed the PLV are exposed only on the Keweenaw Peninsula and Isle Royale, recent geophysical studies have shown the PLV sequence to underlie most of Lake Superior and attain a thickness as great as 15 km. These geophysical studies also show that the PLV basin terminates in the western Lake Superior region in a structurally complex manner Although geologic interpretations of some seismic profiles (Grant-Norpac lines 57 and 53, Fig. 1) by us and others (Thompson et al. 1990; Sexton and Henson 1994) suggest that the PLV sequence projects onshore in northeastern Minnesota, the geologic and structural manifestation of that projection has yet to be characterized. Toward that end, we present geologic, geophysical, petrologic, and structural evidence that suggests that (1) the Schroeder-Lutsen basalts, which occupy the uppermost part of the North Shore Volcanic Group (NSVG), are correlative with the base of the PLV section, and (2) the southwestern margin of the PLV basin is marked by a growth fault that is recognized as an extensive composite diabase dike system within the Beaver Bay Complex, which we term the Finland tectono-magmatic discontinuity (FTMD, Fig. 1).KeywordsGrowth FaultSeismic ReflectionSeismic Reflection ProfileAeromagnetic DataWestern LakeThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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