GNGTS 2019 - Atti del 38° Convegno Nazionale

GNGTS 2019 S essione 3.1 593 rapporto segnale-rumore senza deteriorare significativamente la risoluzione laterale, e procedere con una vera e propria inversione. Inoltre, anche per acquisire sensibilità relativamente ai risultati, e provare ad avere una stima qualitativa della loro incertezza, è utile formalizzare, durante il processo di inversione, diversi tipi di informazioni a priori attraverso l’uso di diversi stabilizzatori. Nel caso del bacino del Nasia, le nuove inversioni hanno permesso l’identificazione di possibili paleovalli glaciali che potrebbero richiedere il ripensamento dell’attuale stratigrafia regionale (Dzikunoo et al. , 2020). Riconoscimenti. Questa ricerca è parzialmente supportata da: “Ground Water Development and Sustainable Agriculture” (GhanAqua)” (Project n. 14-P02-GHA) e CARMA (POR FESR Sardegna 2014/20 - cod. prog. RICERCA 1C-47). Si ringrazia, inoltre, il Geological Survey Authority del Ghana, ed, in particolare, il suo direttore, dott. Duodu, per aver concesso l’uso dei dati. Bibliografia Auken E., Christiansen A.V., Kirkegaard C., Fiandaca G., Schamper, C., Behroozmand A.A., Binley A., Nielsen E., Effersø F., Christensen N.B., Sørensen K., Foged N. and Vignoli G.: 2015 : An overview of a highly versatile forward and stable inverse algorithm for airborne, ground-based and borehole electromagnetic and electric data. Exploration Geophysics, 46(3), pp.223-235. Dzikunoo E., Flemming J., Vignoli G., Bruce B.Y. and Yidana,S.M.; 2018: A 3D geological model of the Nasia sub- basin, Northern Ghana - Interpretations from the inversion results of reprocessed GEOTEM . In AEM2018/7th International Workshop on Airborne Electromagnetics. Dzikunoo E.A., Vignoli G., Jørgensen F., Yidana S.M. and Banoeng-Yakubo B., 2020: New regional stratigraphic insights from a 3D geological model of the Nasia sub-basin, Ghana, developed for hydrogeological purposes and based on reprocessed B-field data originally collected for mineral exploration. Solid Earth, 11, 349-361, https:// doi.org. /10.5194/se-11-349-2020. Carney J.N., Jordan C.J., Thomas C.W., Condon D.J., Kemp S.J. and Duodo J.A.; 2010: Lithostratigraphy, sedimentation and evolution of the Volta Basin in Ghana . Precambrian Research, 183(4), 701-724. Cox L.H., Wilson G.A. and Zhdanov M.S., 2010. 3D inversion of airborne electromagnetic data using a moving footprint. Exploration. Geophysics, 41(4), 250-259. Høyer A.S., Vignoli G., Hansen T.M., Keefer D.A. and Jørgensen F.; 2017: Multiple-point statistical simulation for hydrogeological models: 3-D training image development and conditioning strategies . Hydrology and Earth System Sciences, 21(12), 6069. Jørgensen F., Menghini A., Vignoli G., Viezzoli A., Salas C., Best M.E. and Pedersen S.A.S.; 2017: September. Structural Geology Interpreted from AEM Data-Folded Terrain at the Foothills of Rocky Mountains, British Columbia . In Second European Airborne Electromagnetics Conference. Rapiti A., Jørgensen F., Menghini A., Viezzoli A. and Vignoli G.; 2018: Geological Modelling Implications-Different Inversion Strategies from AEM Data . In 24th European Meeting of Environmental and Engineering Geophysics. Vignoli G., Sapia V., Menghini A. and Viezzoli A.: 2017; Examples of improved inversion of different airborne electromagnetic datasets via sharp regularization . Journal of Environmental and Engineering Geophysics, 22(1), 51-61. Smith R. and Annan, P.; 1998: The use of B-field measurements in an airborne time-domain system: Part I. Benefits of B-field versus dB/dt data . Exploration Geophysics, 29(2), 24-29. Vignoli G., Fiandaca G., Christiansen A.V., Kirkegaard C. and Auken E.; 2015: Sharp spatially constrained inversion with applications to transient electromagnetic data . Geophysical Prospecting, 63(1), 243-255. Wilson G.A., Raiche A.P. and Sugeng F.; 2006: 2.5 D inversion of airborne electromagnetic data . Exploration Geophysics, 37(4), 363-371.