Accurate estimation of impedance functions is essential for the correct interpretation of magnetotelluric (MT) measurements. Noise is inevitably encountered when MT observations are conducted and, consequently, impedance estimates are usually based on least-squares (LS) regression. Least squares ultimately assumes simple Gaussian statistics. However, estimation procedures based on LS would not be statistically optimal, as outliers (abnormal data) are frequently superimposed on a normal ambient MT noise field which is approximately Gaussian. In this situation, the estimation can be seriously misleading.An alternative method for making unbiased robust estimates of MT impedance functions is based on regression M-estimation and the Hilbert Transform, operating on minimum-phase MT impedance functions. In the resulting regression estimates, outlier contamination is removed and other departures from Gauss-Markov optimality are not critical. Using MT data from the Columbia River Plateau and the EMSLAB Lincoln line, it is shown that the method can produce usable MT impedance functions even under conditions of severe noise contamination and in the absence of remote reference data.

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Papandayan is a hydrothermally active volcano in Indonesia. We revealed the subsurface structure around the Mas Crater area of Papandayan based on the magnetotelluric (MT) and geomagnetic (GM) method. For the MT method, 14 sounding stations were deployed and two of them are located close to the active fumaroles. We estimated the MT response functions using a remote reference and then modeled the data with the aid of a 1-D robust inversion. The resistivity structure can generally be divided into three layers, namely a thin resistive surface layer, a middle conductive layer, and a more resistive basement. We interpreted the middle layer to be the hydrothermal zone or clay mineral. For the GM method, we measured the total intensity at 19 data points. The IGRF and diurnal variation were subtracted from the raw data. We then obtained the 2-D magnetic susceptibility model of magnetic field anomaly using an Occam inversion. The model shows a significantly low susceptibility structure beneath the fumaroles which might correlate with thermally demagnetized rocks.

Abstract. In conventional prospecting, scalar CSAMT measurement simplicity and low operational cost. Since the structure of earth's conductivity is complex, the scalar CSAMT The complex conditions need or tensor CSAMT, to interpret interpretation. A full solution 1D CSAMT forward modeling and used to interpret both vector and scalar CSAMT data. constrained inversion was interpretations. The results indicate the importance of vector CSAMT data in complex geological system. In conventional controlled-source audio-magnetotelluric (CSAMT) scalar CSAMT measurement is usually performed because of its simplicity and low operational cost. Since the structure of earth's conductivity is CSAMT method can lead to a less accurate interpretation. s need more sophisticated measurements, such as vector interpret the data. This paper presents 1D vector CSAMT ution 1D CSAMT forward modeling has been developed and used to interpret both vector and scalar CSAMT data. Occam's smoothness was used to test the vector and scalar CSAMT interpretations. The results indicate the importance of vector CSAMT to interpret CSAMT data in complex geological system. Keywords