3D joint inversion of gradient and total-field magnetic data

Recently, the processing of aeromagnetic data to account for leveling has developed into the use of gradients. Utilizing multiple magnetometers allows for the measurement of magnetic gradients and minimizes the diurnal variation and other common-mode noise. We extend the use of these data to quantitative interpretation through 3D inversion. We make use of a well-known relationship between the derivatives of the magnetic field and the derivative of its source to relate both data sets to a common source distribution. Our approach treats the observed gradients as an additional and independent dataset instead of being just supplemental information. These data are incorporated to spatially constrain the recovered model that will fit the total-field and gradient data. We present the methodology of the joint inversion technique and demonstrate it with a synthetic and field example.