cyclic gradient methodlinear convergence rate92C5515A2965K1068U10In this paper, we consider a joint-inversion problem using different types of geophysical data: gravity and magnetism. We first formulate two kinds of inverse problems in the famework of the first kind Fredholm integral equations, ...
Cross-gradient functionjoint inversionmagneticpompeiiresistivityIn this paper we perform a 2-D joint inversion of DC resistivity and magnetic data, constrained by cross-gradients. Inspired by methods developed for potential fields, we introduce into both the separate and joint inversion algorithms also ...
Based on previous work, we present a cross-gradient joint inversion algorithm for gravity and NSS data that employs several proper constraint techniques to reduce the effect of remanent magnetization and improve the resolution of the inverted results. We chose to use NSS data because such data are...
The gravity vertical gradient anomaly is sensitive to the shallow source body providing a relatively high horizontal resolution in imaging.The gravity anomaly contains more information of the deep source body than the shallow.Gravity and gravity gradient
We train the models using Stochastic Gradient Descent. To adapt textual data to our models we use the network architecture described here. First, we represent descriptions by average-pooling the Skip-thought [23] representations of each sentence in a given description (a description contains ...
Gallardo, L.A., 2007, Multiple cross-gradient joint inversion for geospectral imaging, Geophysical Research Letters, 34, L19301, doi:19310.11029/12007GL030409.Gallardo LA (2007) Multiple cross-gradient joint inversion for geo- spectral imaging. Geophys Res Lett 34(19):L19301...
Presently, the cross-gradient inversion scheme stands out as one of the most robust joint approaches, and some authors modified it to manage complex topographies on unstructured meshes even if at the expense of introducing additional parameters in the inversion process. We propose in this work a ...
We present a 3-D cross-gradient joint inversion algorithm for seismic refraction and DC resistivity data. The structural similarity between seismic slowness and resistivity models is enforced by a cross-gradient term in the objective function that also includes misfit and regularization terms. A ...
We have developed a data-space multiple cross-gradient joint inversion algorithm, and validated it through synthetic tests and applied it to magnetotelluric (MT), gravity and magnetic datasets acquired along a 95 km profile in Benxi-Ji'an area of northeastern China. To begin, we discuss a ...
We then perform the 2D cross-gradient joint inversion of gravity and magnetic datasets. Finally, we adapt the structural joint inversion to include the AEM resistivity model as a constraint. We show that there is an area commonly sensed by the three datasets and that the coupled resolution ...