Euler deconvolution of gravity tensor gradient data

Tensor Euler deconvolution has been developed to help interpret gravity ten sor gradient data in terms of 3-D subsurface geological structure. Two form s of Euler deconvolution have been used in this study: conventional Euler d econvolution using three gradients of the vertical component of the gravity vector and tensor Euler deconvolution using all tensor gradients. These methods have been tested on point, prism, and cylindrical mass models using line and gridded data forms. The methods were then applied to measur ed gravity tensor gradient data for the Eugene Island area of the Gulf of M exico using gridded and ungridded data forms. The results from the model an d measured data show significantly improved performance of the tensor Euler deconvolution method, which exploits all measured tensor gradients and hen ce provides additional constraints on the Euler solutions.