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Abstract

A method for generating an improved estimate of horizontal conductivity, dip angle, azimuth and anisotropy parameter of an earth formation penetrated by a wellbore from dual-frequency transverse electromagnetic induction measurements, comprising generating an initial estimate of the horizontal conductivity, dip angle, azimuth and anisotropy parameter from the dual-frequency transverse induction measurements made at each one of a plurality of base frequencies. The initial estimates from each of the plurality of base frequencies are input into a primary trained neural network, and the improved estimate is calculated by the trained neural network. The network is trained by generating models of earth formations each having a known value of horizontal conductivity, anisotropy parameter, dip angle and azimuth. Voltages which would be measured by the transverse electromagnetic induction instrument in response to each model are synthesized. Initial estimates from the synthesized voltages are calculated and the initial estimates and known values from each of the models are input to the neural network to cause it to learn a relationship between the initial estimates and the known values.

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