1. A method for interpreting electromagnetic survey data, comprising: acquiring electromagnetic survey data near a top of a portion of the Earth's substrate using an electromagnetic survey instrument comprising horizontally distributed electromagnetic sensors; generating an initial model of the portion of the Earth's subsurface, the model including at least spatial distribution of formation resistivity within the portion; applying the initial model to an artificial neural network trained to generate expected electromagnetic survey instrument response to the initial model, said training of the artificial neural network including input of type curves representing response of the electromagnetic survey instrument to vertically layered formations including layers of monotonically increasing resistivity, layers of monotonically decreasing resistivity, central layer sandwiched between boundary layers with resistivity of central layer greater than that of boundary layers, and central layer sandwiched between boundary layers with conductivity of central layer greater than that of boundary layers; comparing the acquired electromagnetic survey data to an output of the artificial neural network; and adjusting the initial model, and repeating applying the model to the artificial neural network and the comparing until differences between the output of the network and the acquired survey data fall below a selected threshold; wherein the adjusted model when the differences fall below the selected threshold is a result of the method.