The ultimate goal in survey design is to obtain the acquisition parameters that enable acquiring the most affordable data that fulfill certain image quality requirements. A method that allows optimization of the receiver geometry for a fixed source distribution is proposed. The former is parameterized with a receiver density function that determines the number of receivers per unit area. We optimize this receiver density function through an iterative gradient descent scheme that minimizes the difference between the image obtained with the current acquisition geometry and a reference image. The reference image is obtained from prior subsurface information that is assumed to be available. We tested the method with different subsurface models. The results indicate that the acquisition geometry is optimized according to the complexity of each subsurface model. The receivers are moved toward the areas where more data are needed for obtaining better imaging.
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