The attenuation of source-generated coherent noise energy can be a challenging problem for land data where surface waves often exhibit complex behavior with multiple propagation modes, high lateral variability and relatively short wavelengths. The traditional acquisition and processing strategy for mitigation of coherent noise has combined analog spatial filtering through source and receiver arrays in the field, with multi-channel digital filtering in data processing. The field arrays act as complementary spatial anti-alias filters for data processing algorithms which have difficulty in dealing with aliased events. Limitations of the available processing procedures place constraints on the acquisition design which can potentially both limit flexibility and increase the cost of the acquisition. A new model-based approach to sourcegenerated coherent noise attenuation is presented, where the local properties of the multi-mode surface waves are estimated from the seismic data and used to generate a detailed model of surface-wave noise, spatially-variable over the survey area. The method has significant advantages with respect to the handling of aliased coherent noise energy, and robustness to spatial irregularities. The availability of effective processing tools for aliased noise attenuation can have a significant impact on required survey geometry, and on the cost of land exploration.