Seismic acquisition having high geophone densities is compressed based on Functional Quantization (FQ) for an infinite dimensional space. Using FQ, the entire sample path of the seismic waveform in a target function space is quantized. An efficient solution for the construction of a functional quantizer is given. It is based on Monte-Carlo simulation to circumvent the limitations of high dimensionality and avoids explicit construction of Voronoi regions to tessellate the function space of interest. The FQ architecture is then augmented with three different Vector Quantization (VQ) techniques which yield hybridized FQ strategies of 1) FQ-Classified VQ, 2) FQ-Residual/Multistage VQ and 3) FQ-Recursive VQ. Joint quantizers are obtained by replacing regular VQ codebooks in these hybrid quantizers by their FQ equivalents. Simulation results show that the FQ combined with any one of the different VQ techniques yields improved rate-distortion compared to either FQ or VQ techniques alone.