Ultrasound image simulation is a well-explored field with the main objective of generating realistic synthetic images, further used as ground truth (e.g. for training databases in machine learning), or for radiologists' training. Several ultrasound simulators are already available, most of them consisting in similar steps: (i) generate a collection of tissue mimicking individual scatterers with random spatial positions and random amplitudes, (ii) model the ultrasound probe and the emission and reception schemes, (iii) generate the RF signals resulting from the interaction between the scatterers and the propagating ultrasound waves. To ensure fully developed speckle, a few tens of scatterers by resolution cell are needed, demanding to handle high amounts of data (especially in 3D) and resulting into important computational time. The objective of this work is to explore new scatterer spatial distributions, with application to 2D slice simulation from 3D volumes. More precisely, lazy evaluation of pseudo-random schemes proves them to be highly computationally efficient compared to uniform random distribution commonly used. A statistical analysis confirms the visual impression of the results.