The occurrence and number of herbicide-resistant weeds in the world has increased in recent years. Controlling these weeds becomes more difficult and raises production costs. Precision spraying technologies have been developed to overcome this challenge. However, these systems still have relatively high acquisition cost, requiring studies of the relation between the spatial distribution of weeds and the economically optimum spatial resolution of the control method. In this context, the objective of this work was to evaluate the best control resolution in simulated scenarios of weed distribution to create guidelines to relate the spatial variability of weed distribution with the optimum resolution of weed control. The methodology uses geostatistical simulations to construct different scenarios of weed distribution, based on real observations from Brazilian crop production fields. The simulations were made in a 0.1 X 0.1 m spatial resolution, considering only presence or absence of weeds to be sprayed in each pixel. We evaluated control resolution starting from 0.2 X 0.2 m to 36 X 3 m, considering section widths and valves on/off timing. In each scenario we calculated the minimum area to be sprayed using each technology, targeting a minimum of 99% of weed control. The economical evaluation was based on the total application cost, considering the herbicide savings and the increase in application cost of each technology. Low incidence levels and random distribution of weeds is favorable for sub meter control resolutions. For section control based applications the range is the more important parameter for predicting herbicide savings, and for nozzle control the nugget effect is more important. The raise in herbicide control costs are likely to be a key driver in the adoption of precision spraying technologies.