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At present, the most common tools for drilling operations are those rock-destroying ones that are equipped with cutting elements made from polycrystalline diamonds (PDC) and diamond carbide inserts (DCI). Given this, it is a relevant task to study the influence of the degree of wear of cutting elements on the strength and energy parameters of the process of rock destruction. In order to determine this influence, we have experimentally investigated the cutting process involving a single cutter under laboratory conditions. The mean values of the cutting force components (circular ((Рz) and normal (Рy)) have been established at the cutting depth 0.5; 1.0; 1.5; and 2.0mm, at a varying degree of the cutting element wear (a flat of 0; 5.0; and 8.0mm). We have determined the magnitude of cutting work and the specific energy of rock destruction. At a cutting depth of 0.5mm, with an increase in the cutting element wear rate from 0 to 8mm, the magnitude of work grows from 0.06376 to 0.121 N∙m. At a cutting depth of 2.0mm, the magnitude of work increases from 0.624 to 3.603 N∙m. The energy intensity of the rock destruction process increases, with an increase in the cutting depth from 0.5 to 2.0mm, from 3.88kJ/m2to 11.66kJ/m2for a sharp cutter. Based on the study results, we have built dependence charts of the average values of the cutting force components and its normal component (Рy) on cutting depth and the cutting element wear degree. The results obtained have shown a significant influence of the size of the wear flat on the increase in the process strength parameters, which is the basis for regulating a wear degree of cutting elements during drilling. We have established the tendency towards a growth in the resultant force and specific work of rock cutting by a cutting element with an increase in wear degree. This makes it possible to determine, based on the indicators of fluctuations in the instantaneous strength values during drilling of wells, or based on a change in power, the wear degree of the cutting elements, and to predict the probability of their destruction