In the context of the coronavirus pandemic and quarantine measures taken by the international community, energy demand declined significantly in the second quarter of 2020. In April, oil prices fell to a record low of $13-$14 per barrel. In order to restore oil prices, OPEC+ imposed strict restrictions on production in May. This has in turn decreased the number of drilling wells significantly and has had a negative impact on oilfield service companies. The decline of the oilfield services can lead to a loss of skills in the development of hard-to-recover reserves and to a loss of global market share. In order to reduce risks and ensure accelerated recovery of production volumes, a number of countries are developing and introducing methods of state subsidising to stimulate the construction of oil wells up to the moment of their completion. In Russia, the Ministry of Industry and Trade is also developing a plan to provide preferential loans to oilfield service organisations, and then oil companies will redeem finished wells. Given the recession in the global economy, the high volatility of macro parameters, the risk of the second wave of coronavirus and the new OPEC+ restrictions, makes it necessary to determine the best and most sufficient, but not excessive, mechanism for supporting oilfield services and stimulating the optimal pace of construction of oil wells depending on the type of oil fields and their remoteness from world markets’ sales. In view of the high uncertainty of model parameters, this paper proposes to use probabilistic methods and Bayesian methods to solve the above problems.