Method for Forecasting the Efficiency of Matrix Acid Treatment of Carbonate

Abstract

In the international practice of developing hydrocarbon fields, one of the most common methods of influencing the bottomhole formation zone to stimulate the inflow is acid treatment. Despite the significant accumulated experience, subsoil users increasingly face with a decrease in planned and actual increases in production rates after this type of measures, which is due to both the deterioration of the resource base and the adoption of erroneous decisions during their design. It is necessary to scientifically substantiate the design of acid treatments, taking into account individual well conditions and a preliminary assessment of their effectiveness to reduce technological and economic risks. This study presents a method for predicting the result of acid stimulation on the formation based on multivariate regression analysis and laboratory studies on rock samples. Its approbation was carried out on the example of a carbonate production facility of an oil field in the Perm Krai. The obtained statistical dependencies made it possible to determine with high accuracy the potential success of the planned geological and technical measures, to give recommendations on their adjustment to achieve the target indicators. In the course of laboratory experiments, the optimal technological parameters of the impact were identified: the prospects of multi-volume acid treatments were established with the exclusion of the stage of acid aging for the reaction. The integration of the results of mathematical and physical modeling made it possible to select the required design of acid treatments in relation to the considered geological and physical conditions and assess their expected technological efficiency. The developed technique can be used to rank candidate wells, form and adjust targeted programs for geological and technical measures for short and long term periods, and determine the stimulation technology. The described algorithm can be successfully replicated to other fields.