Relevance of the research is due to the low proportion of successful hydrochloric acid treatments of near-bottomhole zones of carbonate reservoirs in the Perm region caused by insufficiently careful design and implementation of measures to stimulate oil production. Within the framework of this article, the development of a program is presented, which is based on an algorithm that allows determining the volume and rate of injection for an acid composition into a productive formation corresponding to the maximum economic efficiency during hydrochloric acid treatment. Essence of the proposed algorithm is to find the greatest profit from measures to increase oil recovery, depending on the cost of its implementation and income from additionally produced oil. Operation of the algorithm is carried out on the principle of enumerating the values of the volume and rate of injection for the acid composition and their fixation when the maximum difference between income and costs, corresponding to the given technological parameters of injection, is reached. The methodology is based on Dupuis's investigations on the filtration of fluids in the formation and the results of the experiments by Duckord and Lenormand on the study of changes in the additional filtration resistance in the near-well zone of the formation when it is treated with an acid composition. When analyzing and including these investigations into the algorithm, it is noted that the developed technique takes into account a large number of factors, including the lithological and mineralogical composition of rocks, technological parameters of the injection of a working agent and its properties, well design, filtration properties of the formation, properties of well products. The article provides an algorithm that can be implemented without difficulty using any programming language, for example, Pascal. Selection of the optimal values for the volume and rate of injection is presented in this paper, using the example of a production well at the Chaikinskoye oil field, located within the Perm region. Introduction of the developed algorithm into the practice of petroleum engineering will allow competent and effective approach to the design of hydrochloric acid treatments in carbonate reservoirs without a significant investment of time and additional funds.
Amid the ever-increasing urgency to develop oil fields with complex mining and geological conditions and low-efficiency reservoirs, in the process of structurally complex reservoir exploitation a number of problems arise, which are associated with the impact of layer fractures on filtration processes, significant heterogeneity of the structure, variability of stress-strain states of the rock mass, etc. Hence an important task in production engineering of such fields is a comprehensive accounting of their complex geology. In order to solve such problems, the authors suggest a methodological approach, which provides for a more reliable forecast of changes in reservoir pressure when constructing a geological and hydrodynamic model of a multi-layer field. Another relevant issue in the forecasting of performance parameters is accounting of rock compressibility and its impact on absolute permeability, which is the main factor defining the law of fluid filtration in the productive layer. The paper contains analysis of complex geology of a multi-layer formation at the Alpha field, results of compression test for 178 standard core samples, obtained dependencies between compressibility factor and porosity of each layer. By means of multiple regression, dependencies between permeability and a range of parameters (porosity, density, calcite and dolomite content, compressibility) were obtained, which allowed to take into account the impact of secondary processes on the formation of absolute permeability. At the final stage, efficiency of the proposed methodological approach for construction of a geological and hydrodynamic model of an oil field was assessed. An enhancement in the quality of well-by-well adaptation of main performance parameters, as well as an improvement in predictive ability of the adjusted model, was identified.