Many fields of the Solikamsk depression of the Perm region are characterized by the final stage of development and have a high oil recovery rate, close to the design, a high water content of the production, a deterioration of technical and economic indicators of production. To achieve the project indicators at the fields, various methods of enhanced oil recovery are used. The analysis of their application shows that the highest average increase in the initial oil production is achieved by sidetracking. When justifying the location of the lateral wellbore in the range of the productive formation, one of the main indicators of further well performance is the initial oil productivity index of the well.
The proposed method allows us to estimate the values of the oil productivity index for oil wells with a sidetrack based on the results of geophysical and hydrodynamic wells studies, values of reservoir properties, physical and chemical oil properties, as well as geological and technological indicators using mathematical statistics. At the first stage, correlation fields were constructed for all parameters of the initial data. Analysis of field data in combination with the values of the correlation coefficient showed the degree of influence of parameters on the oil productivity index. Then, for all values of the initial data using a step-by-step regression analysis, a multidimensional regression equation was obtained, in which the dependent variable was the oil productivity index, and the remaining parameters were independent. Next, a comparison was made between the actual and calculated by the equation model values of the productivity index in order to determine the uniform distribution of the obtained values. To determine the classes, the dependence of the oil productivity index on the zenith angle of the sidetrack in the interval of the reservoir α, as the most statistically significant, was chosen. At the final stage, to predict the values of the oil productivity index, taking into account the selected classes, regression equations were obtained, which made it possible to increase the accuracy of the forecast of the oil productivity index.
References
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