Analysis of a step-by-step regression model application to predict the effectiveness of a formation proppant fracturing for Tl-Bb terrigenous object
Based on the data, obtained from 36 wells where a formation hydraulic fracturing (FHF) was conducted, the article studies the influence of various indicators on its efficiency. It is found out that FHF efficiency is controlled by a number of geological-technological parameters. Multidimensional regression models are constructed to determine these parameters. The data of four wells was used for the first model construction. The predicted value of oil flow rates was calculated for the other 32 wells, followed by its comparison with the actual values. The comparison is made by calculating the correlation coefficient r. This will allow to evaluate the "working capacity" of the constructed models. It was revealed that oil production increase tends to a maximum: a decrease in the formation occurrence depth; low efficiency factor and high fluid flow rate during fracturing. Based on the results of the analysis, the optimal equation was chosen, which includes 19 wells in training. The basic parameters that pay influence on oil flow-rate growth subsequent decrease are hrel. (≥ 1400 m), kcont. (~0,3 m3/day MPA), Qconsumpt. (~3,8 m3/min), Vzhr (~30 m3). If hrel. > 1400 m it is recommended to increase nprop. and Vgel.. When planning a formation hydraulic fracturing to achieve growth of more than 9 t/day it is necessary to account of kperm near zone (~0,040 mcm2). Statistical analysis of wells with performed hydraulic fracturing of the formation allows constructing an optimal regression equation for forecasting oil flow-rates increase and determining the influence of parameters on the qualitative and quantitative level.