An Interactive Python Based Tool for Flow Rate Prediction and Express Well Completion Design

Accurately predicting oil flow rate in the presence of near-wellbore damage remains a persistent challenge in well completion design, especially when multiple subsurface and fluid properties must be considered. This study introduces SkinFlow, an interactive Python-based application that helps evaluate flow efficiency in open-hole completions for both vertical and horizontal wells. Using established analytical models, the platform lets users adjust input parameters and instantly see the effect on skin factor and oil production rate. SkinFlow offers real-time sensitivity analysis, combined-parameter evaluation, and Monte Carlo simulation. Engineers can test the effect of individual variables or apply several changes together, mimicking treatments such as acidizing, damage removal, or wettability alteration. Probabilistic modeling allows uncertainty in key parameters to be represented through probability distributions, giving a realistic range of outcomes. To demonstrate its value, a case study compared two wells in the same reservoir. Well №2026 produced 500.1 STB/D with a skin of 7.19, while Well №2025, affected by severe damage, produced only 268.3 STB/D with a skin of 20.72. Deterministic stimulation modeling of Well №2025, with altered-zone permeability raised from 10 to 200 mD, increased production to 1207 STB/D and reduced the skin by 43.5 percent. Monte Carlo analysis confirmed clear gains, forecasting post-stimulation rates with a median of 981 STB/D. A second application focused on the pilot horizontal Well №872_H, drilled into a tight, low-permeability formation. Using SkinFlow, the stimulation team was able to rapidly explore how changes in drawdown and near-wellbore permeability would influence performance. The platform delivered an express forecast of potential gains, showing that even under conservative assumptions the well could increase from about 120 STB/D to around 840 STB/D, giving the team confidence to move ahead with stimulation. These results show that SkinFlow can guide stimulation planning while also serving as a practical educational tool. Students can interact with real reservoir parameters and open-hole completion characteristics, adjust values in real time, and instantly see how those changes impact oil rate and formation damage. This hands-on interaction helps students build a clear understanding of how well performance is shaped by completion design, reservoir conditions, and stimulation.