A Gas Well Production Prediction Model Based on Time-convolutional Neural Network

This paper explores gas well production prediction, a crucial aspect of gas field development planning and analysis. Traditional methods like decline curve analysis and numerical simulation have limitations due to their reliance on simple mathematical models. In contrast, machine learning offers a more flexible approach. The study applies a Temporal Convolutional Network (TCN) model to predict production for two gas wells. The model's performance was evaluated using MSE, MAE, RMSE, and R², with results showing the TCN method achieving better accuracy. The TCN model presents a promising new approach for gas well production forecasting.