Abstract: A computer-implemented method that enables dew point pressure prediction using isothermal constant composition expansion and artificial intelligence is described herein. The method includes obtaining constant composition expansion data of a reservoir fluid, and predicting saturation pressures for the reservoir fluid at the constant composition expansion data points using a trained machine learning model selected from multiple machine learning models that are trained using data from a generated constant composition expansion library. The method also includes determining a central tendency of the predicted saturation pressures to obtain a final saturation pressure corresponding to the constant composition expansion data for the reservoir fluid.

Abstract: A computer-implemented method for automated decline curve and production analysis using automated production segmentation, empirical modeling, and artificial intelligence. The method includes segmenting historical production data based on a change in a central tendency of a selected segmentation parameter to generate segmented production data. The method also includes forecasting future production data from a last production segment to a terminal decline rate according to a fitted empirical model, a trained artificial intelligence model, or any combinations thereof. The method includes forecasting exponential production data to an economic limit. Further, the method includes calculating an estimated ultimate recovery by summing the historical production data, future production data, and the exponential production data.