What problem does it solve? Reservoir fluid characterization often requires dividing a heavy plus fraction (C7+) into pseudocomponents or reconstructing detailed compositions from lumped ones, which is tedious to implement correctly. This Skill provides dependency-free Python helpers for gamma molar splits, lumping split factors, delumping, and the universal Paraffinic-Aromatic split factor S, so engineers can run screening-level characterization before moving to rigorous NeqSim Java classes. ## Core Features & Use Cases - Whitson Gamma Split: Split a plus fraction into pseudocomponents with a single controllable alpha factor, returning per-pseudocomponent mole fractions and average molar masses. - Lumping and Delumping: Compute split factors from a detailed reference fluid and reconstruct detailed compositions from lumped ones with mole conservation. - Universal P/A Split Factor S: Divide heavy lumps into paraffinic and aromatic copies using a constant or MW-interpolated split factor, including a C7+ molecular-weight screening correlation. - Use Case: Given a reservoir fluid with 5% C7+ at 220 g/mol, split it into four pseudocomponents with alpha = 1.0, then map the result onto a universal P/A component set for process simulation. ## Quick Start Ask the AI to split a C7+ plus fraction of 0.05 with molar mass 220 g/mol into four pseudocomponents using the gamma split with alpha 1.0 and eta 90.
