SYSTEM AND METHOD FOR DATA-DRIVEN HYDROCARBON FLUID PROPERTY PREDICTION USING PHYSICS-BASED AND CORRELATION MODELS

Abstract: examples of methods and systems are disclosed. the methods may include training a predictor by obtaining, using a laboratory fluid properties analysis system and using physics-based and/or empirical-correlation models, a fluid properties dataset at multiple temperature and pressure conditions. the methods may also include segregating the plurality of data vectors into a plurality of segregated training subsets and forming a set of trained sub-predictors, by training each sub-predictor to predict an output data vector from an input data vector. the methods may further include forming a trained predictor, trained to predict a high-fidelity estimate of an output data vector from an input data vector, by combining each member of the set of trained sub-predictors.

Inventor(s): Ahmed H. Al Ayesh, David Echeverría Ciaurri, Mohammed A. Shahri

CPC Classification: E21B49/0875 ({determining specific fluid parameters})

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