Reservoir Performance Prediction in Steam Huff and Puff Injection Using Proxy Modelling

نویسندگان

چکیده

Steam huff and puff injection is one of the thermal EOR methods in which steam injected a cyclical manner alternating with oil production. The cost time inefficiency problem reservoir simulation persists design scheme. Building predictive proxy models suitable solution to deal this issue. In study, method were developed using two machine learning algorithms, comprising conventional polynomial regression an artificial neural network algorithm. Based on one-well cylindrical synthetic model, 6043 experiment cases 28 input parameter values generated simulated. Outputs from results such as cumulative production, maximum production rate at cycle end extracted each case build model. Reservoir properties that could change after also modeled. evaluated based fitting performance R-square value, mean absolute error (MAE) value root square (RMSE) value. Then, Sobol analysis was conducted determine significance show have better compared models. Neural average over 0.9 lower MAE RMSE than result applying indicates initial water saturation viscosity are most important parameters for predicting performance.

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ژورنال

عنوان ژورنال: Applied sciences

سال: 2022

ISSN: ['2076-3417']

DOI: https://doi.org/10.3390/app12063169