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This matched model was used for prediction of weight percent of precipitated asphaltene from crude oil at any other temperature and pressure.
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The production forecast is analyzed and the predictive capacity of the matched models is assessed.
Our main conclusion is that, even with regularisation, many distinct history matched models are possible, which highlights the importance of applying optimisation methods capable of identifying all such solutions.
The predicted probabilities for CRC incidence in the logistic model, PS weighted outcome model and PS matched models were higher than the unadjusted model, whereas the IVA estimates were lower than the unadjusted model.
The inclusion of a robust array of independent variables in the propensity score matching model is also a strength.
A propensity score-matching model was implemented to take account of the selection bias due to observed individual heterogeneity.
Test results show that the most match model was the three-parameter Weibull distribution; two-parameter Weibull distribution ranked second; the last was logarithmic normal distribution.
The edge-to-edge matching model was used for investigating and comparing the possible poisoning effects of several binary and ternary intermetallic compounds containing Si and Ti.
The edge-to-edge matching model was used to investigate and compare the grain refining efficiency of various (Al, Mn) containing phases existing in the melt.
Note however that results were qualitatively similar regardless of which particular matching model was used.
The history-matched model was applied for various flood processes.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com