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- W4242074072 abstract "Statistical methods are capable of revealing variation trends of study cases by only processing source data. N-way analysis of variance and multivariate linear fitting are a few excellent examples. Then in order to cast off the reliance on using physical model parameters, a statistical method combined N-way analysis of variance and multivariate linear fitting is proposed. This article discloses the function of proposed method in terms of porosity prediction when only logging data is available. The data used for verification derives from the lacustrine carbonate reservoirs of IARA oilfield. Five experiments are well-designed to analyse capability of the method on porosity prediction. Experiment results prove that the proposed method can only utilise logs to predict porosity, and the predicted outcomes are accurate. The proposed method can be viewed as a new tool to obtain porosity data when only logs are handled. [Received: March 8, 2018; Accepted: February 14, 2019]" @default.
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- W4242074072 date "2020-01-01" @default.
- W4242074072 modified "2023-10-16" @default.
- W4242074072 title "Efficient prediction for porosity only using logging data: a case study of lacustrine carbonate reservoirs of IARA oilfield" @default.
- W4242074072 doi "https://doi.org/10.1504/ijogct.2020.109446" @default.
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