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- W2026519394 abstract "Abstract The main objective of this study is to explore the use of parameter estimation techniques that handle cases where error variances (weights) in observed well-test data are uncertain. There are two main sources of uncertainty: 1) The gauge resolution and 2) measurement environment. Many gauges are used in well testing are not well characterized in terms of accuracy and resolution. The measurement environment in the wellbore is very noisy because of high frequency events in the wellbore (any producing interval), eg phase segregation. Because of these uncertainties, in this study, we investigated the use of parameter estimation methods based on the maximum likelihood and presented a new efficient method based on this method. The maximum likelihood method enables one to estimate error variances in pressure data along with the unklnown formation parameters. It is shown that the new method is efficient and powerful in estimating formation parameters from well-test data with uncertain variance. A simulated interval test from the multiprobe wireline formation tester in a single layer system as well as a field interval test in a three layer cross-flow system are used to demonstrate the applicability of the proposed methods." @default.
- W2026519394 created "2016-06-24" @default.
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- W2026519394 date "2000-10-01" @default.
- W2026519394 modified "2023-10-18" @default.
- W2026519394 title "Nonlinear Regression Analysis of Well-Test Pressure Data with Uncertain Variance" @default.
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- W2026519394 doi "https://doi.org/10.2118/62918-ms" @default.
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