This study contains analysis of translation method in the short story "A Blunder" by Anton Chekhov which is translated into Indonesian by students as the participants of this research. In translation analysis processes, the researcher used theory of translation method based on Newmark Theory. While to find out the equivalence in the translation, the researcher used Baker Theory. The researcher thought that there are a lot of variations methods appear in the results of translation, so he wants to know the kinds of equivalence translation used by the participants to make the target language (TL) more comprehensible. Qualitative descriptive method that includes observation and document analysis was used in this research. Here, the result of document analysis were consulted to the translation and literature expertise to check the result of the analysis. As the conclusion, the researcher finds 6 methods used by the participants to render the short story "A Blunder" into the target language (TL). Besides, the researcher finds two kinds of translation equivalence in the translations.

This paper presents a fit-for-purpose approach to mitigate zonal production data allocation uncertainty during history matching of a reservoir simulation model due to limited production logging data. To avoid propagating perforation/production zone allocation uncertainty at commingled wells into the history matched reservoir model, only well-level production data from historical periods when production was from a single zone were used to calibrate reservoir properties that determine initial volumetric. Then, during periods of the history with commingled production, average reservoir pressure measurements were integrated into the model to allocate fluid production to the target reservoir. Last, the periods constrained by dedicated well-level fluid production and average reservoir pressure were merged over the forty-eight-year history to construct a single history matched reservoir model in preparation for waterflood performance forecasting. This innovative history matching approach, which mitigates the impacts of production allocation uncertainty by using different intervals of the historical data to calibrate model saturations and model pressures, has provided a new interpretation of OOIP and current recovery factor, as well as drive mechanisms including aquifer strength and capillary pressure. Fluid allocation from the target reservoir in the history matched model is 85% lower than previously estimated. The history matched model was used as a quantitative forecasting and optimization tool to expand the recent waterflood with improved production forecast reliability. The remaining mobile oil saturation map and streamline-based waterflood diagnostics have improved understanding of injector-producer connectivity and swept pore volumes, e.g., current swept volumes are minor and well-centric with limited indication of breakthrough at adjacent producers resulting in high remaining mobile oil saturation. Accordingly, the history matched model provides a foundation to select new injection points, determine dedicated producer locations and support optimized injection strategies to improve recovery.