During the last two decades, the efficiency and economy of horizontal wells have significantly increased owing to the successful introduction, adoption, and application of new technologies. Proper planning and economic evaluation of proposed horizontal wells requires sufficiently accurate geological and reservoir modeling. Without such an approach, the economic success of any horizontal well should be considered a high risk.

Production logging data in both the horizontal section and the vertical sections are important elements in evaluating the performance of horizontal wells and provide dynamic data for optimization of reservoir modeling and the determination of long-term economics and ultimate recoverable reserves. However, acquiring quality data in horizontal wells remains a significant challenge. In highly deviated and horizontal wells, production-log job planning, which considers the combination of production logging tool sensors and data analysis methods, is a key factor for obtaining accurate information concerning the behavior of well fluids, formation characteristics, and the extent of well-completion mechanical problems.

The objective of this paper is to share the results of measurements taken from new production logging sensors and analysis methods with production data. These results were used to appraise the efficiency of the tool string by evaluating the acquired data and validating the analysis outputs along with the interpretation conclusions of the production efficiency. The "new-to-the-industry" analysis method consists of integrating multi-probe sensor data, including spinner calibration, superficial-phase velocity calculations, and phase hold-up measurements in a continuous wellbore environment.

While the acquired data has shown valuable information concerning fluid types, fluid compositions, and fluid velocities in these different flow environments, the analysis method has provided a complete integrated interpretation with a more accurate production profile, which is required to properly monitor reservoir performance and diagnose well-production problems.

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