Abstract This paper offers a comprehensive exploration into the field applications of Multiphase Flow Meters (MPFM) across global contexts, and the insights from the lesson learned of a smart oil field that truly represents an exemplary sample for evaluating MPFM technologies, as it encompasses several types of MPFM available in the market. By delving into the practical implementations of MPFM technology, the study uncovers invaluable lessons learned and best practices derived from diverse operational environments that drove the development of a robust auto-diagnostic solution to enhance MPFM performance. Through meticulous analysis and flow test data examination, this research illuminates the pivotal role of MPFM in optimizing oil field operations, enhancing production efficiency, and mitigating operational challenges imposed by subsurface complexity, CO2 injection, gas lift operations, testing equipment reliability, configuration, and limitations. Additionally, the paper provides an in-depth examination of common pitfalls encountered in MPFM applications, offering guidance for successful implementation strategies into future projects. Furthermore, the author reviews several technical papers detailing MPFM implementations worldwide, integrating the outcomes of published flow loop tests to enrich the discussion. The know-how and best practices obtained in this research help to develop an agnostic & Automatic diagnostic solution for MPFM system, that oversees the real time data while testing the wells, providing a health check report, indicating the potential root cause of low-quality test from the testing equipment perspective, distinguishing between genuine changes in well performance, metering issues, limitation, etc. Additionally, a benchmark study was conducted across numerous Oil fields, where some assets demonstrated acceptable MPFM performance while others did not. One Asset in particular faced significant challenges related to the quality of well tests post-MPFM installation, resulting in a high well test rejection rate, leading to a negative impact over the system efficiency, inefficient production scenario and poor reservoir management. However, these challenges were overcome after an exhaustive investigation, identifying the major root causes of errors that lead to the successful development of an automatic diagnostic system that support the process of well test quality assurance, highlighting equipment underperformance, sizing evaluation, process upsets, radioactive source issues or decay, proactive detection of fluid properties deviation from "the references" or well performance related issues through a real-time framework. The findings serve to inform industry stakeholders and researchers alike, offering valuable lessons learned from real applications about the adoption of MPFM technology, providing guidelines to achieve superior performance, data quality and reliability for operational excellence.
Rubio et al. (Mon,) studied this question.