Overcoming Challenges of Testing Gas Lifted Wells Via Multiphase Flowmeters with a Novel Work-Process Approach Embedded in a Digital Outlook to Enhance Well Test Data Quality. Lesson Learned from a Smart Field in Abu Dhabi
Authors: Rubio Erismar , Gupta Gaurav , Al-Attar M. , Ali Ahmed Qambar Abdalla , Eltony Ibrahim , Davila Rayner , Al Nuaimi Mai 
Published: October 2023

Abstract
Multiphase flow meter's (MPFM) reliability is a challenge that several oil operators face continuously. Many companies adopt this option attracted by its operational flexibility and cost saving proposition, when testing facilities must have minimum footprint or/and remote operational cases, demanding continued monitoring. However, to succeed, they will require dedicated personnel to monitor their performance, significant investment in instrumentation to allow remote operations, additional surveillance activities and quality-checks routines to maintain 2-10% accuracy.
Moreover, subsurface complexity led to larger uncertainty and deviations in production reconciliation. This case study is presented in one smart field located in Abu Dhabi, composed by tight reservoirs with strong compositional gradient, with saturation pressure ranging from 1000 to 3600 psi along with a large areal and vertical solution gas variation. On the other hand, the EOR program has been in place for the last 40 years, injecting WAG and CO2 in inverted patterns with potential breakthrough in producers. The majority of the wells were commissioned with gas lift, as they were not able to flow naturally; therefore, produced gas will be indirectly estimated from total produced gas. Limited PVT reports are used as reference across field while common PVT data is used in neighbor wells located few Kms away. Furthermore, surface facilities were newly commissioned, adding additional uncertainties anticipated from new projects, which reliability is represented as a "bath-type curve" with expected high-failure rate at the beginning, followed by a failure reduction after some maturity and understanding is achieved; and finally, it will escalate due to equipment wear out. Therefore, early systematic errors with regard to meters configuration, design, data-streaming and data-inputs were found and corrected. Wells are controlled remotely and are equipped with surface pressure and temperature transmitters that can be monitored from the office for production optimization efficiency.
The asset deals with different MPFM providers and technology principles such as: dual-gamma source, single-gamma source and non-radioactive sources to be learned in a very short time. 70% of the flow-tests performed via MPFM were rejected due to anomalies in GOR or rates over-prediction, identified by a 20% additional oil production compared with export fiscal meters. It can be seen that GOR anomalies correction was not obvious, as it represents a multidimensional problem with several sources of errors to investigate. This paper presents the lesson learned from the implementation of real-time monitoring techniques on MPFM to evaluate its performance and troubleshooting, focusing on a novel and simple methodology of root cause analysis with smart analytics, including comparison with continues physics and AI based Virtual Meters, integrated with auto-diagnostic system, allowing optimum allocation of field resources while minimizing vendor intervention, with implicit cost saving. This novel approach provided a quick problem detection enabling the asset to improve its well test acceptance from 50 to 92% due to MPFM reliability improvement.
The presented methodology also opened the door to introduce real time gas lift and production optimization exploiting direct measurements of MPFM parameters such as GVF, permittivity and mix-densities.