Reliable gas well tests provide valuable data for production optimization and maximizing ultimate recovery of gas reserves. Poor data quality, heightened process safety risks and elevated OPEX are inherent limitations in the methods undertaken by operators to measure Condensate Gas Ratio (CGR) during Multi-Rate Tests (MRT) and routine production. This paper describes the steps undertaken by the team in BERA to overcome this challenge by utilizing the density-measuring capability of the Coriolis meter. A density-based algorithm was setup using a designed decantation procedure and encoded in the control system for real-time measurements and made available in the office domain. This technique provides improved data quality, ease of well surveillance and a long-term cost avoiding option while simultaneously increasing the flexibility and ease of executing MRTs. It eliminates the need for manual sampling with its associated process safety concerns.

A well provides the conduit through which hydrocarbons flow from the reservoir to the production facility. It is also a containment barrier once hydrocarbons are released from the reservoir. NORSOK D-010 and OGUK standards stress that ‘installation, removal, testing and monitoring of barriers during all operations’ is key for managing well integrity. Operators are often challenged with both minimising costs and upholding the highest standards of integrity management as they extract value from the wells. They are required to have a documented basis justifying a lower test frequency or accept test frequencies recommended by regulators. They are also challenged with keeping the right stock level of wellhead items for timely repairs or replacement. Addressing both is vital towards minimising deferments, maintenance and inventory costs. This study presents a data-driven philosophy for well integrity management and repair strategy based on the well integrity measures of a major UK operator. It examines failure and repair data of 500+ wells in the North Sea. The data was sourced from a Well Integrity Management System (WIMS) database, processed, analysed and used to develop a statistical stocking model. The Severity Frequency (SF) concept was developed and introduced as a basis for failure trend comparison among well types and well components. Well integrity test intervals, expected annual failures and limiting levels of valve spares were evaluated using this parameter. The analysis showed a link between failure drivers and frequencies to well type and flow conditions. This should be the basis upon which well integrity is managed and appropriate stock levels determined. A comparison of the Stocking levels derived from this exercise shows a realism when compared with the frequency of actual changes/replacements done on the wellhead. It is believed that this approach can improve the management of well integrity quantitatively, minimise costs and deferments associated with overstocking wellhead items and high mean time to repair.