As deeper the oil and gas production goes more important the remote monitoring and control of the subsea assets become, and more reliable they need to be. This work aims to perform a quantitative and qualitative reliability study in a key and complex asset which is part of the subsea production system, the Subsea Control Module (SCM). The benchmark used to evaluate the performance of the assets is the Offshore and Onshore Reliability Data (OREDA) which is a worldwide database from failure records from all segments of the oil industry and different operating companies.
The methodology used in this paper is applicable to any equipment in the oil and gas industry, which was based on statistical analysis and functional study through RAM analysis using block diagram. For this case study a field dataset from 106 SCMs were gathered, analyzed and compared with the OREDA 2015 benchmark.
The reliability distribution for this specific dataset demonstrates an infant failure pattern which is aligned with benchmark in the industry for complex hydraulic and electronic systems, even though for 5 years operating time systems achieves a reliability of 86,83% outperforming the average benchmark from OREDA. The methodology allows a better understanding of how far from a world class performance the asset of interest is and which components are bringing your reliability down. One of the limitations of this study is the few data points available.
The production in deep water and ultra-deep-water fields are increasing every year due to the decrease of production in mature fields. This work contributes with the current literature with field data from deep water operations of Subsea Control Module (SCM), which is a very relevant dataset due to the limited quantity of SCMs in those types of fields. Additionally, the methodology presented here is simple and can be applied using free software.