Development of a Reliability and Maintenance Database System for Offshore Well Equipment in Brazil: MINERVA, Phase 1

Abstract

Abstract This report discusses some of the main challenges and opportunities in the development of a well completion equipment database system in Brazil. To improve the quality of reliability and risk assessments, a major oil field operator recruited a multidisciplinary team to design and implement a Reliability and Maintenance (RM) database system. The primary objective of the proposed solution is to prevent equipment failure and mitigate associated downtime in offshore operations. However, a significant challenge lies in the dispersion of relevant data across multiple sources, including websites, various data repositories, and diverse formats. To address this issue, the solution aims to collect and consolidate these dispersed data into a single, standardized database. The development process involved a comprehensive data science approach encompassing crucial steps such as data collection, cleansing, and standardization. The overarching goal was to strive for accuracy and data integrity. By establishing a centralized and structured database, the solution empowers decision-makers to access reliable and comprehensive data, ultimately improving the management decision process. As a result, a reliability database named MINERVA (MINEr of Reliability for Value Adding) was built with more than 15,000 well-years data (operating time). The main idea is to improve the quality of the risk and reliability assessments for, e.g., workover demand estimates, completion alternative evaluations, "what-if" analysis, and so on. Among the contributions from the efforts undertaken at MINERVA Phase 1, is the incorporation of knowledge for the industry that translates into savings in operating costs such as maximization of well reliability and availability, reduction of the carbon footprint of production operations by avoiding unnecessary interventions, reduction of workover duration and the need for spare parts and associated logistic costs.