The paper presents how the well integrity management system has evolved from a qualitative failure model to a novel data-driven approach using quantitative risk evaluation. This evolution allowed well integrity management to stop being a burden for operating companies and become an opportunity to improve efficiency and create value for their assets. The goal has shifted from constructing the wells in the cheapest and fastest way to providing production availability with cost efficiency, safety, and reliability; aiming to reduce carbon emissions. The concept and implications of this new paradigm, named Well as a Service will be described in the paper. This requires improvement in the design of the well, planning, and management of resources to guarantee operational readiness, integration with production, and clear safety and integrity controls.
The paper focuses on a new set of engineering tools that made Well as a Service possible. In the data-driven approach, different sources of information, such as the reliability history of wells and the real-time monitoring systems must be the centerpiece. New KPIs and criteria for managing the wells are also required. To illustrate how these tools can act combined to support planning and decision-making, some examples will be presented: how to select the best well design, how to manage the portfolio of wells, or make decisions related to a single well integrity failure.
The tools were inspired in the industries that are the benchmark in asset management such as aerospace and nuclear industries. The tools were developed each one for a specific purpose, for the design phase and the operational phase, for the safety and integrity aspects, and for the economic aspects. The correspondent performance indicators were developed as well as the acceptance and target criteria. The combination of tools, indicators, and acceptance criteria results in a panel that allows the management team to plan the resources and make decisions regarding the health of the wells. With the appropriate process, these technologies have generated value while maintaining or even increasing the safety of operations.
Finally, the paper will discuss the next steps in terms of technology to support Well as a Service. The future of risk-based decisions is condition-based, where not only probabilistic analysis provides optimal decisions but by measuring the current health of the components and predicting, based on degradation modeling, their performance in the future will allow deep discussions about remaining useful life, life extension, abandonment and influence the industry in the qualification process for new technologies.