System Engineering Recommendations to Improve Intelligent Completions

Abstract

This paper compiles recommendations from a broad range of sources into a single document to aid future intelligent completion installations and operations. While emphasis was placed on subsea completions, these recommendations can be readily applied to differing well types. Important differences between production wells and injection wells are addressed. While it may appear that intelligent completion equipment can be treated as "commodity items" like many other completion components, this is not recommended. Intelligent completions are complex systems with design and operational requirements that span many engineering disciplines and impact many well components. Changing well temperatures and reservoir pressures generate unique and sometimes very challenging design conditions, with thermally-induced pressure gains in the control lines being an example. Failing to address all load cases, selecting the wrong control fluid, failing to properly clean even a single component, or employing the wrong operating practice even once, can permanently risk the integrity and/or operability of the intelligent completion. This paper reviews each component within the intelligent completion and details a systemic approach for identifying risk and optimizing its design. The recommended process starts with the control fluid and methodically works through the rest of the intelligent completion components and processes. Systems engineering can lead to important insights to overall system specification, risks, and operating recommendations. Numerous recommendations and learnings from past projects are shared. Additionally, the need to properly manage and operate the intelligent completion doesn't end with handover to Production. Recommendations for optimizing system longevity and diagnosing non-conformances are also provided. A spreadsheet-based method of accurately assessing pressure gains in control lines is described, as are several recommended additions to the tree and other parts of the intelligent completion system. Explanations for anomalous behavior seen on several projects, which become clearer through the lens of systems engineering, are shared.