A Multi-Tool Approach to Predictive Well Integrity Diagnostics and Management in Oil and Gas Wells

Abstract Addressing well integrity issues becomes significantly more expensive when not detected early enough and can ultimately lead to total wellbore damage. Proper well integrity management is therefore important to maintain the structural soundness of downhole tubulars, limit environmental hazards, detect potential failures before they occur, and prevent production losses. This study utilizes a systematic operational technique combining field data with tool outputs for proper well analysis. It focuses on a case study dual-completion well in the south-south region of Nigeria. The approach involves first evaluating the well with the multi-finger caliper tool (MFC) in tandem with the electromagnetic thickness scanning tool (EMTS) under shut-in conditions. This is followed by deploying the dual spectral noise tool under flowing conditions, with data collected at varying depths and logging speeds as deemed fit from field data analysis. For more accuracy, the acquisition process also incorporated stop checks at critical depth intervals, such as completion item locations. Results showed the MFC analysis quantitatively classified the tubing joints into four wear categories based on wall thickness reduction. Ovality and eccentricity analysis, on the other hand, provided insight into stress zones, flagging zones exceeding 0.8% ovality and 0.015 inches eccentricity, while noise log data analysis provided insight into flow-induced noise and temperature anomalies at different zones. These findings were used to quantify zonal integrity, address sustained annular pressure, predict potential failures, and recommend timed future solutions. With all three diagnostic tools integrated and dual-condition logging exploring dynamic fluid behavior, the study provides a comprehensive system for well integrity diagnostics in oil and gas wells. While the findings are derived from a single case study, it breaks down the fundamental analysis employed and potential challenges, providing a predictive maintenance framework with significant adaptation potential for operators who seek to ensure sustained production and limit downtime due to integrity issues in similar wells. Future work is encouraged to explore and validate the methodology across multiple wells and varying conditions.