Well Diagnostics Overview

Principles

Definition

Well diagnostics is a methodological approach focused on the systematic evaluation and characterization of the state, performance, and integrity of wells. It employs various testing, monitoring, and data analysis techniques to identify anomalies, optimize operational efficiency, and ensure long-term sustainability across diverse applications.

Ontological type

Core Methods

Well Integrity Assessment

Data Acquisition

Key developments

Key Figures

Real-Time Downhole Integration era

J. S. Selker[1] was active across Stanford University[2] and École Polytechnique Fédérale de Lausanne[3] during the Real-Time Downhole Integration era (2002-2009). In this era, Environmental temperature sensing using Raman spectra DTS fiber-optic methods[4] contributed to real-time environmental diagnostics and the standardization of diagnostic plots, underpinning life-of-well decision making and improved fracture and reservoir characterization. This progression underscores Selker's[1] role in integrating continuous downhole monitoring with real-time interpretation workflows. The collaborations across Stanford University[2] and École Polytechnique Fédérale de Lausanne[3] provided the institutional milieu that enabled these diagnostic advances within environmental and integrity-management applications.

Fiber-Optic Borehole Diagnostics era

Barry Freifeld [1] is a prominent figure in fiber-optic borehole diagnostics during the 2010-2016 era, with affiliations including Princeton University [2]. His key contributions, exemplified by the 2015 paper Field testing of modular borehole monitoring with simultaneous distributed acoustic sensing and geophone vertical seismic profiles at Citronelle, Alabama [3], advanced field-ready modular monitoring that integrates DAS and VSP techniques, a cornerstone for scalable downhole sensing in this era. This line of work demonstrated the value of modular downhole sensing and contributed to translating multi-physics signals into actionable diagnostics. Overall, these contributions helped establish the modular, field-deployable framework that defined fiber-optic borehole diagnostics in this era.

Distributed Pipeline Sensing era

Hong‐Nan Li[1] is associated with Fuzhou University[3] and China University of Petroleum, East China[4] in this era. Pipeline corrosion and leakage monitoring based on the distributed optical fiber sensing technology[7], providing scalable, noise-robust real-time detection that underpins automated, continuous pipeline health monitoring in this era. Tao Jiang[2] is associated with Sun Yat-sen University[5] and Wuhan University of Technology[6] in this era. Pipeline corrosion and leakage monitoring based on the distributed optical fiber sensing technology[7], highlighting the role of this approach in enabling continuous, automated pipeline health diagnostics.