Infrared spectroscopy for real-time gas logging: a critical review of methodological advances and field deployment challenges

Infrared (IR) spectroscopy has emerged as a transformative technology for real-time gas logging, overcoming limitations of traditional chromatographic methods by enabling rapid, noninvasive compositional analysis of formation gases during drilling. This review critically examines recent methodological advances and persistent field implementation challenges associated with IR-based gas logging systems. Through systematic analysis of spectral resolution enhancements, sensitivity optimization strategies, and real-time chemometric frameworks, we consolidate breakthroughs in high-Q metasurfaces, quantum cascade laser systems, cavity-enhanced detection, and adaptive machine learning algorithms. Key findings reveal that while innovations in photonic integration and computational modeling have achieved sub-ppm detection limits and millisecond-scale response times, field deployment remains hindered by environmental instability, calibration drift under dynamic wellbore conditions, and interference from drilling fluids. We further identify that robust sensor designs, autonomous calibration protocols, and edge-compatible algorithms represent critical pathways toward operational reliability. By bridging laboratory-scale progress with practical field constraints, this review establishes infrared spectroscopy not merely as a petroleum diagnostic tool, but as a paradigm for spectroscopic detection in highly disturbed environments. In doing so, it provides a foundational roadmap for advancing IR spectroscopy into a standardized, field-ready platform capable of reliable, real-time chemical sensing across diverse and challenging operational domains.