Advancing gas flaring mitigation: A comprehensive review of progress and future directions

This is the authors' abstract. We don't add key points for this paper.

Gas flaring, a persistent environmental challenge within the petroleum industry, significantly contributes to global greenhouse gas emissions and represents a substantial loss of energy and economic value. Despite extensive research into flare gas recovery and mitigation, the existing literature lacks a comprehensive assessment that integrates scientometric analysis with a systematic evaluation of quantitative optimization methods. This study bridges this gap by integrating a four-decade scientometric review (1981–2024) of 359 Scopus-indexed articles with a systematic review of 32 mathematical optimization studies published from 2014 to 2024. The scientometric analysis reveals an 8.47% annual growth rate in publications and identifies key research hubs across several global regions. Collaboration networks indicate robust research clusters in North America, Asia, and Africa. Keyword and thematic analyses demonstrate increasing scholarly focus on flare gas recovery, emissions reduction, and sustainability. The systematic review categorizes the primary quantitative approaches into multi-objective or multi-period optimization, integer programming, and inverse optimization, in addition to other mathematical techniques. Genetic algorithms (GAs) are the most frequently employed method. Inverse Data Envelopment Analysis (IDEA) presents a promising approach for modeling flaring reductions and pinpointing optimal gas utilization strategies. The findings highlight methodological gaps, specifically the limited application of integer programming and the absence of stochastic inverse-optimization frameworks. These gaps offer clear directions for future research to advance the global zero-routine-flaring (ZRF) agenda by 2030.