We propose a generic, modular framework for methane emission event detection, localization, and quantification on oil and gas production sites that uses concentration and wind data collected by point-in-space continuous monitoring systems. The framework uses a gradient-based spike detection algorithm to estimate emission start and end times (event detection) and pattern matches simulated and observed concentrations to estimate emission source location (localization) and rate (quantification). We test the framework on a month of non-blinded, single-source controlled releases ranging from 0.50 to 8.25 hours in duration and 0.18 to 6.39 kg/hr in size. All controlled releases are identified and 82% are localized correctly. 5.5% of predicted events are false positives. For emissions < 1 kg/hr, the framework underestimates by -3.9% on average, with 90% of rate estimates within a percent difference of [-74.9%, 195.2%] or a factor difference of [-4.0, 3.0] from the true rate. For emissions > 1 kg/hr, the framework overestimates by 4.3% on average, with 90% of rate estimates within a percent difference of [-49.3%, 78.8%] or a factor difference of [-2.0, 1.8] from the true rate. Potential uses for the proposed framework include near real-time alerting for rapid emissions mitigation and emission quantification for data-driven inventory estimation on production sites.