Abandoned and orphaned oil and gas wells constitute a persistent environmental liability due to long-term degradation of wellbore integrity, enabling methane leakage and subsurface contaminant migration. This study develops a comprehensive environmental risk assessment framework integrating refined well inventories, geospatial analysis, methane emission modeling, hydrogeological simulations, and machine-learning prediction. An expanded inventory of 225,287 wells 37 percent higher than prior estimates was derived through regulatory reconciliation and historical data mining. Spatial analysis identified dense clusters of legacy wells intersecting shallow aquifers and populated regions. Methane emission modeling, supported by emission-factor calculations and Monte Carlo simulations, yielded annual emissions ranging from 0.86 to 1.12 kilotons, with undocumented wells contributing an additional 8 percent to total leakage. Hydrogeological modeling demonstrated that casing and cement deterioration can facilitate the vertical migration of saline brines and volatile contaminants, increasing groundwater vulnerability. Machine-learning prediction revealed significant undocumented well densities, elevating estimated high-risk classifications from 14 to 25 percent and increasing population exposure estimates by approximately 150,000 individuals. The integrated assessment confirms that legacy wells are material contributors to greenhouse gas emissions and groundwater contamination risk. Findings underscore the need for expanded inventories, risk-based remediation, and regulatory frameworks that explicitly incorporate legacy infrastructure into climate and groundwater policy.
Nwaloka chibunna Johnkennedy (Wed,) studied this question.