Groundwater‐quality hazards of methane leakage from hydrocarbon wells: A review of observational and numerical studies and four testable hypotheses

Abstract

Methane leakage from hydrocarbon wells plays an important role in the groundwater‐quality impacts of hydrocarbon development and presents a more likely hazard than hydraulic fracturing or formation fluids. Methane released from contaminated water wells has been linked with combustion risks and degraded water quality. Potentially, methane can serve as a precursor to other fluids associated with hydrocarbon extraction, such as volatile organics. In this review, we surveyed studies relating to contamination of drinking‐water aquifers by methane gas from leaking hydrocarbon wells. Challenges associated with linking methane in groundwater to hydrocarbon extraction are identified, highlighting the need for groundwater‐quality and well‐integrity databases. Science‐based policy recommendations are made, including deeper surface casings and greater cement coverage for wells with deviated wellbores, remediation of faulty abandoned wells, and increased gas‐migration monitoring. We suggest four hypotheses to quantify risks to groundwater quality from methane leakage. First, differentiation between thermogenic methane occurring in groundwater due to natural migration and thermogenic methane present due to hydrocarbon development can be used to alleviate the need for baseline measurements of methane in groundwater. Second, methane newly discovered in freshwater aquifers is unlikely to have originated from leaks beginning decades ago. Third, pertaining to the zone separating methane leakage from groundwater, relative permeability will have a larger impact on plume diameter than heterogeneity in intrinsic permeability. Fourth, thermogenic methane in groundwater will serve as a precursor to benzene, toluene, ethybenzene, and xylene (BTEX) under conditions where methane and BTEX coexist in a hydrocarbon reservoir and leakage is transported primarily in the aqueous phase. This article is categorized under: Engineering Water > Sustainable Engineering of Water Science of Water > Water Quality

Competition for shrinking window of low salinity groundwater

“…Factors, such as the permeability of the 'intermediate zone' between the oil/gas reservoir being produced and shallow aquifers [43] and the presence of conduits (e.g. poorly completed or abandoned oil and gas wells) to near-surface environments [44], are important considerations that have yet to be characterized comprehensively.…”

Modeling Gas Migration, Sustained Casing Pressure, and Surface Casing Vent Flow in Onshore Oil and Gas Wells

“…Gas migration into shallow freshwater aquifers through faulty oil and gas wellbores is a decades‐old issue (e.g., Denver Post Editorial Board, ; Harrison, , ) that threatens groundwater in regions with oil and gas development and has recently reemerged as major concern in the United States in light of the expansion of unconventional oil and gas drilling (Brownlow et al, , ; Darrah et al, ; Davies et al, ; Dusseault & Jackson, ; Ingraffea et al, ; Jackson et al, ; Jackson, ; Lackey et al, ; Llewellyn et al, ; Rice, Lackey, et al, ; Sherwood et al, ). Leaked gas from a wellbore flaw or an improperly isolated gas‐bearing formation can migrate vertically along a well through the annuli between the well casings (steel pipes), if the annular cement is faulty (Figure b) or if the annulus is left uncemented (Figure c).…”

Moving beyond forensic monitoring to understand and manage impacts of hydraulic fracturing for oil and gas development

“…Similar studies have begun to appear for identifying methane leakage from shale gas development, using either conceptual or numerical models to assess transport pathways and geochemical outcomes (17,18). Models and monitoring programs are often synergistic: Monitoring is necessary to calibrate, verify, and refine the conceptual and parametric representation of the subsurface embodied by the model, while the modeling helps to identify the sampling needs that are most important for reducing the uncertainties that matter most for both ongoing model improvements and management decisions.…”