2021
Assessment of groundwater well vulnerability to contamination through physics-informed machine learning
Soriano M, Siegel H, Johnson N, Gutchess K, Xiong B, Li Y, Clark C, Plata D, Deziel N, Saiers J. Assessment of groundwater well vulnerability to contamination through physics-informed machine learning. Environmental Research Letters 2021, 16: 084013. DOI: 10.1088/1748-9326/ac10e0.Peer-Reviewed Original ResearchWell vulnerabilityLarge-scale problemsPhysics-informed machineGroundwater risk assessmentGroundwater contamination riskMetamodel predictionsShallow aquiferGroundwater resourcesChemical signaturesScale problemsAnthropogenic activitiesContaminant releaseContaminant sourcesQuality recordsNatural gas productionMarcellus ShaleHigh spatial resolutionUnconventional oilHousehold wellsNortheastern PennsylvaniaFuture impactGas developmentGeographic information systemNecessary numberPB model
2020
Evaluating Domestic Well Vulnerability to Contamination From Unconventional Oil and Gas Development Sites
Soriano M, Siegel H, Gutchess K, Clark C, Li Y, Xiong B, Plata D, Deziel N, Saiers J. Evaluating Domestic Well Vulnerability to Contamination From Unconventional Oil and Gas Development Sites. Water Resources Research 2020, 56 DOI: 10.1029/2020wr028005.Peer-Reviewed Original ResearchPhase contaminationUnconventional oilSingle calibrated modelAqueous phase contaminantsWell vulnerabilityGas developmentGas development sitesCapture zoneMatrix hydraulic conductivitySetback distanceProbabilistic capture zonesHydraulic fracturingRatio of fractureMatrix conductivityHorizontal drillingSurface spillsFlow pathsCalibrated modelHydraulic conductivityPad locationsTransport timescalesDomestic groundwater wellsConductivityGroundwater contaminationModel parameters