Spatiotemporal Modelling of Groundwater Contamination from Oil-Drilling Waste Using Release Rates, Hydrogeological Parameters, Leaching Tests and Monitoring-Well Data

Oil-drilling residues may release dissolved salts, metals and petroleum-associated constituents into shallow groundwater, yet predictions are highly sensitive to source histories and aquifer properties. This study develops a finite-source, two-dimensional, vertically mixed advection–dispersion–reaction formulation for five modelled analytes (Ba, Pb, total Cr, TPH and Cl), and integrates synthetic batch-leaching trajectories, a 14-well synthetic network, and seven monitoring campaigns over 365 days. The computational experiment assumes hydraulic conductivity of 2.5 m d⁻¹, gradient 0.006, effective porosity 0.28 and saturated thickness 18 m. Source masses, rate constants and partition coefficients are scenario assumptions, not empirical estimates. Gaussian Green-function convolution with daily mass-release pulses produces simulated breakthrough curves and day-365 plume maps. Reproducibility is demonstrated through supplied Python/CSV files and seven executed deterministic scenarios. The results identify the effects of finite mass depletion, transport retardation, and groundwater velocity on the timing and distribution of concentration. Synthetic observation perturbations permit a numerical consistency check but do not constitute external calibration. The study offers a transparent methodological prototype for future site-specific inference using measured leaching, hydraulic head and groundwater chemistry data.