Fontaine dbMax Solutions, Inc.
Hydrogeologic understanding. Practical analytical tools.
Selected Projects & Experience
Groundwater modeling, applied machine learning, and supporting data solutions for hydrogeologic decisions.
These examples include current work at Fontaine dbMax Solutions and selected assignments from Russ Fontaine's previous employers. Each entry identifies the organization associated with the work.
Featured development study • Fontaine dbMax Solutions
Hybrid Machine Learning for Groundwater Plume Characterization and Monitoring Design
Developing and evaluating a workflow that combines monitoring observations, groundwater flow information, analytical transport features, and kernel ridge regression to characterize contaminant plumes and identify promising locations for additional monitoring.
Controlled Test Bed
A synthetic Fountain Creek aquifer test bed provides a known reference plume for comparing predictions across three monitoring periods, including migration after source cutoff.
Evaluation & Monitoring Design
Leave-one-location-out validation evaluates predictions at withheld monitoring locations. Spatial comparisons and information-value mapping help assess plume interpretation and prioritize candidate monitoring wells.
Current status: Development and evaluation are ongoing using a controlled synthetic test bed; potential field applications are under consideration.
Ask About the Study →Groundwater Modeling & Hydrogeologic Experience
Remediation & contaminant transport
Groundwater Remediation & Fate and Transport Modeling
Experience spanning groundwater remediation evaluation, hydrogeologic interpretation, numerical modeling, and technical review at industrial and mining sites.
At CDM Federal Programs Corporation, Russ evaluated groundwater remediation using numerical models at sites in New Jersey, Oklahoma, California, Colorado, Arizona, Montana, and Texas. His work included MODFLOW, MT3D, and finite-element DYNFLOW/DYNTRACK models. He also provided technical oversight for EPA Region VIII.
At Geomega, he evaluated groundwater remediation at mining and industrial sites through hydrogeologic interpretation and numerical modeling, including MODFLOW and FEFLOW, supported by calibration using PEST.
Application: Evaluate groundwater conditions, contaminant migration, and remediation approaches through model development, interpretation, and review.
Experience at CDM Federal Programs Corporation and Geomega.
Regional modeling & technical leadership
Resolution Copper Mine, Arizona
Managed a multidisciplinary team developing a regional numerical groundwater model and pre-feasibility report for the proposed block-cave mine near Superior, Arizona.
Integrated well, geologic, and groundwater data into a project database and MODFLOW-SURFACT model; calibrated the model and evaluated mine-development scenarios.
The project received a Rio Tinto award for outstanding technical performance.
Application: Assess potential groundwater impacts to support mine planning and permitting.
Employer: Schlumberger Water Services. Client: Rio Tinto.
Mine dewatering & pit-lake evaluation
South Pipeline Mine, Nevada
Developed a regional MODFLOW-SURFACT groundwater model to assess the effects of dewatering for the South Pipeline open-pit mine.
Organized well and geologic data in a project database and incorporated a pit-lake package to evaluate lake development after mining.
Application: Support permitting and mine development, including evaluation for the Environmental Impact Statement.
Employer: Geomega. Client: Barrick.
Uncertainty analysis, well testing & injectivity
Injection-Well Evaluation & Modeling
McKittrick Oil Field, California
Developed a stochastic numerical injection model to evaluate pressure increases. Monte Carlo simulations sampled permeability and porosity, and alternative injection-well locations were evaluated for planning.
Employer: Geomega. Client: Chevron.
Cameco Injection Wells, Wyoming
Designed a test program for five wells near Douglas and managed on-site work. Developed pressure and long-term injectivity calculations, collaborated on pressure-transient interpretation, and managed hydraulic fracturing of the injection zones.
Employer: Schlumberger. Client: Cameco.
Application: Support injection planning and evaluate well performance through modeling and field testing.
Applied Machine Learning & Data Solutions
Machine learning case study
Colorado Groundwater Nitrate Risk Assessment
Developed a regional machine learning case study integrating groundwater observations, geospatial datasets, and hydrogeologic predictors into a training dataset.
Built and tuned an XGBoost model, generated spatial prediction rasters, and used SHAP feature-attribution analysis to examine predictor contributions.
Application: Explore groundwater nitrate-risk patterns and demonstrate the integration of hydrogeologic data, spatial prediction, and model interpretation.
Organization: Fontaine dbMax Solutions.
Database design & data integration
Louisiana SONRIS Data Conversion
Transformed Louisiana Department of Natural Resources SONRIS well and injection data into a normalized database model for the B3 Insight platform.
Used well-data expertise and SQL transformations to reconcile duplicate records, interpret table relationships, and integrate information from a complex source dataset.
Application: Provide a consistent data foundation for water-management and injection-well evaluation tools.
Employer: B3 Insight.
Let’s Discuss Your Groundwater Project
We welcome collaboration on groundwater modeling, applied machine learning, and supporting software and data workflows.