Real outcomes from leading energy companies: faster workflows, better decisions and measurable ROI—delivered in days, not months.
A leading energy company needed to reprocess well data across their largest field—4,700 wells—to update interpretations and support new drilling decisions.
Wellbore.AI's parallel processing engine handled the entire dataset in 6 minutes, running QC, depth matching and basic interpretation workflows automatically.
What would have taken weeks with legacy tools was completed in under 10 minutes. The team could immediately review results and make field development decisions.
A leading energy company needed to build a volumetric mineralogical model for a field in the Persian Gulf. Standard software workflows typically take a month.
Wellbore.AI's automated volumetric inversion algorithm processed logs, tuned models against core data and generated porosity, saturation and facies results in a single day.
From raw logs to validated volumetric model in 24 hours—30x faster than traditional methods. The model was immediately used for reserve estimation and drilling planning.
An operator with 50-year-old producing assets needed to find missed reserves across 1,500 legacy wells. Traditional reprocessing would take months and might miss subtle patterns.
Wellbore.AI's generative AI workflows reprocessed all 1,500 wells in 4 days, identifying previously overlooked pay zones and suggesting new completion strategies.
Successful identification of additional reserves led to a full software purchase. The operator now uses Wellbore.AI as their primary well data platform.
A greenfield project needed lithofacies predictions across multiple wells to guide drilling and completion decisions. Manual interpretation would take weeks.
Wellbore.AI's built-in ML algorithms trained on available logs and core data, delivering lithofacies forecasts across the field in a single day.
70%+ accuracy validated against core measurements. The predictions were immediately used for well planning, reducing uncertainty and accelerating development timelines.
