Daily drilling reports (DGRs) are a goldmine of operational insights, but they often arrive as unstructured, inconsistent PDFs that are rarely analyzed in real time.
SeisSense™ now leverages natural language processing (NLP) and AI agents to extract, classify, and monitor drilling KPIs—turning free-form reports into structured intelligence.
What Gets Automated
- Parsing depth-wise sections, mud logs, and BHA info: Extracts technical drilling details from scattered formats into organized datasets.
- Extracting KPIs like ROP, torque, WOB, and bit wear: Automates real-time performance monitoring directly from the daily reports.
- Detecting stuck pipe, kicks, and lost circulation patterns: AI flags abnormal operational events using learned drilling behavior profiles.
- Flagging deviations and generating auto-summaries: Enables shift supervisors and engineers to focus only on exceptions and alerts.
- Visualizing KPI trends in rig dashboards: Displays time-series performance metrics in intuitive, customizable charts.
Real Deployment: East Coast India
- A regional operator integrated the SeisSense™ DrillOps module across more than 30 wells.
- Reports that previously took over 3 hours per well to process manually are now auto-generated in under 5 minutes.
- KPI extraction and event detection are now standardized, enabling faster review and better field-level decisions.
SeisSense™ turns scattered drilling reports into high-value intelligence offering real-time visibility into operations, risks, and performance, all without manual intervention.
Key Takeaways
- Transforms unstructured DGRs into structured drilling insights using NLP and AI.
- Provides early warnings for non-productive time (NPT) risks by detecting patterns proactively.
- Seamlessly integrates with WITSML, WellView, and other industry-standard formats.