Train flow check execution and interpretation under realistic wellbore and surface noise.
Request Demo >Aligned to IADC and IWCF driller-level outcomes, this simulation improves confidence in flow checks by exposing operators to realistic ambiguity. Better interpretation reduces unnecessary shut-ins while preventing delayed response to true influx events.
Flow Check Timing
Practice correct flow check duration and execution steps.
Residual Flow Interpretation
Distinguish trapped flow from active influx.
Noise Discrimination
Separate surface noise from wellbore flow signals.
LIVE STATE EVOLUTION
Deploy on-prem, private cloud, or isolated networks. Supported hardware tiers: X1/X2/X3 simulators, Laptop, and Online. Teams can also rent the Endeavor Experience Center for executive demos, assessments, or multi-crew exercises. Typical session: configure scenario parameters, run the study and or simulation sessions, review KPIs, and export results.
Yes. Import well data via WITSML 1.4/2.0 or CSV/JSON, or ingest parameters directly through DOT. Any input from the field—well schematics, logs, tool states, rates/pressures—instantiates a real digital twin of the well for hyper-realistic training and operational planning (Drilling Well on Simulator). APIs and versioned adapters are customized upon request.
The model simulates flow checks and static confirmation by coupling flow observation, pressure response, and surface noise rather than simple pass/fail checks. Accuracy is strongest for training correct execution timing and distinguishing residual flow from true influx. Where ambiguity or surface interference dominates, outcomes are bounded with sensitivity ranges instead of a single binary result.
Inputs typically include the operation configuration—well profile or trajectory, fluid properties, equipment and tool states, boundary conditions, and rate or pressure schedules. Outputs and KPIs capture the scenario’s hydraulic, mechanical, and fluid responses, including pressure and flow behavior across the system, evolving fluid properties, and equipment performance. Results also define , event detection, and time-based cause-and-effect responses to operator actions. Detailed datasets, replays, and assessment metrics can be exported for engineering review, training records, or planning documentation
Enterprise deployments support role-based access control, secure authentication, and encryption of data in transit and at rest. The platform can be deployed on-premise, in private cloud, or in an isolated environment(s) to meet operational and regulatory requirements. Support is provided under defined SLA tiers, with controlled release management and long-term support options available for production environments.