A persistent simulation maintains an authoritative physical state and continuously recomputes system response as conditions, controls and actions change.
RuntimePhysics™ →IADC ADVANCED RIG TECHNOLOGY 2026 · AUSTIN · AUGUST 25
High-fidelity simulation for time-dependent drilling risk.
A technical recap of Samer Shiblaq’s IADC ART 2026 presentation on using high-fidelity simulation to study drilling risk and validate digital-twin-driven drilling and well-control workflows.
Presented in the IADC ART Digital Twin session. View the IADC program ↗
THE PRESENTATION
Using High-Fidelity Simulation to Study Time-Dependent Drilling Risk Behavior
& Validating Digital Twin–Driven Drilling and Well Control Workflows Using High-Fidelity Simulation
CLEAN DEFINITION
What is high-fidelity drilling simulation?
High-fidelity drilling simulation is a physics-based representation of the well and drilling system that calculates changing system behavior from defined physical inputs, operating conditions and control actions. The model maintains the consequences of prior events so pressure, flow, mechanical state and operational risk can evolve through time rather than resetting at each calculation.
A digital twin connects a governed representation of the asset or operation to verified or live information. Runtime simulation supplies the causal physics used to calculate what that changing state means.
Digital Twin Architecture →THE PHYSICS BEHIND THE CLAIM
Drilling risk is not a snapshot.
Many drilling problems become dangerous because conditions accumulate. The sequence matters: what happened minutes or hours earlier changes what the well does next. A runtime model preserves that history and resolves the coupled response.
01
Stuck pipe prediction & risk
Mechanical loading, cuttings accumulation, differential pressure, wellbore contact, circulation and prior movement can combine into a changing risk state. Simulation exposes the causal chain instead of reducing the event to one indicator.
Drilling simulation →02
Hole cleaning modeling
Cuttings transport changes with flow rate, inclination, ROP, string rotation, rheology and time. Beds develop and clear progressively, so the history of circulation and drilling activity matters.
Explore drilling workflows →03
ECD management
Annular pressure loss and hydrostatic behavior evolve with fluid properties, flow, geometry, temperature and transient operations. Runtime calculation keeps the pressure window connected to what the crew and control system are actually doing.
MPD & ECD workflows →04
Torque & drag modeling
Axial load and torque emerge from distributed contact, friction, string configuration, well geometry and motion. The mechanical state changes as the string moves, rotates and interacts with the wellbore.
Mechanical drilling physics →05
Surge & swab
Pipe movement displaces fluid and produces transient downhole pressure response. Those effects matter most when operating margins are narrow and when tripping behavior must be evaluated as a sequence rather than a static case.
Transient operations →06
Well control simulation
Influx, migration, compressibility, phase behavior, shut-in response and circulation remain part of one continuous well state. Actions taken at surface propagate through the same active model.
Well Control Simulator →ARCHITECTURAL DISTINCTION
Planning models answer a case. Runtime models carry the state forward.
Evaluate defined conditions
- Known input set
- Defined operating case
- Useful for design and comparison
- Often recalculated as a new case when assumptions change
→
Maintain the evolving system
- Persistent well and equipment state
- Live changes and control actions accepted during execution
- Prior actions remain in the current condition
- Physics continuously recomputed from the active state
That distinction becomes increasingly important when simulation is connected to live data, actual PLC/HMI logic, automation, DWOS workflows or a digital twin.
FROM MODEL TO OPERATIONS
One physics layer. Three ways to use it.
Rehearse consequence.
Put crews inside a continuously evolving well state where decisions, timing and recovery actions have physical consequences.
Training applications →Evaluate the forward path.
Use verified well data and runtime simulation to examine planned-versus-current conditions, operational windows and scenario branches.
DWOS →Test systems before the well does.
Connect real control logic and automation to RuntimePhysics™ so commands are tested against a dynamic physical system before deployment.
HIL & Automation →RELATED TECHNICAL QUESTIONS
The problem language engineers actually use.
TURN THE CONVERSATION INTO A TESTABLE SCOPE
Bring us a well, workflow or automation system.
Describe the operation, available data, interfaces and deployment needs. Endeavor will map the requirement to the appropriate simulation, integration and deployment scope.