Autonomous inflow control
AICD simulation for oil well completions
AICDs (Autonomous Inflow Control Devices) respond to the fluid phase arriving at their inlet. Predicting that response in a real horizontal oil well means modelling the annulus flow and segregation pattern that governs what each device actually sees. Flowpro Insight resolves both.
What Insight does for AICD studies
AICD simulation workflows
FD-AICD design and sizing
Simulate fluidic diode AICD performance across your reservoir pressure and phase-ratio envelope. Insight resolves the annulus velocity field entering each device, so you see how upstream segregation changes the fluid composition each FD-AICD actually responds to.
RCP-AICD rate control
Model rate-controlled production AICDs in horizontal and extended-reach wells. Predict when high-permeability zones start to dominate and how the RCP response limits water cut evolution over the production life.
Compare AICD types on the same well
Run the same reservoir, completion trajectory, and production boundary conditions with FD-AICD, RCP-AICD, or combinations. Direct head-to-head performance comparison using identical physics assumptions.
Validate against chemical-tracer PLT
If you have tracer data from a producing well, Insight's tracer analysis capability can close the loop: match simulated zonal allocation to measured tracer returns to calibrate AICD response models for the next infill well.
Why it matters
The physics that makes AICD simulation hard
The standard reservoir simulator workflow treats the annulus around an AICD as a single point. In reality, the annulus is where gravity separates oil, water, and gas before any fluid reaches the device. Over the hundreds of metres between production packers, even a fraction of a degree of well deviation drives complete phase segregation. The AICD on the high side of the pipe sees a different fluid than the one on the low side, in the same joint, at the same time.
Legacy mixed-flow simulation is a step up from a bare reservoir simulator in one respect: the steady-state wellbore network solver computes friction along the completion. But it still assumes complete mixing at every junction and reduces the annulus to a one-dimensional pipe. Every AICD response is evaluated on the averaged fluid, not on what the device actually sees. That is why AICD performance modelled on mixed-flow tools routinely overstates water-cut control and understates the phase-specific response that makes autonomous devices worth installing.
Insight resolves the annulus flow field with CFD at the single-joint scale, upscales it to the full completion, and makes the result runnable in your reservoir simulator. The AICD response you predict on paper matches what the device does in the well.
Read more on annulus phase segregation →FAQ
Frequently asked questions
Can standard reservoir simulators model AICD behaviour accurately?
Not on their own. AICDs respond to the fluid phase arriving at each device, and that composition is determined by annulus phase segregation, which simulators like Eclipse and T-Navigator treat as a single flow node. Insight runs CFD at the single-joint scale, captures segregation, and exports upscaled valve tables your simulator can use.
Which AICD types does Insight model?
Fluidic Diode AICDs (FD-AICD), Rate-Controlled Production AICDs (RCP-AICD), and the density-based device family. Custom valve response curves can be imported from manufacturer data sheets or CFD.
How does simulation account for water or gas breakthrough timing?
Insight couples transient annulus segregation with the reservoir drive, so the fluid composition arriving at each AICD evolves as the reservoir depletes. You see the moment water or gas reaches a given device and how the AICD response shifts the production profile.