Relative permeability functions describe:

Effective permeability for each phase as a function of saturation

Absolute permeability of each rock type

A “fully implicit” scheme solves:

Both pressure and saturation simultaneously at each time step

Pressure explicitly, saturation implicitly

Only the continuity equation implicitly

In compositional simulation, flash calculations are used to:

Determine phase splits based on PVT data

A finer grid resolution generally:

Increases computational cost but improves accuracy

The “streamline” simulation method primarily traces:

Paths of minimal travel time for fluid particles

Aquifer modeling in reservoir simulation often uses:

Analytical connections (e.g., Fetkovich model)

The Courant–Friedrichs–Lewy (CFL) condition relates to:

Time-step stability in explicit schemes

In black oil simulators, solution gas‐oil ratio (Rs) is a function of:

Both pressure and temperature via PVT tables

Well modeling in simulators commonly uses:

Peaceman’s well‐block model

Mobility of a phase is defined as:

Relative permeability / viscosity

Viscosity × relative permeability

Grid upscaling is needed to:

Ensure fine‐scale heterogeneity is represented in coarser models

Downscale from regional to field models

Convert two-phase to three-phase simulation

Eliminate the need for time stepping

Capillary pressure is often modeled as a function of:

Pore throat radius and interfacial tension

Phase compressibility affects:

Pressure solution and fluid expansion effects

Anisotropic permeability means:

Different permeability horizontally and vertically

Permeability is the same in all directions

Tracer simulation in reservoirs is used to:

Track fluid movement and estimate sweep efficiency

History matching adjusts:

Model parameters (e.g., permeability, porosity, relative‐permeability curves) to fit production data

The primary disadvantage of explicit schemes is:

Time-step restrictions for stability

Secondary recovery methods (water-flood) are simulated by:

Three‐phase black oil equations with injection wells

Polymer flooding simulation requires:

Modeling of polymer adsorption and viscosity changes

Gas injection (EOR) simulation often uses:

Compositional or miscible models

“Grid sensitivity analysis” tests the effect of:

Grid resolution on simulation results

Numerical dispersion is a problem primarily in:

Explicit schemes and low‐order discretization of advective terms

Dual porosity models simulate:

Fractured reservoirs with matrix/fracture exchange

Well productivity/injectivity in a grid block

Rate‐transient analysis (RTA) complements simulation by:

Interpreting production data trends to estimate reserves

Solving Darcy’s law analytically

In thermal simulation (steam), you must solve:

Coupled mass and energy balances

A “pilot point” method in history match uses:

Parameterization of permeability at scattered points for optimization

CO₂ sequestration simulation requires:

Compositional modeling with CO₂ solubility and phase behavior

In a reservoir simulator, “grid block continuity equation” enforces:

Mass balance for each phase in each block

Vertical heterogeneity is often addressed by:

Layered grid or transmissibility multipliers

Capillary end effects can be simulated using:

Special capillary pressure functions and fine grid near wells

Ignored in compositional models

The “Newton–Raphson” method is used to:

Solve nonlinear algebraic equations in fully implicit schemes

Parallel processing in reservoir simulation:

Speeds up large model runs by distributing grid blocks across CPUs

Replaces the need for history match

A simulation “case deck” typically includes:

Grid, properties, fluid data, well/control schedules

Perforation skin factor in well modeling:

Represents additional near‐wellbore resistance (positive) or enhancement (negative)

Streamline vs. Finite‐Difference simulation:

Streamlines trace flow paths and can be faster for certain scenarios

Streamline solves pressure explicitly

Streamline cannot handle heterogeneity

Finite‐difference only for single‐phase

Sensitivity analysis in simulation is used to:

Identify critical model parameters affecting results

Solve Newton–Raphson equations

Simulation convergence criteria often monitor:

Maximum pressure and saturation residuals below a tolerance

Reservoir Simulation MCQs

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MULTIPLE CHOICE QUESTION

45 sec • 1 pt

Which equation is the fundamental flow law used in reservoir simulation?

Bernoulli’s equation

Darcy’s law

Navier–Stokes equation

Fick’s law

MULTIPLE CHOICE QUESTION

45 sec • 1 pt

In Darcy’s law, permeability has units of:

Pa·s

m²/s

Darcy or milliDarcy

kg/m³

MULTIPLE CHOICE QUESTION

45 sec • 1 pt

The “black oil” model in reservoir simulation assumes:

Constant composition of all phases

No gas phase exists

Three pseudo-components: oil, gas, water

Thermal effects dominate

MULTIPLE CHOICE QUESTION

45 sec • 1 pt

What does IMPES stand for in reservoir simulation?

Implicit Pressure Explicit Saturation

Implicit Porosity Explicit Stress

Instant Pressure Equilibrium Solution

Incompressible Phase Energy Solver

MULTIPLE CHOICE QUESTION

45 sec • 1 pt

In a typical finite-difference simulation grid, a “cell” represents:

A wellbore segment

A discrete volume of rock/fluid

The whole reservoir

Only the aquifer

MULTIPLE CHOICE QUESTION

45 sec • 1 pt

Upstream weighting in finite-difference discretization is used to:

Improve time accuracy

Guarantee numerical stability for convective terms

Enforce boundary conditions

Model capillary pressure

MULTIPLE CHOICE QUESTION

45 sec • 1 pt

The primary purpose of history matching is to:

Generate PVT correlations

Calibrate model parameters to match production data

Optimize well placement

Calculate Darcy flux

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Reservoir Simulation MCQs

Which equation is the fundamental flow law used in reservoir simulation?

In Darcy’s law, permeability has units of:

The “black oil” model in reservoir simulation assumes:

What does IMPES stand for in reservoir simulation?

In a typical finite-difference simulation grid, a “cell” represents:

Upstream weighting in finite-difference discretization is used to:

The primary purpose of history matching is to:

Relative permeability functions describe:

A “fully implicit” scheme solves:

Which boundary condition represents no flow across a boundary?

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