Neqsim Capacity And Utilization Analysis

Gotchas

• getUtilizationSnapshotJson() is side-effect-free and does not run the model. Run/converge first; the API reports stored/current constraint data, not a fresh simulation.
• Default equipment strategies may use incomplete/default design inputs. Inspect each limit's unit, enabled state, source, sourceReference, dataSource, confidence and validity range. A default/fallback is not vendor or installed capacity evidence.
• Utilization and summary scales differ: CapacityConstraint.getUtilization() and snapshot utilization are fractions; ProcessSystem.getCapacityUtilizationSummary() and BottleneckResult.getUtilizationPercent() are percentages. Avoid comparing them without conversion.
• A no-chart compressor has chart-dependent surge/speed constraints disabled; tests verify that power utilization can still be reported and becomes more loaded as flow rises. Do not interpret absence of a chart constraint as proof of surge margin.
• setValues(...) continues after bad addresses and can partially apply; it returns a successful-write count. setValuesTransactional(...) validates the full batch, applies, runs and rolls back on failure. Previously unreadable input values have no snapshot and are skipped during rollback.
• setVariableValueSafe is for address/bounds diagnostics; setVariableValueValidated invokes typed equipment checks. Neither should be mistaken for an engineering feasibility check or automatic process convergence.
• EmpiricalCarryOverConstraint treats units as labels: caller must align the driver, calibration x-values, carry-over y-values and limit. Values above the last x-point extrapolate linearly using the final segment; evidence must support that extrapolation.
• ProductionRateFitter matches gas rate by scaling total hydrocarbon flow and then adjusts water. If the feed has no water component, water matching is skipped; if no gas phase exists at standard conditions, gas-rate fitting is skipped. GORfitter/MPFMfitter retain total mass flow for their GOR/GVF adjustment; these are not equivalent reconciliation objectives.
• BroydenAccelerator returns direct fixed-point output during its initial delay iterations and does not test convergence itself. Handle damping, bounds, residual criteria and failure recovery in the owning solver.

Validation / benchmarks

• UtilizationSnapshotTest verifies schema version, unit records, process-area labels, duplicate-name qualification, deterministic JSON and chartless-compressor constraint behavior.
• CapacityConstraintMetadataTest verifies unset confidence/validity metadata, inclusive validity boundaries and that metadata does not alter utilization math. CapacityConstraintCurrentValueTest and CapacityConstraintMinimumLimitTest cover sampled values and minimum-bound constraints.
• BottleneckTrackerTest verifies empty results, migration identity, peak percent and JSON keys. Record snapshots only after the corresponding process state is converged.
• ProcessAutomationTransactionalTest verifies successful commits, validation rollback and stable JSON fields. WriteValidatorRegistryTest covers registry dispatch; AutomationDiagnosticsTest covers address/value diagnostics.
• Fit production measurements against independently reconciled plant data. Check gas standard conditions, reference conditions, phase presence and water basis before comparing rates; internal regression tests are not a field-data benchmark.
• When a capacity result drives an operating/design decision, supply a documented basis and compare the limiting condition with vendor, installed, empirical or otherwise approved data. A utilization snapshot is not a safety assessment.

Tie-in bottleneck study on an existing process model

When a satellite field is tied to a host that has a Python-driven process model and a datasheet utilization register:

• Feed the model plan rates by year, not the calibration day: split every manifold stream into oil, gas and water at standard conditions with the model EOS and scale the three parts to the plan rate of the field. Include every manifold of the field (a test-separator manifold carried 0.96 MSm3/d gas and was missed once). Check that the standard volumes of the feeds sum to the PDM facility rates before running years.
• Map the satellite fluid into the model pseudo-components (light ends by name, cuts by molar-mass interpolation, moles and mass conserved), check GOR and stock-tank density in the model EOS, and mix it into the intended header with an adiabatic mixer.
• Run annual-mean and p90-day rates (PDM p90 over mean is 1.17-1.21 for oil, gas and water on a North Sea host); annual means hide the exceedances.
• Keep surge and minimum-continuous-flow rows apart from capacity rows; they are turndown indicators.
• Fit linear responses per (unit, metric), never per unit: the binding metric of a vessel can switch (water to oil) when the feed changes. Verify with a run at twice the satellite rate. The multiplier at which a unit reaches 100 % gives the ullage.
• Units outside the model (produced water, water injection, flare) get a separate screen against demonstrated peaks and any STID design case, labelled as such.
• Budget the run time: low-flow years can take 15-60 minutes per case or not converge when swing compressors idle; run jobs as resumable parallel processes and write one result line per point.

Related skills

• neqsim-capacity-increase-screening — turns the constraint map into ranked lever ideas (wells, subsea, topside), an idea register and a maturation pipeline.
• neqsim-agentic-process-optimization — adjustable process inputs, convergence gates, trial feasibility and objectives.
• neqsim-optimization-and-doe — optimizer families, DoE, sweeps, Pareto and uncertainty.
• neqsim-controllability-operability — operating envelopes, turndown and loop response.
• neqsim-process-modeling — process construction and converged process results.
• neqsim-model-calibration-and-data-reconciliation — measured data quality, calibration and residual analysis.
• neqsim-production-optimization — production surveillance, rate allocation and profile fitting.
• neqsim-operational-risk-and-safety-validation — safety-system scenario interpretation and review boundaries.