Crude assay management software helps refineries organize, validate, reconstruct, and apply crude oil assay data throughout the engineering workflow.

It converts laboratory measurements into a consistent crude oil characterization that can support refinery planning, refinery scheduling, crude blending, LP optimization, and process simulation.

Crude oil assays may come from different laboratories, crude suppliers, published databases, or historical refinery records. These sources often report different boiling cut points, properties, units, and laboratory methods.

Some assays may also omit properties required by a particular engineering model. These differences make direct comparison difficult and frequently require data reconciliation before the assay can be used reliably.

CUTS uses a proprietary multidimensional regression method that evaluates relationships between multiple reported properties simultaneously.

Instead of estimating each missing value in isolation, CUTS reconstructs a complete and internally consistent property distribution across the crude’s boiling range while maintaining agreement with the available laboratory information.

Pseudo-components are defined boiling-range fractions used to represent groups of hydrocarbons with similar characteristics.

Crude oil contains thousands of individual compounds, so representing each compound separately would be impractical for most refinery models. Pseudo-components provide a detailed but computationally manageable representation.

CUTS generates contiguous 10°C cuts with calculated properties across the entire crude boiling range.

Crude recutting is the calculation of petroleum fractions using boiling cut points that differ from those reported in the original laboratory assay.

Because CUTS creates a continuous crude characterization, engineers can calculate the yield and properties of virtually any required fraction without altering or rebuilding the original assay.

Yes. CUTS is specifically designed to process incomplete, inconsistent, or differently formatted crude oil assays.

Using data reconciliation and multidimensional regression, it transforms the available measurements into a complete and internally consistent crude oil characterization covering the entire boiling range.

The reliability of the resulting characterization still depends on the quantity and quality of the available input data. Software cannot turn severely deficient laboratory information into certainty, but it can create the most coherent technical representation supported by the data.

A complete characterization can support feedstock evaluation, crude selection, refinery planning, refinery scheduling, crude blending, LP optimization, and process simulation.

Using the same characterization across these activities reduces discrepancies between departments and limits the need to prepare separate versions of the crude data for different engineering applications.

Engineering results are only as reliable as their input data. An internally consistent assay keeps property relationships coherent across the full boiling range.

This helps reduce conflicting results between studies and improves confidence in refinery planning, simulation, optimization, blending, and crude evaluation.