How to Solve Crude Compatibility Challenges in Refining

Apr 24, 2025   Written by Asok Tharanivasan

Thermodynamic modeling predicts blend stability and minimizes equipment damage while optimizing operations

Global crude oil demand is projected to hit 103 million barrels per day by 2025, according to the International Energy Agency. To meet this demand efficiently, you’re likely turning to economically attractive "opportunity crudes" from various global sources.

But there's a catch: these crudes bring substantial refining challenges, especially asphaltene precipitation - a top cause of fouling and equipment damage, which causes significant operational inefficiencies. Here's how you can effectively predict crude compatibility and optimize your blending decisions using thermodynamic modeling.

Understand Crude Compatibility Problems

What exactly are "opportunity crudes," and why should you care? Opportunity crudes offer cost savings, but their unpredictable compositions can significantly disrupt your refinery processes.

Why is asphaltene precipitation problematic? Asphaltenes, complex and heavy molecules, can separate from your crude blends depending on fluid composition, temperature, and pressure. Additional factors such as residence time, equipment, configuration, chemical reactions, and high process temperatures can cause these molecules to precipitate, resulting in fouling, equipment damage, and costly operational setbacks. You need a reliable method to manage asphaltene instability and maintain efficiency.

Recognize Limits of Current Methods

Traditionally, you might rely on standardized titration tests to assess crude compatibility. These tests determine an onset point - the minimum amount of titrating solvent required to initiate asphaltene precipitation. The onsets are reported as P-Values or as solubility blending and insolubility numbers. However, these traditional methods fall short for two key reasons:

  • Impracticality Testing every potential blend combination isn't realistic due to time and costs.
  • Inaccuracy Simple averaging doesn't accurately capture the complex, non-linear interactions in blended crudes.

These limitations emphasize why you need a predictive tool that seamlessly integrates into your process simulator for efficient planning and operations.

Improve Assessments

Unlike your traditional methods, the Multiflash Crude Compatibility Tool (MFCCT) is a robust thermodynamic framework that accurately assesses crude blends. It considers vapor, liquid, and asphaltene as equilibrium phases and employs the cubic plus association equation of state (CPA-EOS) to accurately predict asphaltene precipitation, as shown in Figure 1. Here's how it works:

Predicted Onsets Graph Figure 1: Predicted onsets compared against the measured onsets for Oil 1 and Oil 2 blends
  1. Input Your Data Enter crude assay with asphaltene content and onset data for source oils.
  2. Easily Analyze Blends Combine your crude assays based on your planned blending proportions.
  3. Determine Blend Properties Perform fluid characterization on the fly and use appropriate mixing rules automatically to determine the blend’s composition and parameters for each source oil without any user intervention.
  4. Get Reliable Predictions: Analyze the blend stream properties to determine compatibility of source crudes, predict asphaltene precipitation, and assess blend stability.

By analyzing a structured blend compatibility index (BCI), you can quickly identify problematic crude combinations and optimize your blending proportions. While BCI may suggest ideal blending orders of source crudes, further data is needed to fully leverage this benefit.

Evaluate Results with BCI

The Blend Compatibility Index (BCI) makes your interpretation straightforward:

  • BCI=0.0 Your blend is completely unstable and therefore incompatible source oils.
  • 0.0 < BCI < 0.7 Potentially incompatible source oils - high operational risk.
  • 0.7 ≤ BCI < 1.0: Potentially compatible source oils - keep an eye out.
  • BCI ≥ 1.0 Your blend is stable and source oils are highly compatible (low risk).

For example, a refinery used MFCCT and reported a high predictive accuracy, allowing confident decision-making and avoiding costly disruptions.

Table blends Table 1: MFCCT predictions of P-Values alongside client data, demonstrating alignment between predicted and actual outcomes

Explore Success Stories

Refiners using MFCCT have experienced substantial improvements, as illustrated in Table 1:

  • High predictive accuracy Validated by more than 40 real-world crude blends, including binary (two-source) and ternary (three-source) blends.
  • Cost reductions Decreased reliance on extensive physical testing, saving on downtime and maintenance.

Gain More Benefits

Thermodynamic modeling helps you beyond basic compatibility checks:

  • Planning and Scheduling Supports crude selection and scheduling to improve flexibility for slate mixes and complementing linear programming models.
  • Crude Storage & Handling Minimizes sludge buildup risks.
  • Processing Optimizes your processes, reduces fouling, and boosts sustainability.

Take Next Steps

Proactively managing crude compatibility with thermodynamic modeling is more than just helpful - it's essential for maintaining efficiency and profitability.

  • Notice issues with blend stability? Use the MFCCT to quickly identify and avoid problematic crude combinations.
  • Need better insights into your blending strategy? Integrate thermodynamic modeling into your existing process simulation tools for clearer predictions.
  • Facing unexpected operational disruptions? Turn predictive insights into practical solutions to reduce fouling, equipment damage, and costly downtime.

Opportunity crudes are economically attractive but come with unpredictable challenges. By combining predictive accuracy and seamless integration, tools like MFCCT empower you to optimize refining operations effectively and sustainably.

Ready to elevate your crude blending strategy? Read the full article to learn how two refiners elevated their crude blending strategies.