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Processing Lower Cost Crudes with Greater Confidence & Improved Reliability

By Gerrit Buchheim, P.E., Refining Metallurgical and Corrosion Expert at Becht, Winston (Win) Robbins, PhD, Analytical Chemistry Expert at Becht, and Frank Sapienza, Metallurgy Specialist and CCD Project Manager at Becht. This article appears in the July/August 2020 issue of Inspectioneering Journal.
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Introduction

For more than 100 years, it has been understood in the petroleum refining industry that certain crude oils — or, more accurately, crude oil fractions — contain sulfur (S) species and levels of organic acids that may be very corrosive to equipment and piping in crude distillation and downstream units. Economic pressures on the refining industry are forcing many refiners to look at lower-priced high acid or opportunity crudes to improve margins. The challenge for the integrity management community is how to evaluate the effects of a crude on the equipment metallurgy installed and subsequent impact on equipment reliability. The benefits of having a more accurate crude corrosion model are large in that it allows a refinery to potentially process cheaper crudes for increased profitability with greater confidence and better anticipation and understanding of the potential damage to the equipment/piping.

Some operating companies have focused research on this subject individually or through several joint industry programs (JIPs), but current methods available to most refiners still struggle to accurately predict corrosion behavior in refinery streams on a consistent basis.

This article presents a new simultaneous S/TAN model combined with a superior flow model (SNAPS-TAC) to better predict the corrosivity of hot crude oil streams. Fundamentally, the model relies on a thin barrier layer between the iron(Fe)-based metal and the hot oil fluid. The competing reactions of barrier layer formations due to naphthenic acid (forming a magnetite/Fe3O4 scale) and S (forming an iron sulfide/FeS scale) and their destruction by turbulence and acid species are at the core of the new model. Thermodynamic and kinetic factors were derived from literature published over the past 60 years.

Common industry rules of thumb are 1 or 1.5 to 1 ratio of S/TAN to minimize acid corrosion. However, the quantities of S (wt%) differ so much from the mg KOH/g used to neutralize the acid (total acid number/TAN) that such values are arbitrary. The new model can explain why two crude oils with similar S/TAN values can corrode quite differently at the same temperature.

The new SNAPS-TAC model, resulting from the combined work and experience of numerous Becht SMEs, can help:

  • Set integrity operating windows (e.g., crude and side stream TAN, S/TAN ratio, flow velocity)
  • Predict corrosion for RBI
  • Evaluate corrosion rate of crude blends
  • Address turbulent flow issues
  • Estimate time to restore protective barrier layers
  • Establish TAN or S processing limits with given equipment
  • Estimate optimum aggressive crude slate to reach turnaround (or other controlled shutdown) within remaining life
  • Provide guidance on use of commercially available inhibitors to mitigate corrosion when running corrosive crudes
  • Prioritize the circuits to upgrade for a stepwise investment strategy
  • Identify which circuits or parts of circuits should be monitored more thoroughly
  • Identify spot crudes for feed blending for a given period of time
  • Determine blend limits on opportunity crudes without excessive upgrading or replacement in kind
  • Calculate crude blending requirements to reach non-corrosive levels
  • Evaluate alternating high TAN/high S block operations
  • Estimate barrier layer persistence
  • Compare block operation with blending opportunity crudes
  • Provide much-needed information for proactive decision making to maintain or improve equipment reliability when running opportunity crudes

In addition to all of these offline uses, the new model can be linked to the refinery’s DCS/Historian system and track the expected cumulative metal loss over time depending on actual crudes/blends processed and the operating conditions.

Understanding the SNAPS-TAC Model

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