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  • https://doi.org/10.2118/230514-msCopy DOI Icon

A Laboratory Study to Better Understand the Formation Damage Using Colored and Fluorescent Particles

  • Feb 11, 2026
  • R Oughanem +4 more
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Abstract

Abstract Some formation damage mechanisms remain difficult to understand with common laboratory procedures. A lot of experimental work has been done in these last decades to encircle the main mechanisms governing the formation damage due to PWRI. Nevertheless, the relationship between solid particle deposition profiles, their sizes, and permeability reduction is still not well understood. This work is issued after a few years of collaboration between TotalEnergies and UGIEL, a French start-up specialized in coloring particles of different natures for Jewelry, aiming to test a new generation of colored and fluorescent solid particles to better understand formation damage mechanisms induced by Produced Water Reinjection (PWRI). The main objectives are to gain insights about deposition or invasion profiles of solid particles in the presence or not of oil in suspension. It is also a question to validate the theory of deep bed filtration commonly applied in the oil and gas industry. This paper describes the technology applied by UGIEL for particles coloration, and the dedicated core flooding tests program conducted by TotalEnergies to characterize the internal damage using colored and fluorescent silica particles with and without the presence of oil in suspension. This paper exhibits valuable results of damaged core plugs from post-mortem visualization, which have been subsequently completed with image processing and laser diffraction analysis. These analyses exhibit relevant findings of solid particles deposition profiles within the porous media. Additionally, the injection of suspensions containing fluorescent particles and oil has provided valuable insights into internal damage visualization under specific lighting conditions. This new generation of particles can provide more data than the pressure drop measurements analysis and can be used to validate the predictive models related to wells injectivity.

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