Embodiments of the present disclosure provide optical methods and systems to evaluate the performance of a demulsifying agent in wellbore fluid. The present embodiments provide an optical system which scans wellbore fluid in order to detect the phase separation caused by a demulsifying agent. Using spectral data, the optical system quantifies the opacity and/or transparency of the different phases in the wellbore fluid in order to evaluate the demulsifying agent.

A model-based method of inspecting a specimen for presence of one or more interferent, such as Hemolysis, Icterus, and/or Lipemia (HI L) is provided. The method includes generating a pixelated image of the specimen in a first color space, determining color components (e.g., an a-value and a b-value) for pixels in the pixelated image, classifying of the pixels as being either liquid or non-liquid, defining one or more liquid regions based upon the pixels classified as liquid, and determining a presence of one or more interferent within the one or more liquid regions. The liquid classification is based upon a liquid classification model. Pixel classification may be based on a trained multiclass classifier. Interference level for the one or more interferent may be provided. Testing apparatus adapted to carry out the method are described, as are other aspects.

Embodiments of the present disclosure provide optical methods and systems to evaluate the performance of a demulsifying agent in wellbore fluid. The present embodiments provide an optical system which scans wellbore fluid in order to detect the phase separation caused by a demulsifying agent. Using spectral data, the optical system quantifies the opacity and/or transparency of the different phases in the wellbore fluid in order to evaluate the demulsifying agent.

A model-based method of inspecting a specimen for presence of one or more interferent, such as Hemolysis, Icterus, and/or Lipemia (HI L) is provided. The method includes generating a pixelated image of the specimen in a first color space, determining color components (e.g., an a-value and a b-value) for pixels in the pixelated image, classifying of the pixels as being either liquid or non-liquid, defining one or more liquid regions based upon the pixels classified as liquid, and determining a presence of one or more interferent within the one or more liquid regions. The liquid classification is based upon a liquid classification model. Pixel classification may be based on a trained multiclass classifier. Interference level for the one or more interferent may be provided. Testing apparatus adapted to carry out the method are described, as are other aspects.