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Journal of Young Investigators ments); more specifically, testing for compliance with discharge regulations by measuring the oil in post-treatment produced water. The microscope can potentially be used to view, count, and analyze the oil droplets in treated produced water to estimate the concentration of oil in a particular sample. Such calculations can be done by image processing techniques to interpret the stacks. Calibration of the CLFM method involves comparison of estimated oil content with the CLFM to a prepared sample with known oil content. This normalized comparison refers to the percent recovery (CLFM estimated content/known content) and the standard deviation of the percent recovery to assess accuracy and precision, respectively. Several settings on the CLFM affect the intensity of the fluorescence in the images produced, and thus, affect the concentration of oil that is calculated. One study utilized the CLFM for geochemical analysis of cave deposits and addressed this issue of fluorescence intensity by maintaining all settings constant in an effort to normalize the fluorescence intensity measurements (Orland et al., 2014). None of the previous studies with CLFM, however, have delineated a clear relationship between a sample oil concentration, the number of optical sections per stack, the quantity and location of stacks, the percent recovery, and the standard deviation. This is largely due to the lack of a systematic method in retrieving confocal image data. The objective of this research is to establish a strategy for representative sampling and identify patterns between the sample concentration, number of optical sections per stack, quantity and location of stacks, threshold value for grayscale to binary image processing, percent recovery, and standard deviation. This re