Calculating Porosity and Describing Pore Networks from Computed Tomography (Ct) Data in Permian Carbonate Core Samples from the Happy Spraberry Field, In Garza County, Texas
MetadataShow full item record
This study researched whether there were accurate alternative methods to evaluating porosity values and other rock property characteristics in Permian carbonate samples from well Lott 19-3, 4915’, Lott 19-7, 4940’- 5000’, and Lott 19-8, 4917’- 5000’ in the Happy Spraberry Formation. Through these techniques used pore types, porosity and cement values were identified, to determine whether these alternative methods of petrographic image analysis and Computed Tomography (CT) technology could be viable techniques to replace older image analysis methodologies that take more time, money and are far more destructive. To accomplish this, a workflow was developed to analyze petrographic images and CT scan data. These values were then evaluated for accuracy by comparing the results to a previous study which used helium injection testing, a method considered to have a high level of accuracy. The Happy Spraberry Field is located in the South Central part of Garza County, Texas. It forms part of the Eastern Shelf, which produces from a 100 foot thick carbonate interval and is the second largest oil field that produces from the Lower Clear Fork Formation in the Midland Basin. The formation consists of six facies that have been identified in previous studies. These facies are oolitic skeletal grainstones and packstones, floatstones and rudstones, In situ Tubiphytes bindstones, and siltstones from slope deposits. There was a slightly lower trend in the porosity values from this study and the benchmark data from the helium test analysis. This discrepancy was attributed to the low resolution, and incomplete magnification of the microporosity from the computer and images. The results were within a reasonable range of the true porosity values, but can be improved by reworking the workflow used. The cement values obtained through this workflow helped demonstrate the idea that high cementation levels directly correlate to low porosity values. These results are considered to be accurate due to the specific way in which the workflow was modified to only color-change the pixels inside the cemented areas. Finally, it was concluded that rock characteristics, such as pore types, could be observed through image analysis techniques as long as the thin section images have a good resolution that allows for minimal distortion of the image.
Valenzuela, Gerardo; Martinez, Jaime (2017). Calculating Porosity and Describing Pore Networks from Computed Tomography (Ct) Data in Permian Carbonate Core Samples from the Happy Spraberry Field, In Garza County, Texas. Undergraduate Research Scholars Program. Available electronically from