Reservoir Quality and Maturity Indicators Using Image-Based and Bulk Rock Characterization

Abstract

AbstractScanning Electron Microscopy (SEM) is used for source rock characterization to understand rock texture and compositional variations, porosity, and pore sizes. However, despite having significant benefits to characterization, obtaining quantitative results by SEM is time consuming and costly, and therefore the number of images collected per well is generally limited. Recent advances in image processing make obtaining quantitative data from images more accessible. This improves our ability to gather more image-based data on multiple wells for integration with larger scale measurements. Carbonate rich source rocks were sampled from several wells for SEM imaging. Large field-of-view SEM images were collected and segmented using supervised machine learning to label the pores, fractures/cracks, organics, high density minerals, and matrix minerals. Post-processing methods were used to correct mislabeled components. The relative amount of organic-contained porosity to total porosity (R1) and the relative amount of organic content to total porosity (R2) were calculated for each sample. Porosity was also obtained from crushed rock samples using the Gas Research Institute method. Pyrolysis was used to determine the productivity index and residual hydrocarbon content. Total porosity and organic content are two properties that are used to indicate rock quality. The results show that the R1 and R2 ratios from quantitative image-based analyses can be used to indicate potentially better quality. When compared across several wells of similar maturity, these quality metrics can be used to highlight wells with potentially better quality that warrant additional characterization. Finally, by comparing image-based data to that measured at larger scales, thermal maturity indicators can also be provided. This paper presents a method using image-based characterization to provide relative comparisons of reservoir quality between wells and a method to combine image-based and crushed rock analyses to compare source rock maturity. The results and workflow presented impact special core analysis for unconventional reservoirs and reservoir quality assessment and can complement characterization obtained by other methods.