Distinguishing carbonate reservoir pore facies with nuclear magnetic resonance as an aid to identify candidates for acid stimulation

• Main Author: Genty, Coralie
• Other Authors: Ahr, Wayne M.
• Format: Others
• Language: en_US
• Published: Texas A&M University 2006
• Subjects: carbonate; NMR
• Online Access: http://hdl.handle.net/1969.1/4206

The determination of reservoir quality and its spatial distribution is a key objective in reservoir characterization. This is especially challenging for carbonates because, due to the effects of diagenesis, quality rarely follows depositional patterns. This study integrates data from thin sections and core analyses with measurements of Nuclear Magnetic Resonance (NMR) T2 relaxation times. It exposes a novel approach to the use of NMR by applying geological and statistical analysis to define relationships between pore characteristics and the T2 data, from which a method to identify pore origin from NMR only is developed. One hundred and three samples taken from eleven wells located in fields of the Middle East, Alabama and Texas were used in the study. Modeling of the T2 spectra, as the sum of three normal components, resulted in the definition of 9 parameters representing the average, the variability and the percentage of total porosity of the specific pore sizes present in the sample. Each specific pore size corresponds to one of the following genetic pore types: intergranular, matrix, dissolution-enhanced, intercrystalline, vuggy and cement-reduced. Among the 9 parameters, two variables were identified as having the highest degree of geological significance that could be used to discriminate between pore categories: µmax which represents the largest average pore size of all pore types identified in the sample, and σmain which represents the size variability of the most abundant pore type. Based on the joint distribution of µmax and σmain computed for each pore category, the probability that an unclassified sample belongs to each of the pore categories, is calculated and the sample is assigned to the category with the highest probability. The accuracy of the method was investigated by comparing NMR predicted pore origin and genetic pore type described from thin section. A result of 89 successful predictions out of 103 samples was obtained. These promising results indicate that T2 time can be a useful identifier of carbonate pore types. Success in this work takes us closer to identifying genetic pore types from NMR logs with minimal calibration against borehole cores and will help predict the spatial distribution of poroperm facies in complex carbonate reservoirs with much improved accuracy.