Assistant Professor, Research Institute of Petroleum Industry (RIPI), Tehran, Iran
Masters Student, Islamic Azad University - Science and Research Branch, Tehran, Iran
Assistant Professor, Islamic Azad University - Science and Research Branch, Tehran, Iran
Research Assistant, Research Institute of Petroleum Industry (RIPI), Tehran, Iran
Qualitative analysis of petroleum reservoir rocks is still one of the most important topics of core laboratories and directly affects hydrocarbon-in-place, fluid flow, and prediction of field performance. Magnetic Resonance Imaging (MRI) as a non-invasive, millimeter resolution technique which only images fluids in porous media fits this purpose perfectly. Magnetic resonance is a radio frequency spectrometry, based on excitation of nucleus energy levels which can exploit a wide range of information on the saturation fluid, geometry of pores, and diffusion. Using magnetic gradients and signal encoding, this can be used as a tomography technique. Determining porosity regardless of rock lithology, reservoir rock quality, bound and free water (which presents production potential) and potential permeable tight beds are applications of this method, from among many others. Recent advances in imaging techniques along with new software and processing methods has resulted in exploiting the images containing valuable physical information.
The main aims of this study are qualitative investigation of core sample, determining the number and distribution of vugs, presenting three-dimensional models and comparing this method with other conventional methods. We acquired images of cores adequate for revealing characteristics of matrix, vugs, and other different porosity types in carbonate rocks as well as their interaction. The images in the form of matrices of MR signal were analyzed using both image analysis and physics of MR signal. Studied samples are a selection from one of southern Iranian carbonate reservoirs, cleaned using Soxhlet extraction, dried in oven and saturated with synthetic reservoir brine. Rock type, pore-filling fluid, the MRI imaging hardware and software, pulse sequence, and image processing affect such study results. So, impacts of several items were considered and best available pulse sequence parameters were set. Presence of ferromagnetic minerals adversely affects image quality, so samples bearing these minerals are very difficult to image in high fields and have to be imaged with special pulse sequences and systems.
Samples without ferromagnetic minerals, as in most carbonate rocks, can be imaged in high fields, so because of the superior quality of high field imaging, this method is used in our carbonate samples.
Validity of MRI images was verified using histogram analysis of water, rock and air segments of the images subsequent to acquisition. Reference fluids, brine (the pore-filling fluid) and air, helped us in matching and comparing histograms and check the validity of signal from porous sample. In image analysis we utilized histogram, field of view, and segmentation techniques. Results of this analysis after using physical models of MRI signal in porous media led to numerical and visual models of rock samples. In addition to visual models of porosity, we prepared visual models of mean-T2 of invaluable to quantitative and qualitative study of porosity, ultimately resulting in determining fraction of vuggy, moldic, and inter-particle porosity. This model was constructed by superposition of image slices.
Inter-particle porosity cannot be determined from sub-millimeter MRI image analysis, so it is calculated from the physics of MR signal. We determined the accuracy of the method in comparison with other conventional experiments such as helium porosimetry and petrographic image analysis which revealed reasonable accuracy of the method in determining porosity types and visualization. Effect of several items in the accuracy of this method is proposed. First, gravimetry porosity is always lower compared to the helium porosimetry, and porosity calculated from MRI imaging only is affected by water saturation of the sample, so MRI porosity should always be compared with gravimetry porosity. Second, MRI images are not only sensitive to water in porous samples, but also sensitive to pore size of the sample. Water in very fine pores is not shown in images unless echo time is set to 1-3ms, not possible in our study because of hardware limits. Third, magnetic field inhomogeneity can account for up to nine percent of signal intensity.
This study obtained a new perspective in using MRI imaging for qualitative study of porosity and determining share of porosity types.