Introduction:
For many years, researchers have employed various experimental techniques to characterize hydrocarbon-bearing porous media. One of the aims behind characterizing porous media is to be able to extract hydrocarbons from tight gas and oil reservoirs more efficiently. In this context, the word ‘tight’ is used to label media with pore size smaller than 100 µm. Efficient hydrocarbon production is aided through the understanding of fundamental transport mechanisms and the bridging among elements of the pore space architecture, namely geometry, connectivity and transport. In tight media, the latter includes not only understanding the diverse pore space, but also possible pore-fracture connectivity. Computed micro-tomography (µCT) and various nuclear magnetic resonance (NMR) methods have been used for this characterization. Magnetic resonance imaging (MRI) has been used for characterization with relative success in recent years.
µCT is one of the most popular techniques used to characterize geological samples. This technique is nondestructive and can resolve features at the micro or even nano scale, making this method advantageous for high resolution. However, µCT utilizes density contrast, making it a complex process to discern pore space from solid materials, which requires rigorous and elaborate modeling, image processing and analysis [1].
Higher-resolution techniques incur in the cost of smaller sample volume. In contrast, MRI offers direct imaging, namely direct spatial encoding, not tomography or inversion protocols, of the three-dimensional (3D) features of porous media. This is possible because MRI draws contrast by encoding the NMR signals to specific nuclei, e.g. proton spins in hydrogen-bearing molecules such as water and magnetic spatial gradients [2]. When compared to µCT, MRI also offers the advantage of characterizing a more encompassing image of the pore system by imaging a comparatively larger sample size. The larger size allows resolving multiscale features in a porous system. MRI and µCT can be complimentary to each other through digital registration algorithms [1].
NMR methods are not new to geological media characterization, but NMR’s evolving versatility offers significant advantages. For instance, Time-Domain NMR (TD-NMR) data can be collected at low-field strength (0.05 T) [1,3,4]. With this low field, the induced internal gradients that compromise NMR signals at higher filed strength are minimized. However, TD-NMR spectra are known to have poor signal-to-noise ratios (S/N) and it can be challenging to detect signals with very short (ns) transverse-relaxation times (T2) [1,3]. Fluid-flow experiments are also absent in the literature devoted to TD-NMR, because dynamic experiments and the measurement of rheological quantities cannot be performed simultaneously with TD-NMR systems [5]. Despite these drawbacks, TD-NMR can be complimentary to MRI methods in that the former can determine volume of water within the sample, T2 relaxation distributions, and diffusion measurements on a relatively fast timescale. Single-point imaging (SPI) can be performed at low magnetic field, but requires long acquisition times and is often impractical especially for high resolution images [3,6].
High-field NMR instruments, e.g. 7 T or 9.4 T, have been used for imaging in various disciplines, including the geological and medical fields. A commonly used pulse sequence is rapid acquisition with relaxation enhancement with inversion recovery (RARE-Inv-Rec), which uses flip angles of 90° and 180° for an echo recovery [7]. This pulse sequence works efficiently with high proton density areas, such as in those found in soft tissue or porous media with pores on the scale of millimeters. Fluids trapped in these samples have long T2 values (ms), allowing for a long repetition time of the applied pulse sequences [8]. With small pores (spanning nm to µm), which are commonly found in bone or geological samples, the T2 values are much shorter, (tens of µs), and the nuclear spins under study become mostly relaxed before commonly used pulse sequences are fully applied [8]. Other pulse sequences must be employed in tight porous media that allow for efficient FID acquisition, along with short repetition times.
Zero Echo Time (ZTE) is a pulse sequence that has been used for image collection of tight porous media. This pulse sequence uses a smaller excitation flip angle (5°), constant gradients and radial encoding techniques [1,3,4,9,10,11]. When compared to the more common pulse sequences that use 90°-flip angles, the 5°-flip angle used in ZTE allows for a much shorter pulse time, leading to less relaxation of the magnetization before the receiver is switched on. Another aspect of the traditional imaging pulse sequences that causes them to take longer for full application is the gradient switching process. Additionally, gradient switching can be very taxing on the instrument hardware and cause excessive heating. To avoid gradient switching, ZTE uses nonselective radio frequency (RF) excitation while the gradients are already acting [12,13]. The strength of the gradient gradually increases over time, so that spatial encoding is still possible, but the encoding happens with zero delay. The ramping gradients also reduce eddy current effects within the magnet [9]. This technique has been used in multiple fields such as imaging tissues with T2 value on the µs scale in animal bones [2] and human teeth [10,11]. The ZTE pulse sequence has also been applied to image porous media such as dolomite, reef reservoirs, and sandstone [1,3,4,11].
Subsequent to the collection of images of a porous medium, pore-cluster analysis (PCA) is frequently used to evaluate properties in geological samples, such as porosity, surface-to-volume ratio, and mass transport such as single-phase (groundwater) or multiphase flow (oil/gas) [15-17]. Pore clusters are defined by connected pore voxels that are in full contact with each other. The criterion commonly referred in connectivity analysis is that vertex and edges are not considered true connections [15]. Pore-cluster analysis allows the examination of pore connectivity through the 3D space and can be used in simulation exercises such as random walks [17].
The primary goal of the work described herein is to test the ability of ZTE, combined with PCA, to resolve both pores and fractures in rock cores with a variety of pore distributions [1,3,4,14], such as sandstone and carbonate lithologies. We initially use a porous medium consisting of 4-mm glass beads submerged in water to test the efficiency and accuracy of a PCA protocol implemented through an in-house developed Wolfram Mathematica 12.0 notebook. We provide evidence that when ZTE combined with PCA is applied to tight porous media, connectivity can be determined, and analyzed producing efficient characterization of tight porous media. Resolution limits are shown to affect the results of this analysis.