Inter-Scaled Digital Core Analysis: From Core to Pore and Back

Ly, Chi Vinh; Mintz, Jason S.; Bian, Aiguo; Andrew, Matthew; Bhattiprolu, Sreenivas

doi:10.15530/urtec-2017-2671200

Cited by 3 publications

(1 citation statement)

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“…The digital core technology has been widely used to advance oilfield development [23,24], including micro-flow mechanism research, oil displacement mechanism research, and reservoir production performance simulation and prediction. Meanwhile, it is realized that CT scanning is a favorable method for reconstructing the digital core, as it can reproduce the micro-pore structure of the actual core with high accuracy.…”

Section: D Reconstruction Of Digital Shale Core By Ct Scanningmentioning

confidence: 99%

Digital-Rock Construction of Shale Oil Reservoir and Microscopic Flow Behavior Characterization

Wei

Yang

et al. 2023

Processes

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In shale oil reservoirs, nano-scale pores and micro-scale fractures serve as the primary fluid storage and migration space, while the associated flow mechanism remains vague and is hard to understand. In this research, a three-dimensional (3D) reconstruction of the shale core and micro-pore structure description technique is established; digital core technology for shale reservoirs was developed using X-ray computed tomography (X-CT), scanning electron microscope (SEM) and a focused ion beam scanning electron microscope (FIB-SEM). Microscopic oil–water two-phase flow is mimicked using the lattice Boltzmann method (LBM), a well-acknowledged approach to exploring nanoconfined fluid dynamics. In addition, coupled with digital cores, the flow characteristics of shale reservoirs are characterized. The total porosities of bedding fractures in shale and lamellar shale are 2.042% and 1.085%, respectively. The single-phase oil flow inside bedding fractures follows Darcy’s linear flow principle. This work can deepen the understanding of the microscopic flow characteristics of continental shale reservoirs and provide a reference for similar problems that may be encountered.

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Section: D Reconstruction Of Digital Shale Core By Ct Scanningmentioning

confidence: 99%

Digital-Rock Construction of Shale Oil Reservoir and Microscopic Flow Behavior Characterization

Wei

Yang

et al. 2023

Processes

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Integration of Large-Area Scanning-Electron-Microscopy Imaging and Automated Mineralogy/Petrography Data for Selection of Nanoscale Pore-Space Characterization Sites

Kazak

Chugunov

Chashkov³

2018

SPE Reservoir Evaluation &Amp; Engineering

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Summary The task of reliable characterization of complex reservoirs is tightly coupled to studying their microstructure at a variety of scales, which requires a departure from traditional petrophysical approaches and delving into the world of nanoscale. A promising method of representatively retaining a large volume of a rock sample while achieving nanoscale resolution is based on multiscale digital rock technology. The smallest scale of this approach is often realized in the form of working with several 3D focused-ion-beam–scanning-electron-microscopy (FIB-SEM) models, registration of these models to a greater volume of rock sample, and estimation and scaling up of model local properties to the volume of the entire sample. However, a justified and automated selection of representative regions for building FIB-SEM models poses a big challenge to a researcher. In this work, our objective was to integrate modern SEM and mineral-mapping technologies to drive a justified decision on location of representative zones for FIB-SEM analysis of a rock sample. The procedure is based on two experimental methods. The first method is automated mapping of sample surface area with the use of backscattered electrons (BSEs) and secondary electrons (SEs); this method has resolution down to nanometers and spatial coverage up to centimeters, also referred to as large-area high-resolution SEM imaging. The second method is automated quantitative mineralogy and petrography scanning that allows covering sample's cross section with a mineral map, with resolution down to 1 µm/pixel. Data gathered with both methods on millimeter-sized cross sections of rock samples were registered and integrated in the paradigm of joint-data interpretation, augmented with computer-based image-processing techniques, to provide a reliable classification of nanoscale and microscale features on sample cross sections. The superimposed SEM and mineral-map images were combined with physics-based selection criteria for reasonable selection of FIB-SEM candidates out of a great number of potential sites. In the result, a semiautomated work flow was developed and tested. Demonstration of the work flow is made on one of Russia's most promising tight gas formations, where the characteristic dimension of void-space objects spans from a single nanometer to millimeters. An example of an optimized site selection for FIB-SEM operations is discussed.

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High-Quality MicroCT Rock Imaging: Methodology To Measure and Correct for X-Ray Scatter

Katsevich

Frenkel²,

Sun

et al. 2019

SPE Journal

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Summary Microcomputed tomography (microCT) of cores yields valuable information about rock and fluid properties at pore scale for conventional rock and at rock heterogeneity scale for unconventionals. High levels of uncorrected X-ray scatter in computed tomography (CT) data lead to strong image artifacts and erroneous Hounsfield unit (HU) values, making reconstructed images unsuitable for accurate digital rock (DR) characterization (e.g., segmentation, material decomposition, and others). MicroCT scanners do not include scatter correction techniques. To fill this gap, we developed a new methodology to measure and remove the scatter component from raw projection microCT data collected during rock core scans, and ultimately improving the image quality of scanned cores. Widely used approaches for scatter estimation, based on Monte Carlo (MC) simulations and simplified analytical models, are time-consuming and may lose accuracy when imaging complex unconventional shale cores. In this paper, we propose a more practical approach to perform scatter correction from direct scatter measurements, an approach that is based on the beam-stop array (BSA) method. The BSA method works as follows: The radiation scattered by the core sample is emitted in random directions. By placing an array of small, highly absorbing beads between the source and the core, the primary X-ray signal through the beads is blocked, but the overall object scatter signal is not affected. The observed values in the beads’ shadows on the detector are assumed to be scatter signal. Performing interpolation of the scatter signal between the shadowed by beads pixels on the detector gives an estimate of the scatter signal at every pixel on the detector. Subtracting scatter from projection data yields scatter-corrected data used for 3D CT core image reconstruction. To develop the core scatter correction methodology, we executed the following three tasks: (1) performed modeling of primary and scattered signals to optimize the BSA design (beads size and layout) and scan parameters; (2) developed and implemented an accurate scatter correction algorithm into our 3D microCT image reconstruction workflow; and (3) tested the proposed methodology using four shale core samples from the United States and the Middle East. To better assess the impact of scatter, all experiments with shale core plugs presented in this paper were conducted using source energy of 160 kVp. Our results demonstrated that in many cases, especially with higher attenuating cores, failing to correct for X-ray scatter may result in significant loss of image reconstruction accuracy. We also showed that the developed methodology allows for accurate estimation and removal of scatter from the raw (projection) CT data, enabling reconstruction of high-quality core images that are required for performing DR analysis. To assess the impact of X-ray scatter on the accuracy of DR segmentation, we compared the amount of resolved air-filled space using a stack of image slices by thresholding for the air regions. Our results showed that the amount of detected air-filled space may increase significantly when scatter correction is applied. The presented scatter correction methodology is general and can be used with any microCT scanner used by the petroleum industry to improve image quality and derive accurate HU values. This is of significant importance for quantitative characterization of highly heterogeneous rock with fine structural changes, as is the case for shale. Ultimately, this methodology should expand the operational envelope and value of microCT imaging in the exploration and production workflows.

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Inter-Scaled Digital Core Analysis: From Core to Pore and Back

Cited by 3 publications

References 0 publications

Digital-Rock Construction of Shale Oil Reservoir and Microscopic Flow Behavior Characterization

Digital-Rock Construction of Shale Oil Reservoir and Microscopic Flow Behavior Characterization

Integration of Large-Area Scanning-Electron-Microscopy Imaging and Automated Mineralogy/Petrography Data for Selection of Nanoscale Pore-Space Characterization Sites

High-Quality MicroCT Rock Imaging: Methodology To Measure and Correct for X-Ray Scatter

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