Computed tomography has become a routine method for probing processes in porous media, and the use of neutron imaging is especially suited to the study of the dynamics of hydrogenous fluids, and of fluids in a high-density matrix. In this paper we give an overview of recent developments in both instrumentation and methodology at the neutron imaging facilities NEUTRA and ICON at the Paul Scherrer Institut. Increased acquisition rates coupled to new reconstruction techniques improve the information output for fewer projection data, which leads to higher volume acquisition rates. Together, these developments yield significantly higher spatial and temporal resolutions, making it possible to capture finer details in the spatial distribution of the fluid, and to increase the acquisition rate of 3-D CT volumes. The ability to add a second imaging modality, e.g., X-ray tomography, further enhances the feature and process information that can be collected, and these features are ideal for dynamic experiments of fluid distribution in porous media. We demonstrate the performance for a selection of experiments carried out at our neutron imaging instruments.
The knowledge of how hydrous fluids are redistributed within a pore network
is central to many porous media experiments, and 3-D imaging using a variety
of different imaging modalities (e.g., X-ray and neutron tomography) has
become a useful tool since it can provide information about the displacements
of fluids as well as the solid structures of the pore network within the
sample. X-rays (XCT) are currently the most widely used imaging modality
because of the high spatial and temporal resolution that can be achieved at
modern synchrotron X-ray sources
The flexibility of the instrumentation at neutron imaging beamlines meets the
needs of a wide user community, and can cater for both large and small
samples with a trade-off between sample size and (spatial and temporal)
resolution. Ongoing instrument development is steadily pushing the frontiers
in capability and making new experiments possible. Here, we review recent
advances in spatial and temporal performance at NEUTRA
The individual radiographs collected during neutron imaging represent the
neutrons that were transmitted through the sample. The mechanism that
prevents the neutrons from reaching the detector is a combination of
absorption and scattering. Scattering is often the dominant component of the
neutron attenuation coefficient
When designing an experiment the key consideration when selecting the camera
is its ability to resolve the details of interest with sufficient spatial and
temporal resolution. The contrast between the phases in the sample also plays
an important role. The contrast between phases occurs because each phase or
component in the sample has a different attenuation coefficient. The number
of captured neutrons determines how well this contrast can be resolved, with
the difference between attenuation coefficients and the signal-to-noise ratio
determining detectability. Figure
Average number of neutrons per pixel as a function of exposure time
and pixel size calculated for a neutron flux of
10
Comparison of the neutron radiographs of the gadolinium Siemens star
test object based on
Most high-resolution neutron imaging systems today operate with resolutions
on the order of several tens of microns. This applies to camera-scintillator-based systems
A first prototype of a microscope that magnifies the radiograph by a factor
of 4.3 on a gadolinium oxysulfide 4
To shorten the acquisition times, and therefore allow further practical
improvement of the spatial resolution, scintillator screens based on
isotopically enriched gadolinium oxysulfide (
Despite the relatively long acquisition times needed for imaging with the prototype Neutron Microscope, the instrument already allows observation of even slower processes in radiographic mode.
A sample of a model porous medium was used to demonstrate the spatiotemporal
capabilities of the Neutron Microscope at the BOA beamline. The sample
consists of a SiO
Visualization of the time series (Fig.
Although the data presented are from a 2-D study, the quality of the images
indicates that 3-D high-resolution neutron imaging of even slow processes
could be performed when coupled to advanced reconstruction techniques
(described later in Sect.
Time series of the evaporation of water from a model porous medium
sample. The field of view is approximately 3
The distribution of fluids in porous media can be considered as static under steady-state flow of a single fluid, or as dynamic under variable flow or composition. For the dynamic case, when capturing the effects of diffusion or flow processes over time is the objective of the experiment, time-lapse or 4-D imaging is required. With neutron imaging, experimental approaches vary with the required contrast, spatial resolution, and the temporal development of the observed process. The main challenge during a dynamic CT experiment is to avoid artifacts caused by changes within the sample during imaging and the performance of the acquisition system. Reconstruction methods generally assume that the sample is invariant during the acquisition of all the projection data used for the reconstruction.
Changes to a sample during the acquisition of the data for a single 3-D image can be induced by vibrations and centrifugal forces imposed by the sample environment. However, in many experiments these effects can be neglected, and most artifacts relate to the acquisition rate. Motion artifacts can appear if the acquisition rate is low relative to the observed process. Sub-pixel displacement rates within the sample are sufficient to cause motion artifacts in the reconstructed data. The motion artifacts appear as tangential streaks emerging from the changing region, and poorly defined phase boundaries.
Increasing acquisition speeds would reduce motion artifacts, but can be counterproductive, as faster acquisition means lower SNR, and image quality will be substantially reduced leading to possibly coarser resolution. Hence, the challenge with 4-D CT experiments is to minimize the impact of motion artifacts while providing sufficient image contrast to allow observations of the process of interest in a sample that is unaffected by the acquisition procedure.
Detecting small changes in the fluid distribution with high spatial resolution requires longer exposure times to capture a sufficient neutron dose (number of detected neutrons per pixel) to resolve the attenuation contrast between phases. Exposure times on the order of several tens of seconds or even minutes per projection are not uncommon with neutron imaging. Thus, a typical duration for a neutron CT scan is several hours. Increasing the number of neutrons improves contrast and the signal-to-noise ratio, thereby improving post-processing segmentation performance and reducing the errors in qualitative and quantitative analysis of the fluid distribution in the sample.
For most aqueous processes, the long exposure times mean that significant changes in the fluid distribution are likely over a single exposure, and that strong motion artifacts will appear in the reconstructed data. Two methods to reduce the impact of these artifacts use alternative acquisition sequences that have a time-averaging effect in the reconstructed data. The motion's artifact streaks are replaced by a smooth gradient across the extent of the dynamic region, which appears as edge unsharpness in the reconstructed data set, but does not affect static regions.
The first approach uses the repetition of several scans with equiangular
increments each with a slight angular offset upon start. The second uses
angular increments determined by the golden ratio
When the process of interest is fast compared to the projection acquisition
rate, the alternative acquisition schemes do not prevent motion artifacts.
Under these conditions the projection (frame) acquisition rate must be
increased at the cost of neutron dose. As a consequence, the dynamic range of
the gray levels and SNR will be inferior in the reconstructed data. sCMOS
cameras allow frame rates greater than 25 frames per second (making it
possible to acquire an entire set of CT projection data in about 10 s). Under such acquisition conditions, the sample table is continuously
turning, while the camera acquires projections at a specified frame rate to
avoid unnecessary time delay caused by discrete stepping. This so-called
on-the-fly tomography was demonstrated by
The neutron dose per pixel can be improved by increasing the pixel size
(Fig.
Time series neutron tomography of D
Rate and location of root water uptake by plants growing in soil is poorly
understood due to the dynamic behavior of soil and roots of transpiring
plants. In 2-D, high spatiotemporal resolution coupled to high sensitivity
to the contrast between normal (H
Performing these neutron tomography experiments was challenging because of the spatial and temporal resolution required; the process has been proven to take place within the course of several minutes depending on root thickness. Frame rates of 6 fps were needed to remove motion artifacts (to keep the water displacements below one pixel over the entire 3-D data set) during on-the-fly tomography.
The cylindrical samples of sandy soil were 27 mm in diameter and 100 mm in
length. D
The reconstructed data from the steady-state experiment
(Fig.
Working at a single depth (50 mm from the soil surface) and tracking the
D
Reconstruction from 60 projections to show the difference iterative
methods can make to resolving key spatial information in fluid flow studies.
The images show an axial slice (
Experimental projection data are usually reconstructed using the analytical
filtered back projection (FBP) reconstruction algorithm
Undersampled projection data are best treated using iterative reconstruction techniques, as these can account for various inaccuracies required by the experimental method such as nonuniform sampling steps, low-intensity dynamics, and SNR in the measurements. These reconstruction techniques also allow the imposition of some regularity (e.g., smoothness) or data consistency (e.g., rejection of nonzero values) into the process to find the solution. The benefit hereby is to improve image quality, particularly for undersampled and under-exposed projection data.
Commonly, a priori information assumes some expected local intensity
correlations, i.e., regions that remain unchanged throughout the experiment.
In the fluid-flow problems of interest here, the initial stationary “dry”
stage is an ideal “prior” reference for iterative reconstruction.
Simultaneous iterative reconstruction (SIRT) and the conjugate gradient least
square (CGLS) methods employed are now available
It can be seen that the CGLS–NLST (non-local spatiotemporal) method
Rendered volume of the stationary “dry” sample (sandstone) prior to water ingress. Reconstruction from 150 projections using a CGLS–TV algorithm.
It is possible to reconstruct a time-lapse series showing the condition of
the sample, using smaller subsets of projection data from one long sequence
of time-evolving projection data, provided the data are acquired using the
golden ratio method. The improved feature resolution provided by the
CGLS–NLST reconstruction
The fluid phase in the rock sample at three different times of the water ingress. Each volume is reconstructed from 60 projections using the CGLS–NLST method.
Cropped part (22.1
Bivariate histograms of cropped part of the X-ray and corresponding
neutron tomograms, representing a soil sample with large macropores during
various stages of recurrent ponding infiltration experiment. Histograms show
Macropore system that represents 1.97 % of the sample volume segmented from X-ray tomogram (left). Time sequence of water contents in the macropore system derived from series of 22 tomograms (right). The blue columns indicate the time of two ponding infiltration episodes.
Another successful approach
The stationary region is redefined as the experiment progresses, so the
reconstruction focusses on the dynamic regions only. This approach gives much
better spatiotemporal resolution (data comparable to that of the CGLS–NLST
method with fewer than 20 projections) than has been previously achieved
Every imaging modality has it strengths and weaknesses, and one method is rarely capable of providing all the information needed. Integrating data from a second imaging modality can provide important complementary information and reduce ambiguity. Combining neutron and X-ray CT is one example of bimodal imaging particularly relevant for investigations of flow in porous media. The attenuation coefficients of a particular phase will be significantly different in the two data sets, and therefore multivariate methods will provide better results than those using single data sources. In some cases the contrast is even reversed between the modalities, e.g., water which is low contrast for X-rays while it provides a high contrast for neutrons.
There are two typical uses for bimodal imaging: (1) the sample is static but it is difficult to identify relevant features due to small differences in contrast between the present materials and (2) samples with a dynamic component. In the latter case, one modality can be used to identify the static structures, while the other is used to capture the displacements caused by the observed process. For experiments with complex sample compositions, combining the two approaches to increase performance and data quality may be required.
Bimodal imaging using neutrons and X-rays is available to users at NEUTRA
One key advantage of using the same sample manipulation environment is the reduced registration required to align the image data from the modalities onto a common coordinate system. This is in particular true for the installation at NEUTRA where the X-ray and neutron beams have a very similar geometry, and makes pixel-wise comparison possible. At ICON, an alternative approach has been taken, and the divergent X-ray source and beamline mounted perpendicular to the neutron beam direction. This installation further reduces the time between imaging using each modality, and makes simultaneous imaging using both modalities possible. The only need to drive ex situ X-ray imaging in this case is the potential for higher spatial resolutions that can be achieved elsewhere.
There are several strategies to analyze bivariate data. The work flow
usually starts with a registration step to align the data sets onto a common
coordinate system. This guarantees that pixel-/voxel-wise analysis of the two
data sets is possible. Approaches that start data fusion during the
reconstruction stage first register the projection data
As an example of combined X-ray and neutron tomography imaging, we present a
study of water and air behavior in soil. The infiltration of water and air
trapping was studied on intact samples of coarse sandy loam soil from a
mountainous site (Cambisol series, Korkusova Hut, Sumava Mountains, Czech
Republic) from a depth of 40 cm below the surface. Preferential and
localized water flow often occurs in this soil
The experiment performed at the NEUTRA beamline consisted of two infiltration
episodes during which a layer of D
The neutron and X-ray tomograms were reconstructed by the MuhRec3 code
Fine co-registration of the X-ray and neutron tomograms was done by searching
for the minimum of sum of differences while rotating and translating the
X-ray tomogram as a rigid body. Bivariate histograms shown in
Fig.
The segmented X-ray tomogram was then used as a binary mask (see
Fig.
We have shown, using state-of-the-art approaches, that neutron
imaging beamlines are a vital tool for observing processes in porous media.
Routine methods are now approaching, or exceeding the spatial and temporal
scales that can be achieved with lab-based X-ray sources. However, it is this
capability coupled to the high sensitivity to hydrogen that makes neutron
imaging such an ideal probe for high-resolution experiments (2-D or 3-D over
time) into the spatiotemporal distribution of fluids in porous media. PSI
instrument options achieve spatial resolutions on the order of a
1–50
While it is important that the data can be acquired, the techniques shown here aim to increase the information that can be extracted from the data as well as increase the data acquisition rate. The neutron imaging community is currently focussed on developing improved methods for multidimensional and multimodal data analysis under low SNR conditions through close collaboration between the user community, instrument scientists, and algorithm developers. For experiments that produce data with intrinsic time structure, it is often beneficial to perform the analysis in 4-D instead of processing the data as a sequence of individual 3-D images. Ideally, the subsequent post-processing quantitative analyses will also involve the time structure to yield more accurate analyses.
Already, thanks to recent technological improvements, neutron imaging is a good choice to observe and quantify transport processes in porous media at different scales in time and space, regardless of whether the pore space can be resolved or not.
For the experiments performed at NEUTRA, we kindly acknowledge the instrument support by Jan Hovind, Martina Sobotkova, and Vladka Jelinkova. We would also like to acknowledge the support and funding from COST action MP1207, the Czech Science Foundation (project no. 14-03691S), as well as the European Union's Seventh Framework Programme for Research and Technological Development under the NMI3-II grant no. 283883, SINQ 20110581. Edited by: H. Steeb Reviewed by: F. Fusseis and R. Jänicke