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Determination of oil and water in drilled bore cores via fast-neutron resonance transmission radiography D. Vartsky a ,∗, M.B. Goldberg a , V. Dangendorf b , I. Israelashvili a,d , I. Mor c , D. Bar c , K. Tittelmeier b , M. Weierganz b , B. Bromberger b , A. Breskin a a
Weizmann Institute of Science, Rehovot, 7610001, Israel Physikalisch-Technische Bundesanstalt (PTB), 38116 Braunschweig, Germany c Soreq NRC, Yavne 81800, Israel d Nuclear Research Center of the Negev, P.O. Box 9001, Beer Sheva, Israel b
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Keywords: Fast neutron resonance radiography Oil exploration Core analysis Time resolved event-counting optical neutron detector
ABSTRACT Fast-Neutron Resonance Transmission (FNRT) Radiography was applied to the rapid, non-destructive and quantitative determination of the oil and water weight fractions in cores taken from subterranean or underwater geological formations. In this article, we describe the FNRT method and present results of an experimental determination of oil and water weight fractions in synthetic samples containing minerals, oil and water as well as in 10 cm thick rock samples of Berea Sandstone and Indiana Limestone formations. Moreover, Monte-Carlo simulations, demonstrate the possibility of determining the oil grade contained in the rock by calculating its C/H ratio. This is of a prime importance in decision-making during a drilling process. The technique is suitable for all types of formations, including tight shales, clays and oil sands.
Contents 1. 2. 3. 4.
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Introduction ....................................................................................................................................................................................................... Fast-Neutron resonance transmission radiography................................................................................................................................................... 2.1. FNRT detectors........................................................................................................................................................................................ FNRT method for oil exploration........................................................................................................................................................................... Experimental procedures...................................................................................................................................................................................... 4.1. Neutron irradiation procedure................................................................................................................................................................... 4.2. Irradiation of compartment box................................................................................................................................................................. 4.3. Irradiation of formation rocks saturated with fluids ..................................................................................................................................... Experimental results ............................................................................................................................................................................................ 5.1. Determination of mass-attenuation coefficients of pure materials .................................................................................................................. 5.2. Reconstruction of areal densities ............................................................................................................................................................... 5.2.1. Compartment box ...................................................................................................................................................................... 5.2.2. Sandstone and limestone formation samples ................................................................................................................................. Evaluation of oil grade by FNRT ........................................................................................................................................................................... Discussion and conclusions................................................................................................................................................................................... References..........................................................................................................................................................................................................
1. Introduction In oil exploration, it is important to perform a rapid analysis of a drilled formation core in order to make a decision whether the investigated well can be economically exploited. The fundamental core properties of interest are: (1) Rock porosity as a measure for the storage
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capacity for reservoir fluids, (2) Saturation of pore volume with different fluid types and their quantitative volume fractions, (3) Rock permeability as a measure for the reservoir’s flow capacity, and (4) Oil grade which determines the quality of the crude oil. The most prevalent analysis techniques are based on destructive analysis of small plug samples removed from the core [1]. More recent
∗ Corresponding author. E-mail address:
[email protected] (D. Vartsky).
https://doi.org/10.1016/j.nima.2018.10.024 Received 25 July 2018; Received in revised form 3 October 2018; Accepted 3 October 2018 Available online xxxx 0168-9002/© 2018 Elsevier B.V. All rights reserved.
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techniques include X-ray CT [2] and MRI analysis [3] that could, in principle, be applied non-destructively to larger core samples. The application of Fast-Neutron Resonance Transmission radiography (FNRT) for oil exploration has been described previously by our group [4,5]. We have demonstrated that FNRT can be used for non-destructive, specific and quantitative determination of porosity, fluid saturation in mixtures such as oil-sand and water-sand and also in formations such as sandstone and limestone saturated with a single fluid (oil or water). Although our Monte-Carlo calculations [4,5] show that we can simultaneously determine both oil and water in the drilled core containing both types of fluids, in our previous experimental work we used samples saturated with either oil or water, but not with both. In the present work we demonstrate experimentally, using calibrated synthetic samples, that it is possible to determine by the FNRT method each fluid in a combined oil/water sample. In addition, we show by Monte-Carlo calculations that the FNRT method can provide information on crude oil grade or the oil composition. Fig. 1. Calculated transmission through 10 cm thick TATP, polyethylene and melamine samples. The density of all samples was defined to be 1.0 g/cm3 [9].
2. Fast-Neutron resonance transmission radiography
Table 1 Properties of FNRT detectors.
In FNRT, the inspected object is radiographed with a broad spectrum of neutrons in the 1–10 MeV energy range. The FNRT method [6] exploits characteristic structures (resonances) in energy-dependency of the neutron interaction cross-section of specific elements in the analysed object—to determine the identity, abundance and spatial distribution of materials contained in that object. This requires measuring the spectral and spatial distribution of the transmitted-neutron field through the object. Depending on the nature of the inspected object the transmitted neutron spectrum will exhibit dips and peaks at specific energies. Therefore, the transmitted neutron spectrum carries information about the composition of the object. A principal application of FNRT has been the automatic detection of explosives [7,8], in commercially transported items. Due to its ability to detect simultaneously the main elements present in explosives, such as C, O and N, the method is suitable for the detection of most standard and improvised explosives. A system for detection of explosives in airpassenger bags based on this method has been constructed and tested by University of Oregon [7] and Tensor Technology Inc. [8]. Both systems used accelerator-based, nanosecond-pulsed, broad-energy neutron beams for interrogating the objects of interest. Neutron spectroscopy was performed by the Time of Flight (ToF) method. An example of an improvised explosive employed by suicide bombers is Tri-Acetone-Tri-Peroxide (TATP), combining acetone, hydrogen peroxide and sulfuric acid. FNRT is particularly effective in distinguishing small quantities of TATP, from other equal-density materials, due to the different proportions of their constituent elements [9]. Fig. 1 shows the calculated neutron transmission vs. neutron energy through 10 cm thick samples of TATP, polyethylene and melamine; all samples had density of 1.0 g/cm3 . Here we used the tabulated ENDF [10] total neutron crosssections. The effects of neutron scattering were not considered.
Parameter
Value
Detector area [cm2 ] Detection efficiency [%] Position resolution [mm] Time resolution [ns] Energy resolution [keV] at few MeV Count-rate capability [c/s/cm2 ] Sensitivity to gamma-rays
>20 × 20 >20 1–5 1–5 <200 ∼105 As low as possible
Miller et al. [8] used a large-area detector consisting of individual 4 × 4 × 3 cm3 plastic scintillators, each coupled to a photomultiplier tube. With such detector dimensions a spatial resolution of 3.3 × 3.3 cm2 was achieved at the object position. Clearly, this position resolution is not suitable for detection of small and thin objects. In 2001 we started to develop fast-neutron detectors with millimeterposition-resolution and few-ns timing, as required for FNRT. These were several generations of Time-Resolved Integrating Neutron (TRION) detectors [12,9], a Time-Resolved Event-Counting Radiation (TRECOR) detector for detection of gamma-rays and neutrons [13,14] and also a liquid-Xe based neutron/gamma-ray imaging detector [15]. For the application of FNRT to oil exploration, the most suitable fast-neutron detector appears to be the Time-Resolved Event-Counting Neutron (TRECON) detector, a simplified version of TRECOR, dedicated to fast-neutron detection. The TRECON detector is based on a time resolved event-by-event counting technique of optical signals. Fig. 2 shows schematically the configuration of the detector. Fast neutrons transmitted through the inspected object interact with a 3–5 cm thick planar plastic scintillator slab or an array of scintillating fibres. The scintillator face is viewed through a front-coated bending mirror (98% reflectivity) positioned at an angle of 45◦ relative to the incoming beam direction, by a largeaperture lens (120 mm F#0.95); the latter focuses the light on the photocathode of a 40 mm effective diameter Event Counting Image Intensifier (ECII), which is capable of measuring the position of each detected event and its ToF [13]. A position resolution of about 1 mm and a timing resolution of about 4–5 ns were achieved with the TRECON detector [14].
2.1. FNRT detectors In most FNRT systems there is a need for a large area, efficient imaging detector. The dimensions and the detection efficiency influence the inspection time of the object. The spatial resolution (pixel size) determines the smallest possible detectable detail of interest. Further important parameters are the energy resolution, the counting-rate capability and the sensitivity to gamma rays and to scattered radiation. Most of the FNRT systems developed to date applied the time-of-flight (ToF) method for high resolution neutron spectroscopy, requiring detectors with nanosecond timing properties [11]. Table 1 summarizes the requirements of an FNRT detector.
3. FNRT method for oil exploration Fig. 3 shows the energy dependence of the neutron mass-attenuation coefficients of calcite, silica, (the principal constituents of limestone and sandstone rocks respectively), oil and water. 2
Please cite this article in press as: D. Vartsky, et al., Determination of oil and water in drilled bore cores via fast-neutron resonance transmission radiography, Nuclear Inst. and Methods in Physics Research, A (2018), https://doi.org/10.1016/j.nima.2018.10.024.
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Fig. 2. Schematic view of the TRECON detector [13]. Light emitted from the plastic scintillator is focused by a large aperture lens on a photocathode of an event-counting image-intensifier (ECII).
Fig. 3. The neutron mass-attenuation coefficients of silica, calcite, oil and water vs. neutron energy.
Fig. 4. Schematic description of an FNRT irradiation configuration of a core in its protective sleeve. The arrow marked ‘‘A’’ stands for part of the fast-neutron beam that traverses the thickness x of the sample and impinges on a specific pixel within the detector array.
The values for the above substances were calculated using compiled neutron cross-sections [10] of their elemental constituents. It can be observed that the attenuation coefficients of the four substances exhibit a different characteristic dependency on the neutron energy. This is due to resonances in the neutron interaction with the most abundant elements in these materials, such as carbon in oil, oxygen in water, oxygen and silicon in silica and calcium, oxygen and carbon in calcite. Hydrogen, present in oil and water does not exhibit any resonances in its attenuation coefficient, which decreases smoothly with the neutron energy. Thus, for example, the resonant features in water are all due to resonances in the oxygen cross-section, which are superimposed on a smooth hydrogen cross-section curve. Fig. 4 schematically describes the FNRT irradiation configuration. An intact core within its protective sleeve is subjected to a broad-energy (1– 10 MeV) neutron beam. The transmitted neutron spectrum is detected by one of the previously described fast-neutron spectroscopic imaging detectors. Assuming that the inspected object, such as an oil-drilling core, consists mainly of a porous rock matrix (e.g. sandstone), oil and water;
the ratio 𝑅𝑖 of the transmitted-to-incident neutron flux at energy 𝑖 and at the position indicated in the drawing by the arrow (A) is: 𝑅𝑖 = exp[−(𝜇𝑖𝑠 𝜌𝑠 𝑥 + 𝜇𝑖𝑜 𝜌𝑜 𝑥 + 𝜇𝑖𝑤 𝜌𝑤 𝑥)]
(1)
Where 𝜇𝑖𝑠 , 𝜇𝑖𝑜 , 𝜇𝑖𝑤 and 𝜌𝑠 𝑥, 𝜌𝑜 𝑥, 𝜌𝑤 𝑥 are the mass-attenuation coefficients and areal densities of a dry formation (sandstone, limestone), the oil, and the water, respectively. The densities 𝜌 in Eq. (1) are not the intrinsic physical densities of the substances, they represent the mean densities averaged over the trajectory 𝑥. Since the spectrum may consist of 𝑛 discrete neutron-energies, 𝑛 such equations can be written. By taking a natural logarithm of 𝑅𝑖 one obtains a set of 𝑛 linear equations where the areal densities are the unknowns of interest. The procedure of reconstructing core mineral, oil and water areal densities has been described in detail in [4]. It consists of solving 3
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an over-determined system of 𝑛 linear equations with three to five unknowns. Such a problem can be solved by e.g. a least-squares solution with bootstrapping or by a Bayesian minimization method [16,17]. Once a solution for the 3 areal densities is found for a given detector pixel, we can determine the areal-density-ratio of oil or water to that of the dry rock. This yields the local weight-fractions of oil and water 𝐹𝑜 and 𝐹𝑤 in the traversed core, independent of the sample thickness or its shape. It must be noted that the fluid weight-fractions in the sample are determined independently, thus the oil-to-rock weight-ratio is independent of water content. One can now display the map of oil or water weight-fractions for each individual pixel. Prior to a given core analysis we must calibrate our system using reference materials. To this end, the values of the mass-attenuation coefficients vs. neutron energy must be determined experimentally for pure dry-rock of known grain-density, oil and water. This calibration procedure is necessary since there could be significant differences between rock and oil types from one drilling site to another. For experimentally determining the mass-attenuation coefficients 𝜇𝑖𝑠 , 𝜇𝑖𝑜 , 𝜇𝑖𝑤 we used as reference materials SiO2 and CaCO3 powders, samples of dry Indiana limestone (LS) and Berea sandstone (SS), pure Odorless Mineral Spirit (OMS) liquid and regular tap water. From the determined oil and water average weight fractions 𝐹o and 𝐹w it is further possible to calculate the dry weight of the core, its average rock porosity and its average oil and water saturation levels, provided we can measure the core’s total weight and volume and that the grain-density of the rock, as well as the densities of oil and water are known [5]. The method can provide the relevant information regardless of the object geometry.
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Fig. 5. Description of the compartment box.
4.3. Irradiation of formation rocks saturated with fluids
4. Experimental procedures
Berea Sandstone (SS), bulk density 2.11 g/cm3 and Indiana Limestone (LS), bulk density 2.26 g/cm3 , cubical samples 100 ⋅ 100 ⋅ 100 mm3 were saturated either with OMS hydrocarbon or water. In order to determine the uniformity of the fluid saturation, these samples were scanned with a collimated neutron beam directed perpendicularly to the direction of the fluid saturation process. The scans were performed from the bottom to the top of each sample, in 1 cm steps. The scans indicated that the fluids were uniformly distributed along the saturation direction to within ±2%.
4.1. Neutron irradiation procedure
5. Experimental results
The experiments were performed using the CV28 isochronous cyclotron at the Physikalisch-Technische Bundesanstalt (PTB), Braunschweig, Germany. Neutrons were produced in a broad spectral range by a pulsed 12 MeV deuterium beam impinging on a 3 mm thick Be target. This reaction yields a useful neutron spectrum in the energy range of 1 MeV up to 12 MeV [18]. The deuteron beam was pulsed at a rate of 2 MHz and a pulse width of 1.7 ns. The average beam current was approximately 2 μA. Since our samples were uniform in their composition, no imaging was performed and the neutrons were detected in a counting mode using a single cylindrical 25.4 mm diameter × 25.4 mm long liquid-scintillator detector (BC501) positioned at a distance of 1247 cm from the target. The sample was positioned at a distance of 240 cm from the detector in order to minimize neutron scattering effects. Neutron spectroscopy was performed using the Time-of_Flight (ToF) technique, i.e. by measuring the time difference between the deuteron pulse hitting the target and the neutron event detected in the BC501 scintillator. The total measurement time per sample ranged from 100–1000 s.
5.1. Determination of mass-attenuation coefficients of pure materials The mass-attenuation coefficients, shown in Fig. 6 were determined by measuring the neutron transmission through pure dry limestone (LS) and sandstone (SS) rock samples, water and OMS oil. The measured mass attenuation coefficients of CaCO3 and SiO2 powders were indistinguishable from those of dry LS and SS respectively. Compared to the calculated spectra of Fig. 3 some of the sharp resonance peaks are missing here due to the limited timing resolution of the experimental system. Also note that the mass attenuation coefficient values for oil are lower than those of Fig. 3. This could be due to the fact that the OMS oil composition used here was not known and could be different from the composition of oil used for calculations of Fig. 3. These experimentally determined mass-attenuation coefficients are used as 𝜇𝑖𝑠 , 𝜇𝑖𝑜 , 𝜇𝑖𝑤 values in Eq. (1) for reconstructing the areal densities of the formation mineral, oil and water in samples. For reconstruction, we used only a limited range of neutron ToF values, shown in Fig. 6, corresponding to an energy range of 1.7–4.2 MeV. We found that this range resulted in the best reconstruction.
4.2. Irradiation of compartment box
5.2. Reconstruction of areal densities
In order to evaluate the FNRT method for an object consisting of mineral material and different fluids, we used a box divided into compartments as shown in Fig. 5. The box volume was divided into compartments, separated by 1 mm thick Al sheets. The large compartment (100 ⋅ 100 ⋅ 100 mm3 ), was loaded with either SiO2 powder (bulk density 1.45 g/cm3 ) or CaCO3 powder (bulk density 0.982 g/cm3 ). The narrow compartments (10 ⋅ 100 ⋅ 100 mm3 ) were filled with either oil (OMS-0.748 g/cm3 ) or water or with both fluids. This method assured a uniform distribution of the various materials in the sample.
We used two methods for reconstructing the areal densities: (1) a least-squares solution with bootstrapping and (2) the WinBUGS program (Bayesian Inference Using Gibbs Sampling) [17]. Both yielded very similar reconstruction results and uncertainties. The reconstruction methods provide a probability distribution of the areal density for each constituent, indicating whether it is likely to be present in the inspected sample and what is the most probable areal density. The shape of the distributions provides additional information. Substances which are likely to be present in the inspected sample (true positive) have probability distributions that are Gaussian-like in shape and exhibit 4
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Fig. 8. Reconstructed weight fractions (%) of water in limestone and sandstone samples.
Fig. 6. Experimentally determined mass-attenuation coefficients for dry limestone, dry sandstone, water and oil (OMS) vs. ToF (expressed in ADC channel number). The neutron energy range is 1.7–4.2 MeV.
relative standard deviations of the order of few percent, whereas the frequency distributions of the areal density for substances which are not present in the inspected sample, have probability densities that peak at or around 0 and are skewed. The relative standard deviations in these cases are of the order of 30% or higher.
5.2.2. Sandstone and limestone formation samples Fig. 8 shows the reconstructed weight fractions (in %) of oil (𝐹o ) and water (𝐹w ) in the limestone (LS) and the sandstone (SS) rock samples. Also here the uncertainties have been calculated using bootstrapping. The expected values are shown as circles. Using these weight fractions it is possible to calculate the important formation parameters, such as dry core weight, porosity and oil and water saturations [5].
5.2.1. Compartment box
6. Evaluation of oil grade by FNRT
Fig. 7 shows the reconstructed experimental areal-density distributions of SiO2 powder, oil and water obtained using the compartment box loaded with SiO2 +oil, SiO2+water and SiO2+oil+water. The expected areal density values of mineral, oil and water are indicated in red.
An important parameter in oil exploration is the grade (quality), or composition of the crude oil. Crude oils are complex, but mainly paraffinic, naphthenic and aromatic mixtures. The characterization of crude oil is usually carried out by standardized ASTM methods, such as the true boiling point distillation, gravity and by elemental (C, H, N and S) analysis [19,20]. One indicator of the crude oil quality is the C/H ratio. This ratio increases with the saturated-hydrocarbon chain length. Thus C3 hydrocarbon will have a C/H weight ratio of 4.5, while in C20 this ratio increases to 5.7. FNRT can provide us with the C and H content in oil trapped in the rock sample, provided we use rock, water, elemental-carbon and
The probability distributions, their mean value and the estimate of the standard deviations of the areal densities were determined by fitting with a generalized least square model with bootstrapping. The distributions for CaCO3 samples were similar in shape. The ratio of the reconstructed areal density of oil (or water) to that of the mineral yields the weight fractions 𝐹o and 𝐹w of each fluid in the sample.
Fig. 7. Distribution of the reconstructed areal density of SiO2 , oil and water in the compartment box for various SiO2 /fluid combinations. The expected values are indicated in red colour.
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Table 2 Reconstructed areal densities [g/cm2 ] of limestone and water in core, carbon in oil, hydrogen in oil and their weight ratio. Oil type
Limestone
Water
C in oil
H in oil
Oil C/H weight ratio
Light Heavy
25.9 ± 0.29[26] 26.3 0.2[26]
1.25 ± 0.15[1.3] 1.37 ± 0.11[1.3]
2.36 ± 0.13[2.13] 2.27 ± 0.1[2.21]
0.47 ± 0.02[0.47] 0.395 ± 0.012[0.39]
5.0 ± 0.35[4.5] 5.7 ± 0.29[5.7]
* [expected values].
elemental-hydrogen mass attenuation coefficients in solving our set of linear equations instead of using the substance’s attenuation coefficients of Fig. 6. As at this stage we do not have experimentally-determined values of elemental-hydrogen mass attenuation coefficients we have tested this idea by using Monte-Carlo calculations, employing the Geant4 toolkit [21]’’. A 10 cm thick limestone core was saturated with oil—10% by weight and with water—5% by weight. In our calculations, we used light (𝐶3 H8 ) and heavy (𝐶20 H42 ) oils. Table 2 shows the reconstructed areal densities of limestone, water, carbon in oil and hydrogen in oil. The figures in brackets are the expected values. One can observe that although elements, such as, C and H are present also in limestone and water, respectively, the method is able to take this into account and derive the oil carbon and hydrogen areal densities with a reasonable accuracy, thus providing valuable information on the oil grade.
25%. Selection of energy region 1.7–4.2 MeV provided results closest to the expected values. We have demonstrated experimentally that the core water and oil contents can be determined with good accuracy. Moreover, it was demonstrated by Monte-Carlo calculations that it is possible to provide a measure of oil grade by determining the C/H ratio of oil. References [1] American Petroleum Institute, Recommended practices for core analysis, API Publications and Distributions 2nd Edition, February 1998. http://w3.energistics. org/RP40/rp40.pdf. [2] M. Boone, T. Bultrjs, B. Masschaele, D. Van Loo, L. Van Hoorebeke, V. Cnudde, Int. Symposium of Society of Core Analysts, Snowmass Colorado, 2016, SCA2016-018. [3] J. Mitchell, T.C. Chandrasekera, D.J. Holland, C.V. Gladden, E.J. Fordham, Phys. Rep. 526 (2013) 165. [4] D. Vartsky, M.B. Goldberg, V. Dangendorf, I. Israelashvili, I. Mor, D. Bar, K. Tittelmeier, M. Weierganz, B. Bromberger, A. Breskin, Int. J. Appl. Radiat. Isot. 116 (2016) 87. [5] D. Vartsky, M.B. Goldberg, V. Dangendorf, I. Israelashvili, I. Mor, D. Bar, K. Tittelmeier, M. Weierganz, B. Bromberger, A. Breskin, Proc. Int. Symposium of the Society of Core Analysts, Vienna, Austria, Aug. 2017, SCA2017-034, arXiv: 1706.07689v1. [6] J.C. Overley, Int. J. Appl. Radiat. Isot. 36 (1986) 185–191. [7] M.S. Chemelnik, R.J. Rasmussen, R.M.S. Schofield, G.E. Gieger, H.W. Lefevre, J.C. Overley, C.J. Bell, FAA report No. DOT/FAA/AR-97/;61, 1997. [8] T.G. Miller, P.K. Van Staagen, B.C. Gibson, J.R. Orthel, R.A. Krauss, SPIE Proceedings, Vol. 2936, 1997, p. 102. [9] I. Mor, D. Vartsky, D. Bar, G. Feldman, M.B. Goldberg, D. Katz, E. Sayag, I. Shmueli, Y. Cohen, A. Tal, Z. Vagish, B. Bromberger, V. Dangendorf, D. Mugai, K. Tittelmeier, M. Weierganz, JINST 4 (2009) P05016, http://arxiv.org/abs/0905.4399. [10] Evaluated Nuclear Data File, (ENDF), 2015, https://www-nds.iaea.org/exfor/endf. htm. [11] D. Vartsky, Proc. Int. Workshop on Fast Neutron Detectors and Applications, University of Cape Town, South Africa, 2006, PoS(FNDA2006)084. [12] V. Dangendorf, D. Bar, B. Bromberger, G. Feldman, M.B. Goldberg, R. Lauck, I. Mor, K. Tittelmeier, D. Vartsky, M. Weierganz, IEEE Trans. Nucl. Sci. 56 (2009) 1135–1140. [13] S. Schössler, B. Bromberger, M. Brandis, L. Schmidtd, K. Tittelmeier, A. Czasch, V. Dangendorf, O. Jagutzki, JINST 7 (2012) C02048. [14] M. Brandis, D. Vartsky, V. Dangendorf, B. Bromberger, D. Bar, M.B. Goldberg, K. Tittelmeier, E. Friedman, A. Czasch, I. Mardor, I. Mor, M. Weierganz, JINST 7 (2012) C04003. [15] I. Israelashvili, A.E.C. Coimbra, D. Vartsky, L. Arazi, S. Shchemelinin, E.N. Caspi, A. Breskin, JINST 12 (2017) PO9029. [16] B. Efron, Ann. Statist. 7 (1) (1979) 1–26. [17] D.J. Lunn, A. Thomas, N. Best, D. Spiegelhalter, Stat. Comput. 10 (2000) 325–337. [18] H.J. Brede, G. Dietze, K. Kudo, U.J. Schrewe, F. Tancu, C. Wen, Nucl. Instrum. Methods 274 (1989) 332. [19] J.G. Speight, J. Petrol. Sci. Eng. 22 (1999) 3. [20] F. Sanchez-Minero, J. Ancheyta, G. Silva-Oliver, S. Flores-Valle, Fuel 110 (2013) 318. [21] S. Agostinelli, J. Allison, K. Amako, J. Apostolakis, H. Araujo, et al., Nucl. Instrum. Methods A 506 (2003) 250.
7. Discussion and conclusions We describe a method based on Fast-Neutron Resonance Transmission (FNRT) radiography for a non-destructive, specific and quantitative determination of oil and water content in core samples. The method measures the average fluid/dry-core-weight ratio along the path traversed by the fast neutrons, regardless of the object’s shape, thickness or distribution. In principle the entire length of an intact core, within its protective sleeve can be scanned along the core length, providing information about the content distribution. The fluid weightfractions in the interrogated sample are determined independently, thus the ratio of oil-to-rock weights is independent of the water content. The FNRT method permits determining the fluid weight-fractions in any type of cores including tight shales, clays and oil sands. As mentioned in Section 5.1 we used only a selected neutron energy region (1.7–4.2 MeV) for reconstructing the areal densities of rock formation, oil and water. For an efficient reconstruction the behaviour of the different mass attenuation coefficients should be different from each other and should vary with energy as much as possible, otherwise the information may be redundant. In addition, the contribution of hydrogen to the total attenuation coefficient of oil and water at energies below ca 4 MeV is much more significant than above that energy. On the other hand, using more energy channels improves the counting statistics. We have found that by using attenuation values at energies above 4 MeV the reconstruction procedure overestimated the formation (limestone or sandstone) areal density by 8%, underestimated oil by 10% and did not find any water. Using all energies gave correct results for the rock and oil areal densities, but still underestimated water by
6 Please cite this article in press as: D. Vartsky, et al., Determination of oil and water in drilled bore cores via fast-neutron resonance transmission radiography, Nuclear Inst. and Methods in Physics Research, A (2018), https://doi.org/10.1016/j.nima.2018.10.024.