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H. Nguyen, J. Campbell, G. Couchell, S. Li, D. Pullen, W. Schier, E. Seabury, S. Tipnis (1996)
Programs in C for parameterizing measured 5″ × 5″ NaI gamma response functions and unfolding of continuous gamma spectraComputer Physics Communications, 93
H. Murrieta, E. Muñoz, E. Adem, G. Burillo, M. Vazquez, E. Cabrera (1996)
Effect of irradiation dose, storage time and temperature on the ESR signal in irradiated oat, corn and wheat.Applied radiation and isotopes : including data, instrumentation and methods for use in agriculture, industry and medicine, 47 11-12
(2006)
Monte Carlo simulation of gamma spectra
I. Motoc, W. Bruns (1981)
The Monte Carlo Method and Applications
L. J. Huang (1985)
The Principle of Radioactive Logging
Pang Ju-feng (2005)
New Analyzing Method & Software and Applications of Enelastic Spectra from C/O Spectrometry LogNuclear Physics Review
F. Al-Ghorabie (2006)
Development of a computer code using the EGS4 Monte Carlo simulation system to evaluate the response of a NaI(Tl) detector to photons with energies below 300 keV.Applied radiation and isotopes : including data, instrumentation and methods for use in agriculture, industry and medicine, 64 1
J. A. Grau, J. S. Schweitzer (1989)
Elemental concentrations from thermal neutron capture gamma-ray spectra in geological formationsNuclear Geophysics, 3
J. A. Grau (1989)
1Nuclear Geophysics, 3
(2002)
MCNP modeling Applied Radiation and Isotopes
S. Chapman (1987)
27The Technical Review, 35
R. Hertzog, L. Colson, O. Seeman, M. O’Brien, H. Scott, D. Mckeon, P. Wraight, J. Grau, D. Ellis, J. Schweitzer, M. Herron (1989)
Geochemical Logging With Spectrometry ToolsSpe Formation Evaluation, 4
Li Min (2006)
Analytical Methods With Neutron-Gamma Ray Spectrometry From Formation ElementsJournal of Isotopes
(1987)
The emergence of geochemical well logging
L. C. Pei, X. Z. Zhang (1980)
The Monte Carlo Method and Its Application in Particle Transport
J. Grau, J. Schweitzer, R. Hertzog (1990)
Statistical uncertainties of elemental concentrations extracted from neutron-induced gamma-ray measurementsIEEE Transactions on Nuclear Science, 37
J. Grau, J. Schweitzer (1989)
Elemental concentrations from thermal neutron capture gamma-ray spectra in geological formationsThe International journal of radiation applications and instrumentation. Part E. Nuclear geophysics, 3
Hu-Xia Shi, Bo-Xian Chen, T. Li, D. Yun (2002)
Precise Monte Carlo simulation of gamma-ray response functions for an NaI(Tl) detector.Applied radiation and isotopes : including data, instrumentation and methods for use in agriculture, industry and medicine, 57 4
P. Hendriks, M. Maučec, R. Meijer (2002)
MCNP modelling of scintillation-detector gamma-ray spectra from natural radionuclides.Applied radiation and isotopes : including data, instrumentation and methods for use in agriculture, industry and medicine, 57 3
(1989)
Geochemical logging with spectrometry
for its interpretation. Since the standard element spectra are usually derived using Monte Carlo simulation RIHLWKHUDSXUHHOHPHQWRULWVR[LGHZHV\QWKHVL]HGWKHVWDQGDUGQHXWURQFDSWXUHGȖVSHFWUDDVZRXOG be observed using a NaI(Tl) detector) of elements H, Si, Ca and Fe from each element and its oxide. To compare the standard spectra from the elements and oxides, we operated three simulations of sandstone, limestone and mixed formation of sandstone and limestone each with ten different porosities, and used the two kinds of standard spectra to analyze the mixed spectra modeled from sandstone and limestone formations. The results show that the standard element spectra from oxides have more prominent energy peaks than the standard spectra from pure elements. The calculated formation element contents are close to the theoretical values when the standard element spectra from oxides are used to analyze the formation mixed spectra. Therefore, the formation element standard spectra should be calculated from oxide models in the analysis of neutron captured Ȗ spectra by logging tools. Standard spectrum, spectrum analysis, neutron captured Ȗ spectrum, formation element Key words: 1 Introduction 2 Numerical simulation model Multi-element spectrum logging can effectively identify The calculation model is a cylinder with a height of 1 m lithology and mineralogy in formations, and plays an and a radius of 70 cm, as shown in Fig. 1. The diameter of important role in exploring complex reservoirs (Hertzog et al, the logging tool with a pulsed neutron source is 45 mm. The 1989; Chapman et al, 1987; Grau and Schweitzer, 1989; Grau source emits 14 MeV neutrons into the formation with a pulse et al, 1990). Accurate and effective full spectrum analysis ZLGWKRIȝVDQGDSHULRGRIȝV7KHUHLVD1D,7O LVRQHRIWKHNH\WHFKQRORJLHVLQIXOOVSHFWUXPFDSWXUHGȖ detector 40 cm away from the source and the detector is 10 logging, and the spectrum analysis method requires simulated cm in length and 4 cm in diameter. The tool is pressed closely VWDQGDUGFDSWXUHGȖVSHFWUDRIPDMRUIRUPDWLRQHOHPHQWV up against one side of the borehole. The space between the There are two ways to acquire standard element spectra, VRXUFHDQGWKHGHWHFWRULV¿OOHGZLWKVKLHOGLQJPDWHULDO7KH one is instrument measurement in a standard calibration detector responses are considered in the calculation. model, and the other is numerical simulation (Nguyen et al, 1996; Al-Ghorabie, 2006; Shi et al, 2002; Xiang and Guo, 2006). As numerical simulation can not completely take the real tool and well conditions into account, it is better to obtain Borehole the standard spectra with a spectrum tool in a model well. Owing to a variety of reasons, almost all publications do not describe elements or compounds used to synthesize standard element spectra in the model well. Generally, either a pure Detector element or its oxide can be used to obtain standard element spectra by Monte Carlo modeling. With the Monte Carlo numerical simulation program MCNP(5C) (Pei and Zhang, 1980), we studied the differences Formation of spectrum analysis using standard spectra calculated either from pure elements or their oxides. Source *Corresponding author. email: wwsheng@yahoo.com.cn Received January 5, 2012 The calculation model Fig. 1 464 Pet.Sci.(2012)9:463-468 A two-step simulation is used in the calculation. First is interact with the atoms of the materials behind the detector the simulation for neutrons. When photons are generated, IHFW &RPSWRQDQGHIWKHUHVXOWDQWEDFNVFDWWHUHGȖUD\VDUULYH the position where photons are generated is treated as the back at the detector, are detected and form the backscattered departure position. The energy and motion direction of the low-energy peak. As well, backscattered photons produced photons are determined by random sampling of the known in shielding materials also contribute to the backscattered energy distribution and motion direction distribution, thus peak. The energy of backscattered photons is always around the second step simulation begins (Hendriks et al, 2002). 200 keV, so it is easy to identify the backscattered peak in the The advantages of this two-step simulation are significant spectrum. whole energy, single escape and double escape peaks, short 3.2 The simulation for the formation filled with computation time, and low calculation error generally less element oxide than 0.1%. Considering the element in the strata is not a pure element, 3 The simulation for standard element but an oxide form, for example, element H occurs as H O, and Si occurs as SiO O, spectra in formation 2 2 SiO , CaCO , and FeO, and the calculated captured Ȗ spectra 2 3 are shown in Fig. 3. 7KHVLPXODWLRQIRUWKHIRUPDWLRQ¿OOHGZLWKHSXU elements With the above calculation model and calculation 100 techniques, the next most critical step is filling the element H O in the model for standard spectrum simulation. Since the 2 standard element spectrum is the detector response of the logging tool to a transient nuclear reaction of atomic nuclei SiO in the borehole, pure substances are first considered to be CaCO filled in the model to simulate element standard spectra. In computation, the pure element in the model is respectively H, 0.1 FeO in Fig. 2. The inelastic scattered gamma counts are deducted from the captured spectra counts in Fig. 2. Because the 0.01 spectra are obtained between two neutron pulses, the spectra LQWKH¿JXUHDUHDOPRVWIUHHIURPWKHLQÀXHQFHRIDFWLYDWLRQ 0 24 6 8 gamma rays. Energy, MeV &DSWXUHGȖVSHFWUDRIWKHR[LGHVRI+6L&DDQG)H Fig. 3 10 Ca To compare the differences of spectra in Fig. 2 and Fig. 3, the spectra of Si and SiO are taken as an example shown Si in Fig. 4. Fig. 4 shows that compared with the spectrum of pure element Si, the characteristic peak positions of Fe the SiO spectrum do not change but its peaks are more 0.1 prominent, especially the characteristic peak at 4.93 MeV. The characteristic peaks in the spectra of other oxides are also more prominent than those in corresponding pure element 0.01 spectra. Some small peaks in SiO spectrum are due to the presence of element O. The standard captured Ȗ spectrum 1E-3 of Si can be obtained by doing mathematical algorithm 0 1 2 345 678 processing to remove the oxygen peaks from the spectrum of SiO . EnergyMeV Fig. 2 Captured Ȗ spectra of H, Si, Ca and Fe 4 Comparison of energy spectrum analysis results Fig. 2 shows that there is a characteristic peak of H at 2.23 MeV; two whole energy peaks of Si appear at 3.54 MeV 4.1 Sandstone with different porosities and 4.93 MeV; Ca peaks are at 1.94 MeV and 6.42 MeV; Fe In order to compare the spectrum analysis results based on peaks are at 7.46 MeV and 5.92 MeV (Huang, 1985). In the the above two types of element standard spectra, it is assumed figure, the first peak on the left is the backscattered peak. that there is a sandstone reservoir with different porosities 6RPHRIWKHȖUD\VDUULYLQJDWWKHGHWHFWRUSDVVFRPSOHWHO\ from 1% to 45% corresponding to ten points, and the pore is through the detector crystal without being detected. They then Relative intensity Relative intensity 6L&DDQG)HDQGWKHFDOFXODWHGFDSWXUHGȖVSHFWUDDUHVKRZQ WKHPRGHOLV¿OOHGZLWKWKHR[LGHV+ Pet.Sci.(2012)9:463-468 465 2005; Pang and Li, 2006): Wt F y / S (2) j jj SiO Fig. 5 and Fig. 6 show the weight percentages of H and Si acquired respectively with the oxide standard spectrum and pure element standard spectrum. The x-axis indicates 0.1 Si the theoretical composition of the element in the formation, the y-axis represents the calculated element content, and the GLDJRQDOGDVKHGOLQHLQWKH¿JXUHGHQRWHVWKDWWKHFDOFXODWHG value is equal to the theoretical value. Fig. 5 shows that the H content obtained from a pure element standard spectrum is higher than the corresponding 0.01 theoretical value. The content of H based on oxide standard 02 4 6 spectrum is lower than the corresponding theoretical value for Energy, MeV low porosities, and higher than the corresponding theoretical Fig. 4 Comparison of Si and SiO spectra 2 value for high porosities. On the whole, the analysis results using the oxide standard spectrum are closer to the diagonal ¿OOHGZLWKZDWHUDVVKRZQDEOHLQDEOH7,Q7 C and C H Si dashed line than those of the pure element standard spectrum, represent the weight percentage of H and Si respectively, and which demonstrates that spectrum analysis with the standard ȡ is formation density. spectrum calculated from the oxide can provide a more accurate estimate of the hydrogen content. Table 1 Sandstone formation model with different porosities C C Porosity ȡ H Si b Point wt% wt% % g/cm 0.0075 1 0.01 36.70 1 2.634 2 0.06 36.12 5 2.568 0.0060 3 0.12 35.36 10 2.485 4 0.19 34.54 15 2.403 5 0.26 33.67 20 2.320 0.0045 6 0.34 32.73 25 2.238 7 0.42 31.71 30 2.155 0.0030 8 0.51 30.62 35 2.073 9 0.61 29.44 40 1.990 10 0.71 28.15 45 1.908 0.0015 Oxide standard spectrum Pure element standard spectrum The program MCNP (5C) is used to simulate the captured 0.0000 ȖVSHFWUDIRUWKHWHQSRLQWVLQDEOH7%HIRUHVSHFWUXP 0.0000 0.0015 0.0030 0.0045 0.0060 0.0075 analysis, the element standard spectra are isolated from Theoretical value the oxide spectra by mathematical processing, and these Fig. 5 Weight percentage of H based on sandstone model element standard spectra are called oxide standard spectra. The standard spectra assuming pure elements are called Fig. 6 shows that the content of Si calculated from pure element standard spectra. To conveniently perform the oxide standard spectrum is extremely close to the mathematical processing, the standard spectra and formation corresponding theoretical value, and the content derived mixed spectra are expressed as 256-dimensional vector P and from the pure element standard spectrum is lower than the the components are normalized according to Eq. (1) corresponding theoretical value. The lower the formation P 1 porosity, the higher the deviation degree. (1) Therefore, according to the spectrum analysis results in sandstone formation, the computation accuracy of element With oxide standard spectra and pure element standard content with oxide standard spectrum is better than that with spectra, a full spectrum least-square method is used to analyze pure element standard spectrum. the mixed spectra for the ten points in Table 1 and obtain the relative yields of H and Si. In order to calculate the weight 4.2 Limestone with different porosities percentage of each element with the oxide model, each point in Table 1 is calibrated to get the normalization factor F To compare the spectrum analysis results for oxide and sensitivity factor S, and then the weight percentages of standard spectrum and pure element standard spectrum, it is elements at each point are calculated by Eq. (2) (Pang et al, assumed that there is a limestone reservoir with the porosity Normalization count Calculated value 466 Pet.Sci.(2012)9:463-468 0.03 0.375 Si Oxide standard spectrum Pure element standard spectrum Pure element standard spectrum Oxide standard spectrum 0.360 0.02 0.345 0.330 0.01 0.315 0.300 0.00 0.285 0.270 0.00 0.01 0.02 0.03 0.270 0.285 0.300 0.315 0.330 0.345 0.360 0.375 Theoretical value Theoretical value Fig. 6 Weight percentage of Si based on sandstone model Weight percentage of H based on limestone model Fig. 7 from 1% to 45% corresponding to ten points, and the pores value, it is still close to it. The content of Ca from a pure DUHDOVRFRPSOHWHO\¿OOHGZLWKZDWHUDVVKRZQDEOHLQ7,Q element standard spectrum is significantly higher than the Table 2, C and C stand for the weight percentages of H and corresponding theoretical one. H Ca Ca respectively. Therefore, from the spectrum analysis results in the limestone formation, the accuracy of the element content Table 2 Limestone formation model with different porosities calculated from the oxide standard spectrum is better than that from the pure element standard spectrum. C C Porosity ȡ H Ca b Point wt% wt% % g/cm 1 0.04 31.70 1 2.693 0.32 Ca 2 0.21 31.21 5 2.625 3 0.44 30.57 10 2.539 0.30 4 0.68 29.87 15 2.454 5 0.94 29.13 20 2.368 6 1.22 28.33 25 2.283 0.28 7 1.52 27.47 30 2.197 8 1.84 26.54 35 2.112 9 2.19 25.54 40 2.026 0.26 10 2.58 24.44 45 1.941 Pure element standard spectrum Oxide standard spectrum 0.24 The analysis results with an oxide standard spectrum and 0.24 0.26 0.28 0.30 0.32 pure element standard spectrum for the mixed spectra at ten Theoretical value points in Table 2 are shown in Fig. 7 and Fig. 8. Fig. 8 Weight percentage content of Ca based on limestone model Fig. 7 shows that the intersections of calculated content of H using an oxide standard spectrum and the theoretical 4.3 Mixed formation of sandstone and limestone with content are almost all located on the diagonal line, which different porosities means the calculated value is almost the same as the theoretical one. The content of H obtained from the pure To further compare the spectrum analysis results in element standard spectrum is much lower than the theoretical complex formations with the above two types of standard one, and the higher the formation porosity, the larger the spectra, we suppose that there is a reservoir with the lithology difference between the calculated value and the theoretical of limestone and sandstone with porosity from 2% to 10% value. These show that the accuracy of H content calculated corresponding to nine points, and the formation pores are from the oxide standard spectrum is relatively high. FRPSOHWHO\¿OOHGZLWKDVZDWHUDEOHVKRZQLQ7 C , C and H Si In Fig. 8, although the content of Ca obtained from an C in Table 3 represent the weight percentages of H, Si and Ca oxide standard spectrum is slightly higher than the theoretical Ca respectively. Calculated value Calculated value Calculated value Pet.Sci.(2012)9:463-468 467 0.4 Table 3 Mixed formation model of sandstone and limestone Oxide standard spectrum Ca Pure element standard spectrum C C C Porosity ȡ Si Ca H matrix Point wt% wt% wt% % g/cm 0.3 1 0.046 0.320 0.004 10 2.433 2 0.092 0.285 0.004 9 2.454 0.2 3 0.138 0.250 0.003 8 2.475 4 0.184 0.214 0.003 7 2.496 5 0.231 0.178 0.002 6 2.517 0.1 6 0.278 0.142 0.002 5 2.539 7 0.326 0.106 0.002 4 2.560 0.0 8 0.374 0.070 0.001 3 2.581 9 0.422 0.033 0.001 2 2.602 0.0 0.1 0.2 0.3 0.4 Theoretical value Fig. 10 Weight percentage of Ca based on mixed formation Fig. 9 and Fig. 10 show the analysis results with oxide standard spectrum and pure element standard spectrum for the mixed spectra at nine points in Table 3. As shown in Fig. 9, when the content of Si is higher 5 Conclusions than 0.2, the calculated value using pure element standard The standard spectra of formation elements can be spectrum is higher than the theoretical one, and the higher calculated using either pure elements or their oxides. the content of Si, the higher the deviation degree from the Compared with the standard spectra using a pure element, theoretical value. When the content of Si is less than 0.2, the standard spectra using the oxide have more prominent the content of Si obtained from a pure element standard characteristic energy peaks. It can be seen from the analysis spectrum is lower than the theoretical value, and even results of different formation models that the element content negative. However, the intersections of the calculated content calculated with oxide standard spectrum is close to the of H using oxide standard spectra and the theoretical content theoretical value. Therefore, element standard spectra should are almost all distributed along the diagonal line, which be calculated from the oxides. means the calculated value is extremely close to the model composition. Fig. 10 shows information similar to that of Fig. Acknowledgements This paper is financially supported by National Natural 1.0 Science Foundation of China (Grant No. 41074101) and Si Science Foundation of China University of Petroleum 0.8 (Beijing) (No. KYJJ2012-05-12). 0.6 References 0.4 Al- Ghorabie F H H. Development of a computer code using the EGS4 Monte Carlo simulation system to evaluate the response of a NaI(Tl) detector to photons with energies below 300 keV. Applied Radiation 0.2 and Isotopes. 2006. 64(1): 85-92 Cha pman S, Colson J L, Everett B, et al. The emergence of geochemical 0.0 well logging. The Technical Review. 1987. 35(2): 27-35 Gra u J A and Schweitzer J S. Elemental concentrations from thermal -0.2 neutron capture gamma-ray spectra in geological formations. Nuclear Geophysics. 1989. 3(1): 1-9 Oxide standard spectrum -0.4 Gra u J A, Schweitzer J S and Hertzog R C. Statistical uncertainties of Pure element standard spectrum elemental concentrations extracted from neutron induced gamma-ray -0.4 -0.2 0.0 0.2 0.4 0.6 0.8 1.0 measurements. IEEE Transactions on Nuclear Science. 1990. 37(6): Theoretical value 2175-2178 Hen driks P H G M, Maucec M and De Meijer R J. MCNP modeling Fig. 9 Weight percentage of Si based on mixed formation RIVFLQWLOODWLRQGHWHFWRUȖUD\VSHFWUDIURPQDWXUDOUDGLRQXFOLGHV Applied Radiation and Isotopes. 2002. 57(3): 449-457 The same can be seen from the analysis results of mixed Her tzog R, Colson L, Seeman O, et al. Geochemical logging with spectrometry tools. SPE Formation Evaluation. 1989. 4(2): 153-162 formation spectra that the computation accuracy of element (SPE16792) content using the oxide standard spectrum is better than that Hua ng L J. The Principle of Radioactive Logging. Beijing: Petroleum with a pure element standard spectrum. Calculated value Calculated value 468 Pet.Sci.(2012)9:463-468 Physics Review. 2005. 22(1): 67-71 (in Chinese) Industry Press. 1985. appendix (in Chinese) Pei L C and Zhang X Z. The Monte Carlo Method and Its Application in Ngu yen H V, Campbell J M, Couchell G P, et al. Programs in C for Particle Transport. Beijing: Science Press. 1980. 5-50 (in Chinese) SDUDPHWHUL]LQJPHDVXUHGƎîƎ1D,JDPPDUHVSRQVHIXQFWLRQV Shi H X, Chen B X, Li T Z, et al. Precise Monte Carlo simulation and unfolding of continuous gamma spectra. Computer Physics of gamma-ray response functions for a NaI(Tl) detector. Applied Communications. 1996. 93(2-3): 303-321 Radiation and Isotopes. 2002. 57(4): 517-524 Pan g J F and Li M. Analytical methods with neutron-gamma ray Xia ng D and Guo L Y. Monte Carlo simulation of gamma spectra. spectrometry from formation elements. Journal of Isotopes. 2006. Journal of Mathematical Medicine. 2006. 19(3): 229-231 (in 19(2): 70-74 (in Chinese) Chinese) Pan g J F, Li M and Yan Z G. New analyzing method & software and (Edited by Hao Jie) applications of inelastic spectra from C/O spectrometry logs. Nuclear
Petroleum Science – Springer Journals
Published: Nov 21, 2012
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