Computer Simulation of Two Nuclear Well Logging Methods

1981 ◽  
Vol 21 (03) ◽  
pp. 315-322 ◽  
Author(s):  
Harry D. Smith ◽  
Ward E. Schultz

Abstract Monte Carlo techniques have been used to simulate the response of a multi window natural gamma ray spectral log to varying borehole conditions and to investigate the potential of a porosity logging concept using a ratio of fast to epithermal neutrons. Introduction There are many situations in nuclear well logging research when it would be highly desirable to have a theoretical method of realistically simulating the measurements made by a downhole logging instrument. In the early stages of research into the feasibility of a logging concept, it would be possible to make an accurate theoretical determination of whether the idea should be pursued. Should the concept turn out to be unsound, the expense and time required to design, build, and test a logging system would be avoided. In later stages of log development, the theoretical model could be used to assist in optimizing sonde design and specifications. In situations where a logging device already has been developed fully, such a model also could be used to ascertain much information about the way the physical device works. As an illustration, a theoretical simulation of a neutron (n, ?) logging sonde could provide information regarding the relative importance of the gamma rays scattered into the detector from the various downhole materials (Le., toolcase, borehole fluid, formation, cement, and well casing). The depth of investigation into the formation and the significance of neutrons in the gamma ray detector could be estimated also. Few of these parameters could easily be determined experimentally. Monte Carlo radiation transport techniques,1,2 which long have been used by scientists involved in nuclear reactor shielding design and radiation dosimetry, perhaps provide the best methods for fulfilling the theoretical nuclear logging objectives mentioned. Several papers in this area have been published.3–6 Our paper briefly describes both the Monte Carlo method and the specific Monte Carlo computer programs - SAM-C7 and an updated version SAM-CE8 - which we have been using in nuclear logging applications. Two specific illustrations are discussed. The first example involves the simulation of a natural gamma ray spectral logging device. Monte Carlo results are presented which indicate that significant errors can be introduced into the elemental concentrations obtained from these instruments unless compensations are made for differing borehole conditions. The second example describes how we have used Monte Carlo program SAM-CE to simulate an untested porosity logging technique that uses a ratio of fast to epithermal neutrons. The sensitivity and linearity of this ratio to changes in porosity were determined from the program, as were the effects of changing matrix type. These results then are compared with calculations simulating a conventional dual-spaced epithermal porosity measurement under identical lithologic conditions. The two examples presented in this paper involve relatively simple geometries to facilitate concept comprehension by the reader. Much more complex geometries also are well within the capabilities of SAM-CE or other current Monte Carlo programs.

2021 ◽  
Author(s):  
David Breitenmoser

<p>The objective of this work is to simulate the spectral gamma-ray response of NaI(Tl) scintillation detectors for airborne gamma-ray spectrometry (AGRS) using Monte Carlo radiation transport codes. The study is based on a commercial airborne gamma-ray spectrometry detector system with four individual NaI(Tl) scintillation crystals and a total volume of 16.8 l. Monte Carlo source-detector simulations were performed in an event-by-event mode with the commercial multi-purpose transport codes MCNP6.2 and FLUKA. Validation measurements were conducted using <sup>241</sup>Am, <sup>133</sup>Ba, <sup>60</sup>Co, <sup>137</sup>Cs and <sup>152</sup>Eu radiation sources with known activities and source-detector geometries. Energy resolution functions were derived from these measurements combined with additional measurements of natural Uranium, Thorium and Potassium sources. The simulation results are in good agreement with the experimental data with a maximum relative error in the full-energy peak counts of 10%. In addition, no significant difference between the two Monte Carlo radiation transport codes was found with respect to a 95% confidence level. The validated detector model presented herein can be adopted for angular detector response analysis and calibration computations relating radionuclide activity concentrations with spectral detector counts.</p>


2004 ◽  
Vol 218 ◽  
pp. 419-420
Author(s):  
P. Leung ◽  
K. S. Cheng ◽  
L. Zhang ◽  
Z. J. Jiang

We use Monte Carlo techniques to simulate the statistical properties of rotation-powered pulsars in the Gould Belt. The gamma-ray properties of these pulsars are calculated by using a self-consistent outer gap model and other pulsar properties, i.e., initial magnetic field and period, and velocity distribution of the neutrons stars at birth, are obtained from the statistics of radio pulsars. We obtain distributions of the magnetic inclination angle, period, distance and age for these gamma-ray pulsars in the Gould Belt.


Mathematics ◽  
2021 ◽  
Vol 9 (11) ◽  
pp. 1176
Author(s):  
Jie Hu ◽  
Guangzheng Jiang ◽  
Yibo Wang ◽  
Shengbiao Hu

The thermal conductivity of a stratum is a key factor to study the deep temperature distribution and the thermal structure of the basin. A huge expense of core sampling from boreholes, especially in offshore areas, makes it expensive to directly test stratum samples. Therefore, the use of well logging (the gamma-ray, the neutron porosity, and the temperature) to estimate the thermal conductivity of the samples obtained from boreholes could be a good alternative. In this study, we measured the thermal conductivity of 72 samples obtained from an offshore area as references. When the stratum is considered to be a shale–sand–fluid model, the thermal conductivity can be calculated based on the mixing models (the geometric mean and the square root mean). The contents of the shale and the sand were derived from the natural gamma-ray logs, and the content of the fluid (porosity) was derived from the neutron porosity logs. The temperature corrections of the thermal conductivity were performed for the solid component and the fluid component separately. By comparing with the measured data, the thermal conductivity predicted based on the square root model showed good consistency. This technique is low-cost and has great potential to be used as an application method to obtain the thermal conductivity for geothermal research.


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