1.University of Electronic Science and Technology of China, Chengdu 610000, China
* zhanqio@uestc.edu.cn
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Source-less density measurement using an adaptive neutron-induced gamma correction method[J]. 核技术(英文版), 2023,34(8):125
Qiong Zhang, Yi Ge, Yu-Lian Li. Source-less density measurement using an adaptive neutron-induced gamma correction method[J]. Nuclear Science and Techniques, 2023,34(8):125
Source-less density measurement using an adaptive neutron-induced gamma correction method[J]. 核技术(英文版), 2023,34(8):125 DOI: 10.1007/s41365-023-01274-4.
Qiong Zhang, Yi Ge, Yu-Lian Li. Source-less density measurement using an adaptive neutron-induced gamma correction method[J]. Nuclear Science and Techniques, 2023,34(8):125 DOI: 10.1007/s41365-023-01274-4.
The use of radioactive isotopes, such as Cs-137, to measure formation density is a common practice; however, it poses high risks such as environmental contamination from lost sources. To address these challenges, the use of pulsed neutron sources for density measurements, also known as "source-less density", has emerged as a promising alternative. By collecting gamma counts at different time gates according to the duty cycle of the pulsed sequence, the inelastic gamma component can be isolated to obtain more accurate density measurements. However, the collection of gamma rays during the neutron burst-on period often contains a proportion of capture gamma rays, which can reduce the accuracy of density measurements. This proportion can vary depending on the formation environment and neutron duty cycle. To address these challenges, an adaptive capture gamma correction method was developed for density measurements. This method distinguishes between "burst-on" and "burst-off" periods based on the gamma time spectra, and derives the capture ratio in the burst-on period by iteratively fitting the capture gamma time spectra, resulting in a more accurate net inelastic gamma. This method identifies the end of the pulse by automatically calculating the differential, and fits the capture gamma time spectra using Gaussian process regression, which considers the differences in formation attenuation caused by different environments. The method was verified through simulations with errors of below 0.025 g/cm,3, demonstrating its adaptability and feasibility for use in formation density measurements. Overall, the proposed method has the potential to minimize the risks associated with radioactive isotopes and improve the accuracy of density measurements in various duty cycles and formation environments.
Neutron-induced gammaAdaptive correctionSource-less density
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