Volume fraction detection in multiphase systems using neutron activation analysis and artificial neural network

IF 1.6 3区工程技术 Q3 CHEMISTRY, INORGANIC & NUCLEAR

Applied Radiation and Isotopes Pub Date : 2024-09-07 DOI:10.1016/j.apradiso.2024.111504

引用次数: 0

Abstract

This study presents an application of an Artificial Neural Network (ANN) to detect fluids in an annular flow regime using Prompt-Gamma Neutron Activation Analysis (PGNAA). The ANN was trained using gamma-ray spectra resulting from neutron interactions with chemical elements found in fluids typical of multiphase flow in oil exploration. These spectra were generated through mathematical simulation using the MCNP6 Monte Carlo computer code to model nuclear particle transport. A²⁴¹Am-Be polyenergetic neutron source was simulated for these calculations. Several combinations of fluid fractions were developed to create a dataset used for both training and evaluation of the ANN. The ANN demonstrated robust generalization capabilities by accurately predicting the volume fraction of the three investigated fluids (saltwater, oil, and gas), even for cases not included in the training phase. The combination of ANN and PGNAA proved effective for analyzing multiphase systems, with over 92% of all showing errors of less than 5%.

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利用中子活化分析和人工神经网络检测多相系统中的体积分数

本研究介绍了人工神经网络（ANN）在环流机制中使用即时伽马中子活化分析（PGNAA）检测流体的应用。人工神经网络是利用中子与石油勘探中典型多相流流体中的化学元素相互作用产生的伽马射线光谱进行训练的。这些光谱是通过使用 MCNP6 蒙特卡洛计算机代码进行数学模拟生成的，以模拟核粒子传输。这些计算模拟了 241Am-Be 多能中子源。开发了几种流体分数组合，以创建用于训练和评估 ANN 的数据集。通过准确预测三种调查流体（盐水、石油和天然气）的体积分数，方差网络展示了强大的泛化能力，即使是在训练阶段未包含的情况下也是如此。事实证明，方差网络和 PGNAA 的组合可有效分析多相系统，其中 92% 以上的误差小于 5%。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Applied Radiation and Isotopes 工程技术-核科学技术

CiteScore

3.00

自引率

12.50%

发文量

406

审稿时长

13.5 months

期刊介绍： Applied Radiation and Isotopes provides a high quality medium for the publication of substantial, original and scientific and technological papers on the development and peaceful application of nuclear, radiation and radionuclide techniques in chemistry, physics, biochemistry, biology, medicine, security, engineering and in the earth, planetary and environmental sciences, all including dosimetry. Nuclear techniques are defined in the broadest sense and both experimental and theoretical papers are welcome. They include the development and use of α- and β-particles, X-rays and γ-rays, neutrons and other nuclear particles and radiations from all sources, including radionuclides, synchrotron sources, cyclotrons and reactors and from the natural environment. The journal aims to publish papers with significance to an international audience, containing substantial novelty and scientific impact. The Editors reserve the rights to reject, with or without external review, papers that do not meet these criteria. Papers dealing with radiation processing, i.e., where radiation is used to bring about a biological, chemical or physical change in a material, should be directed to our sister journal Radiation Physics and Chemistry.