可控中子源中子-伽马测井仪中屏蔽结构的优化

本文设计了一种使用遗传算法调用蒙特卡罗计算软件MCNP的方案,用以优化设计中子-伽马测井仪中的屏蔽结构。以D-D聚变中子源和BGO探测器为研究对象,以最小化探测器内的辐照本底为优化目标,设计出了3种不同厚度的屏蔽结构。模拟结果表明,这些屏蔽结构具有优异的屏蔽性能,可有效地降低探测器中的辐射本底。

An optimization of shielding structure in controllable neutron sourceneutron-gamma well logging instrument

Neutron-gamma well logging instrument based on controllable neutron sources is widely used in the exploration of petroleum,shale gas and minerals.During the well logging process,neutron is emitted from neutron source and interacts with the surrounding stratum’s elements.Thus,the specific gamma rays are generated and detectors within the well logging instrument can detect them.After analyzing the spectrum of gamma rays,the component of the stratum can be obtained.However,part of neutrons and gamma rays may go through the shielding structure and reach into the detector.These particles can introduce noise signals into the exploration result and reduce the accuracy of the instrument.Thus,it is important to develop an efficient shielding structure to reduce the flux of neutron and gamma rays which may induce the noise.For this purpose,a method employed genetic algorithms and MCNP code was established to develop the shielding structure.As a typical case,the D-D fusion neutron source and BGO detector were adopted in this study.Three shielding structures with different thickness were obtained.The results showed that,these shielding structures have the better performance than the common shielding structures.