Development of mixed field radiation detection techniques for oil and gas well logging.

2018年1月，由NuSec主持的研讨会发布了一份报告，其中强调了在测井中开发替代检测和数据解释方法的必要性。谢菲尔德大学的探测器开发小组在包括Muon、中子和伽马在内的一系列粒子的探测器开发方面有着长期的记录。我们最近在STFC支持下开发用于水分监测的中子敏感探测器的工作，在制造内部正在开发的中子敏感箔方面产生了新的专业知识。这一新能力与之前用于CCS监测的钻孔探测器原型方面的专业知识并驾齐驱。此外，由于与LabLogic的长期合作关系，我们可以使用闪烁体制造设施，从而缩短周转原型和开发周期。加上我们的一系列中子源(脉冲DT、AMBE、252Cf)，这使我们处于独特的地位，能够开发低成本的塑料闪烁体和基于中子敏感箔的探测系统，用于井下配置。在学生期间，我们打算探索使用掺杂不同材料的闪烁体块来生产能够安装在标准井眼下的精细分段辐射探测器的可能性。与标准方法相比，这种方法有几个优点，例如：-使用位置敏感检测/符合来使用覆盖混合场的单个检测器。因此，不需要许多不同类型的探测器的现场专业知识；-部署由许多类似堆叠的“模块”或“块”组成的精细分段探测器意味着系统具有冗余；-从初始中子发生器脉冲到探测中子/伽马的时间可以提供在使用放射源时无法获得的额外的细粒度信息。例如，伽马测井几乎被用作定性测量。同样，中子孔隙度测量需要进一步校准才能有效。包括脉冲发生器和相关的颗粒检测产生补充信息，然而，这是以额外的处理时间和培训为代价的。对此的解决方案是使用机器学习来提取感兴趣的量，例如，在初始发电机脉冲之后在选通窗口中观察到的来自钻孔探测器的总检测到的中子/伽马计数将用作诸如神经网络的多变量分析(MVA)方法的适当输入。这样的MVA可以通过模拟来训练，以提取相关的兴趣量。虽然钻孔探测器是该应用的主要硬件焦点，但公认的是，塑料闪烁体与中子敏感箔的融合可以在诸如环境监测和核工业的其他应用领域中提供机会，因此，预计项目产出将包括一个可操作的钻孔探测器原型，并与“标准”(如3He)方法进行经验比较，以及用于信号识别的基于MVA的软件工具。

The NuSec-mediated workshop in January 2018 produced a report in which the need to develop alternative detection and data interpretation methods in well logging was highlighted.The detector development group at the University of Sheffield has a long track record of detector development for a range of particles including muons, neutrons and gammas. Our recent STFC-supported work on the development of neutron-sensitive detectors for water content monitoring has resulted in new expertise in the fabrication of neutron- sensitive foils being developed in house. This new capability sits alongside previous expertise in prototyping borehole detectors for CCS monitoring. Furthermore, due to a long-standing relationship with LabLogic we have access to a scintillator fabrication facility enabling short turnaround prototyping and development cycles. Along with our range of neutron sources (pulsed DT, AmBe, 252Cf) this places us in a unique position to be able to develop low-cost plastic scintillator and neutron-sensitive foil based detection systems for application in borehole configurations.Via the studentship, we intend to explore the possibility of using scintillator blocks doped with different materials to produce finely segmented radiation detectors that can fit down a standard borehole. There are several advantages to this approach over standard methods, e.g.:- use of a single detector that covers mixed fields using position-sensitive detection/ coincidence. On-site expertise in many different detector types is thus not required;- deployment of a finely segmented detector made of many similar stacked "modules"or "blocks" means the system has built in redundancy;- the time from initial neutron generator pulse to detection of neutrons/gammas canprovide additional fine grained information not available when using radiological sources.A further issue with current well logging technologies, as noted in papers, is the analysis of data. Gamma logs, e.g., are used as almost a qualitative measure. Similarly, neutron porosity measurements require further calibration to be effective. The inclusion of pulsed generators and associated particle detection yields supplementary information, however, this is at the cost of additional processing time and training. A solution for this is to use machine learning to extract quantities of interest, e.g. the total detected neutron/gamma counts from a borehole detector observed in a gated window after the initial generator pulse would serve as suitable input to a multivariate analysis (MVA) method such as a neural network. Such an MVA could be trained, via simulations, to extract relevant quantities of interest. These simulations could then be experimentally validated using a scenario in which a detector is placed in parallel with the Sheffield DT source and surrounded by volume of material (e.g. soil and/or rock) of known properties.Whilst the borehole detector is the primary hardware focus of this application it is acknowledged that the fusion of plastic scintillator with neutron-sensitive foils may afford opportunities in other application areas such as environmental monitoring and the nuclear industry, where alternative format detectors employing the same underlying technology may be of interest.The project output is therefore expected to comprise an operational borehole detector prototype with empirical comparisons with "standard" (e.g. 3He) methods as well as MVA-based software tools for signal discrimination.