睿眼综合录井仪溢流模拟测试系统研究与设计

发布时间：2019-07-06 06:26

【摘要】：睿眼综合录井仪是西南石油大学与川庆钻探地研院合作研发的具有综合录井和试油录井等功能的智能化系统,是软硬件系统高度相容形成的测量仪器。调试新生产的录井仪本身具有很大的难度,特别是综合调试时,人们需要将录井仪运输到录井现场进行现场调试,现场调试费用昂贵并且妨碍现场生产。随着钻井技术快速发展,新型录井仪的软硬件研发速度由于以上原因跟不上钻井技术发展速度,使综合录井仪发展前景面临诸多问题。故项目组开展以解决新型录井仪软件硬件的研发和调试周期长等问题为目的的课题研究,本课题即是安排设计一种这样的原型系统。本系统根据溢流发生的原理,设计了溢流发生的规则模型,通过运用云模型的数据源生成算法,依托溢流规则模型生成钻井过程中的各种表现溢流的数据。根据软件功能性测试方法构建测试序列,通过多路径随机测试实现对溢流预警模型有针对性的测试,直接检验溢流预警模型是否有效。基于遗传算法的启发式搜索特性测试录井仪上新开发的溢流预警软件系统的全面性。启发式搜索相比于随机测试能更有效的找到溢流预警软件系统的功能性漏洞。同时以睿眼录井仪和实际的录井环境为背景,通过制作模拟器对录井现场的传感器信号进行模拟。模拟器实现了对4-20mA电流信号和大电压脉冲信号的模拟,为录井仪提供实质的信号源,可以模拟真实录井环境,用于测试录井仪。系统通过设计云模型推理机为录井仪硬件采集通道和录井仪系统软件标定提供诊断测试。最后论文对系统进行了实验验证,实验结果表明,通过Max538进行DA转换,配合AD694进行VI转换能实现4-20mA信号源发生,通过Lm358能实现电压脉冲信号模拟。通过实验测试,也验证了云模型数据源产生方法、多路径随机测试方法和遗传算法测试溢流方法可行,说明了原型系统研究设计合理,但是还需优化和对参数的调整。论文研究设计的系统完善后应用于录井仪调试、测试和开发具有良好的发展前景和经济效益。
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[Abstract]:Rui eye comprehensive logging tool is an intelligent system with the functions of comprehensive logging and oil testing logging, which is developed by Southwest Petroleum University and Chuanqing drilling Research Institute. It is a highly compatible measuring instrument formed by software and hardware systems. It is very difficult to debug the newly produced logging tool itself, especially when the logging tool is comprehensively debugged, people need to transport the logging tool to the logging site for on-site debugging, which is expensive and hinders the field production. With the rapid development of drilling technology, the research and development speed of software and hardware of the new logging tool can not keep up with the development speed of drilling technology because of the above reasons, which makes the development prospect of comprehensive logging tool face many problems. Therefore, the project team carries out the research to solve the problems of the research and development of the software and hardware of the new logging tool and the long debugging cycle, and this topic is to arrange and design such a prototype system. According to the principle of overflow occurrence, the rule model of overflow occurrence is designed in this system. By using the data source generation algorithm of cloud model, all kinds of overflow data in drilling process are generated by using overflow rule model. According to the software functional test method, the test sequence is constructed, and the overflow early warning model is tested by multi-path random test, and the effectiveness of the overflow early warning model is directly verified. The heuristic search characteristic based on genetic algorithm is used to test the comprehensiveness of the newly developed overflow early warning software system on the logging tool. Heuristic search can find the functional vulnerability of overflow early warning software system more effectively than random test. At the same time, based on the Rui hole logging tool and the actual logging environment, the sensor signal in the logging site is simulated by making a simulator. The simulator realizes the simulation of 4-20mA current signal and high voltage pulse signal, provides a substantial signal source for logging tool, and can simulate the real logging environment, which can be used to test logging tool. The system provides diagnostic test for hardware acquisition channel of logging tool and software calibration of logging tool system by designing cloud model inference engine. Finally, the experimental results of the system are verified by experiments. The experimental results show that the 4-20mA signal source can be realized by DA conversion with AD694 and VI conversion by AD694, and the voltage pulse signal can be simulated by Lm358. The experimental results also verify the feasibility of cloud model data source generation method, multi-path random test method and genetic algorithm test overflow method, which shows that the research and design of the prototype system is reasonable, but it still needs to be optimized and adjusted. The system studied and designed in this paper has a good development prospect and economic benefit after being applied to the debugging, testing and development of logging tools.
【学位授予单位】：西南石油大学
【学位级别】：硕士
【学位授予年份】：2015
【分类号】：TE927.9

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