测井网络路由器的研究与实现

为满足测井数据传输的实时性和可靠性要求,提出了轻量级的路由器设计方案.将点到点协议的状态机精简为3个状态和5个事件,缩小了逃逸字符的数量.路由缓存管理采用了最长首部对齐的预分配策略和减少搬移缓存数据的方法,设计了线性静态路由表的查找方法,并以数字信号处理器的定时器驱动和直接存储器访问方式快速处理缓存数据.试验结果表明,该轻量级路由器开销小,转发延迟和延迟抖动小,满足测井网络的需要.

新世纪的测井技术——网络测井及其技术体系初探

测井技术正面临着新的变革。基于互联网技术的第五代测井数据采集系统以快速、可靠、信息共享为主要特征 ,正在形成之中。相应的井下仪器提供的观测信息应该适合网络技术和油藏实时解决方案的要求。一些有深刻物理背景的、能够快速提供地层流体和地质信息的方法 ,在网络测井中一定会得到进一步重视和发展。核磁共振、阵列感应、声电成像、交叉偶极声波、脉冲中子、过套管电阻率以及电缆地层测试和井壁取心等方法 ,为勘探和开发阶段的油藏解决方案提供丰富的岩石物理和油气信息 ,将成为新一代测井技术中不可缺少的重要方法。第一次正式提出网络测井新概念 ,初步探讨新一代测井技术体系 ,包括基于互联网的测井数据采集、流体识别和储层评价系统。较为详细地讨论了以核磁共振为核心的裸眼井油气识别和评价技术。

网络测井技术及其发展趋势

伴随互联网技术的发展，以互联网技术为基础的网络测井正在形成。其主要特征是快速、可靠、信息共享。网络测井将实现信息的实时共享和指令的多向传递并将真正实现油藏解决方案的动态化。一些有深刻物理背景的、能够快速提供地层流体和地质信息的方法在网络测井中会得到进一步重视和发展。世界上几个著名的油田服务公司，正在努力实现新技术的转型，斯伦贝谢、贝克阿特拉斯和哈里伯顿公司等从20世纪90年代末即已开始概念设计。本文介绍了网络测井的数据采集系统、总结出了其优点并预测了发展趋势，认为网络测井将成为新一代测井技术中不可缺少的重要方法。

NDLS-3000网络双测井系统解决声感并测干扰的方法

声感并测时,特别是测高阻地层或遇到测井电缆性能不好时,声波同步对中感应、八侧向曲线存在严重的干扰。NDLS-3000网络双测井系统为了解决声感并测干扰,通过应用可控定时采样和间隔可控声波同步技术,改变了直流板采样方式和声波板声波同步产生方式,在满足采样精度要求的情况下,获得了最佳的并测效果。

声波测井中几个重要问题的探讨

声波测井传输网络考虑了声源与接收器的电-声、声-电传输特性对测井信号的影响,使得测井信号能够更准确地反演所测量的地层。利用阵列测井仪可大大提高测井声信号的首波幅度,利用特殊的数字信号处理算法可将淹没在强噪声背景中的弱测井信号的首波信号提取出来。在提高首波幅度的同时,进一步考虑了实际声波测井仪中使用的薄圆管压换能器的指向性对测井信号的影响,提出了优化设计薄圆管压换能器的方法。

ACME测井采集控制管理平台开发与应用

ACME测井采集控制管理平台是基于Windows平台的测井实时采集软件,具有高度可靠的多通道数据采集、开放式底层平台、可视化测井服务配置、丰富的数据显示、便捷的仪器挂接等特点,可满足常规测井、成像测井、工程测井、生产测井等多种测井服务需求。软件分层设计,具备分布式的网络数据传输功能,能够实现现场采集处理解释的一体化。

ACME测井采集控制管理平台探析

ACME测井采集控制管理平台通过分层设计软件,使得网络数据能够进行分布式的传输。该软件是在Windows平台基础上得以实现的,它建立有开放式的测井平台,能够通过多个通道采集完整可靠丰富的数据并通过可视化系统配置得以显示,在石油工程测井采集工作中,能够很好地实现各种工程的、常规的、生产的、成像的测井服务要求。

正在兴起的网络测井技术及其发展趋势

伴随互联网技术的发展,以互联网技术为基础的网络测井正在兴起。其主要特征是快速、可靠、信息共享。网络测井将实现信息的实时共享和指令的多向传递并将真正实现油藏解决方案的动态化。一些有深刻物理背景、能够快速提供地层流体和地质信息的方法在网络测井中会得到进一步重视和发展。世界上几个著名的油田服务公司正在努力实现新技术的转型,斯伦贝谢、贝克阿特拉斯和哈里伯顿公司等从20世纪90年代末即已开始概念设计。

Backpropagation neural network method in data processing of ultrasonic imaging logging-while-drilling

The existing methods for extracting the arrival time and amplitude of ultrasonic echo cannot eff ectively avoid the local interference of ultrasonic signals while drilling,which leads to poor accuracy of the echo arrival time and amplitude extracted by an ultrasonic imaging logging-while-drilling tool.In this study,a demodulation algorithm is used to preprocess the ultrasonic simulation signals while drilling,and we design a backpropagation neural network model to fit the relationship between the waveform data and time and amplitude.An ultrasonic imaging logging model is established,and the finite element simulation software is used for forward modeling.The response under diff erent measurement conditions is simulated by changing the model parameters,which are used as the input layer of the neural network model;The ultrasonic echo signal is considered as a low-frequency signal modulated by a high-frequency carrier signal,and a low-pass fi lter is designed to remove the high-frequency signal and obtain the low-frequency envelope signal.Then the amplitude of the envelope signal and its corresponding time are extracted as an output layer of the neural network model.By comparing the application eff ects of the various training methods,we fi nd that the conjugate gradient descent method is the most suitable method for solving the neural network model.The performance of the neural network model is tested using 11 groups of simulation test data,which verify the eff ectiveness of the model and lay the foundation for further practical application.

Monitoring Efficiency Evaluation of the Well-water-level Observation Network in China

In order to understand the monitoring efficiency status of the well-water-level observation network in China after the completion of the 10 th "Five-year Plan " digital network project,and to provide a basis for the future network optimization and equipment updating, the monitoring efficiency of the well-water-level observation network was evaluated. On the whole,61. 8% observing stations have good monitoring effectiveness,the observation environment of 73. 5% of observing stations meets the monitoring requirements of well-water-level. The operation status of the network is as a whole getting better,operation rates of 75% observing instruments are above 95%. Most well water levels can monitor crustal stress changes and seismic activities. However,some observation stations,due to inherent deficiency in wells,environmental disturbance,instrument aging,and low-level operation and maintenance,need to improve the monitoring efficiency level by taking measures such as observation environment improvement,equipment updating,and management training. About 6. 5% of the stations need to stop observation due to the unqualified observational environment.

Neural network forecasting model based on phase space re-construction in water yield of mine

The neutral network forecasting model based on the phase space reconstruction was proposed. First, through reconstructing the phase space, the time series of single variable was done excursion and expanded into multi- dimension series which included the ergodic information and more rich information could be excavated. Then, on the basis of the embedding dimension of the time series, the structure form of neutral network was constructed, of which the node number in input layer was the embedding dimension of the time series minus 1, and the node number in output layers was 1. Finally, as an example, the model was applied for water yield of mine forecasting. The result shows that the model has good fitting accuracy and forecasting precision.

Experimental study on f-ω regulation model under abnormal methane emission

In view of the difficulty of automatic adjustment, the recovery lag and the major accident potential of the mine ventilation system, an experimental model of the pipe net was established according to the typical one mine and one working face ventilation system of Daliuta coal mine. Using the best uniform approximation method of Chebyshev interpolation to fit the fan performance curve, we experimentally determined fan characteristics with different frequencies and establish the data base for the curves. Based on ventilation network monitoring theory, we designed a monitoring system for ventilation network parameter monitoring and fan operating frequency automatic control. Using the absolute methane emission quantity to predict the air quantity requirement of branch and fan frequency, we established a f-ω regulation model based on fan frequency and absolute methane emission quantity. After analysing methane emission and distribution characteristics, using CO_2 to simulate the methane emission characteristics from a working face, we verified the correctness and rationality of the f-ω regulation model. The fan operation frequency is adjusted by the method of air adjustment change with methane emission quantity and the curve searching method after determining air quantity requirements. The results show that the air quantity in a branch strictly changes according to the f-ω regulation model, in the airincreasing dilution by fan frequency regulation, the CO_2 concentration is limited to the set threshold value. The paper verifies the practicability of a frequency regulation system and the feasibility of the frequency adjustment scheme and provides guidance for the construction of automatic frequency conversion control system in coal mine ventilation networks.

NDLS—3000配接GR—DEV—Rmg—Rmn—CAL组合仪

首先简单介绍NDLS-3000的特点和华北油田砂泥岩剖面测井项目，分析其他组合测井所存在的问题，再详细说明在NDLS-3000网络双测井系统上配接GR-DEV-Rmg-Rmn-CAL组合仪的方法，包括井下仪器的连接方法和组合测井软件的编制与使用方法。