Predicting formation lithology from log data by using a neural network

In order to increase drilling speed in deep complicated formations in Kela-2 gas field, Tarim Basin, Xinjiang, west China, it is important to predict the formation lithology for drilling bit optimization. Based on the conventional back propagation （BP） model, an improved BP model was proposed, with main modifications of back propagation of error, self-adapting algorithm, and activation function, also a prediction program was developed. The improved BP model was successfully applied to predicting the lithology of formations to be drilled in the Kela-2 gas field.

Design and Implementation of Log Data Analysis Management System Based on Hadoop

With the rapid development of the Internet,many enterprises have launched their network platforms.When users browse,search,and click the products of these platforms,most platforms will keep records of these network behaviors,these records are often heterogeneous,and it is called log data.To effectively to analyze and manage these heterogeneous log data,so that enterprises can grasp the behavior characteristics of their platform users in time,to realize targeted recommendation of users,increase the sales volume of enterprises’products,and accelerate the development of enterprises.Firstly,we follow the process of big data collection,storage,analysis,and visualization to design the system,then,we adopt HDFS storage technology,Yarn resource management technology,and gink load balancing technology to build a Hadoop cluster to process the log data,and adopt MapReduce processing technology and data warehouse hive technology analyze the log data to obtain the results.Finally,the obtained results are displayed visually,and a log data analysis system is successfully constructed.It has been proved by practice that the system effectively realizes the collection,analysis and visualization of log data,and can accurately realize the recommendation of products by enterprises.The system is stable and effective.

HiLog:OpenHarmony的高性能日志系统

日志是计算机系统中记录事件状态信息的的重要载体,日志系统负责计算机系统的日志生成、收集和输出.OpenHarmony是新兴的、面向全设备、全场景的开源操作系统.在所述工作之前,包括日志系统在内OpenHarmony有许多关键子系统尚未构建,而OpenHarmony的开源特性使第三方开发者可以为其贡献核心代码.为了解决Open Harmony日志系统缺乏的问题,主要开展如下工作:(1)分析当今主流日志系统的技术架构和优缺点;(2)基于OpenHarmony操作系统的异构设备互联特性设计HiLog日志系统模型规范;(3)设计并实现第1个面向OpenHarmony的日志系统HiLog,并贡献到OpenHarmony主线;(4)对HiLog日志系统的关键指标进行测试和对比试验.实验数据表明,在基础性能方面,HiLog和Log的日志写入阶段吞吐量分别为1500 KB/s和700 KB/s,相比Android日志系统吞吐量提升114%;在日志持久化方面,HiLog可以3.5%的压缩率进行持久化,并且丢包率小于6‰,远低于Log.此外,HiLog还具备数据安全、流量控制等新型实用能力.

A Real-time Lithological Identification Method based on SMOTE-Tomek and ICSA Optimization

In petroleum engineering,real-time lithology identification is very important for reservoir evaluation,drilling decisions and petroleum geological exploration.A lithology identification method while drilling based on machine learning and mud logging data is studied in this paper.This method can effectively utilize downhole parameters collected in real-time during drilling,to identify lithology in real-time and provide a reference for optimization of drilling parameters.Given the imbalance of lithology samples,the synthetic minority over-sampling technique(SMOTE)and Tomek link were used to balance the sample number of five lithologies.Meanwhile,this paper introduces Tent map,random opposition-based learning and dynamic perceived probability to the original crow search algorithm(CSA),and establishes an improved crow search algorithm(ICSA).In this paper,ICSA is used to optimize the hyperparameter combination of random forest(RF),extremely random trees(ET),extreme gradient boosting(XGB),and light gradient boosting machine(LGBM)models.In addition,this study combines the recognition advantages of the four models.The accuracy of lithology identification by the weighted average probability model reaches 0.877.The study of this paper realizes high-precision real-time lithology identification method,which can provide lithology reference for the drilling process.

基于VideoLog可视化测井的井筒深度重采样方法研究

当前,VideoLog可视化测井视频的播放的基准线是时间。油气井的深度都在几千米不等,完整地播放一口油气井的测井视频需要十几小时。在测井资料解释阶段,处理测井视频不仅复杂,还浪费了大量的时间。为了节约时间,简化测井资料解释的步骤,现提出一种测井视频以深度值为基准线进行播放索引的研究方法。该研究方法基于接箍识别和测井视频的处理,接箍识别提供接箍数据,视频处理提供视频帧数据,二者相结合获取视频每一帧的深度值,输出数据,在测井资料解释软件中实现可视化。通过Matlab搭建的实验平台进行实验,结果计算出了每一帧图像的深度数据并实现了与深度值索引,获得了预期的实验结果。

Application of Seismic Inversion Using Logging Data as Constraints in Coalfield

Seismic inversion and basic theory are briefly presented and the main idea of this method is introduced. Both non-linear wave equation inversion technique and Complete Utilization of Samples Information (CUSI) neural network analysis are used in lithological interpretation in Jibei coal field. The prediction results indicate that this method can provide reliable data for thin coal exploitation and promising area evaluation.

THE METHOD OF ORIGINAL LOGGING DATA PROCESSING BASED ON VBA

目前主流测井仪器生成的ASCII、LAS、WIS文件格式，在卡奔BendlinkEx等测井解释软件中无法直接加载。以处理LAS文件以适应卡奔导入要求为例，介绍以ExcelBVA为基础的测井数据处理方法。利用VBA进行编程，首先通过“格式化格式”函数处理单个文件，删除卡奔软件加载时多余的信息，保留测井作业范围上各种曲线每个采点上的数值，并生成TxT文件；然后利用“批量处理”函数，对工区所有测井LAS文件进行批量处理，完成测井解释数据准备工作。该方法极大的降低了重复性数据操作，减少了人工参与和人为错误的发生，提高了工作效率，对从事地球物理和地质开发研究的人有重要意义。

Logging Data High-Resolution Sequence Stratigraphy

The recognition and contrast of bed sets in parasequence is difficult in terrestrial basin high-resolution sequence stratigraphy. This study puts forward new methods for the boundary identification and contrast of bed sets on the basis of manifold logging data. The formation of calcareous interbeds, shale resistivity differences and the relation of reservoir resistivity to altitude are considered on the basis of log curve morphological characteristics, core observation, cast thin section, X-ray diffraction and scanning electron microscopy. The results show that the thickness of calcareous interbeds is between 0.5 m and 2 m, increasing on weathering crusts and faults. Calcareous interbeds occur at the bottom of a distributary channel and the top of a distributary mouth bar. Lower resistivity shale （4-5 Ω · m） and higher resistivity shale （〉 10Ω·m） reflect differences in sediment fountain or sediment microfacies. Reservoir resistivity increases with altitude. Calcareous interbeds may be a symbol of recognition for the boundary of bed sets and isochronous contrast bed sets, and shale resistivity differences may confirm the stack relation and connectivity of bed sets. Based on this, a high-resolution chronostratigraphic frame- work of Xi-1 segment in Shinan area, Junggar basin is presented, and the connectivity of bed sets and oil-water contact is confirmed. In this chronostratigraphic framework, the growth order, stack mode and space shape of bed sets are qualitatively and quantitatively described.

Reservoir heterogeneity and fracture parameter determination using electrical image logs and petrophysical data(a case study, carbonate Asmari Formation, Zagros Basin, SW Iran)

Assessment of reservoir and fracture parameters is necessary to optimize oil production,especially in heterogeneous reservoirs.Core and image logs are regarded as two of the best methods for this aim.However,due to core limitations,using image log is considered as the best method.This study aims to use electrical image logs in the carbonate Asmari Formation reservoir in Zagros Basin,SW Iran,in order to evaluate natural fractures,porosity system,permeability profile and heterogeneity index and accordingly compare the results with core and well data.The results indicated that the electrical image logs are reliable for evaluating fracture and reservoir parameters,when there is no core available for a well.Based on the results from formation micro-imager(FMI)and electrical micro-imager(EMI),Asmari was recognized as a completely fractured reservoir in studied field and the reservoir parameters are mainly controlled by fractures.Furthermore,core and image logs indicated that the secondary porosity varies from 0%to 10%.The permeability indicator indicates that zones 3 and 5 have higher permeability index.Image log permeability index shows a very reasonable permeability profile after scaling against core and modular dynamics tester mobility,mud loss and production index which vary between 1 and 1000 md.In addition,no relationship was observed between core porosity and permeability,while the permeability relied heavily on fracture aperture.Therefore,fracture aperture was considered as the most important parameter for the determination of permeability.Sudden changes were also observed at zones 1-1 and 5 in the permeability trend,due to the high fracture aperture.It can be concluded that the electrical image logs(FMI and EMI)are usable for evaluating both reservoir and fracture parameters in wells with no core data in the Zagros Basin,SW Iran.

Design and Implementation of a Photovoltaic Data Acquisition System for Some Meteorological Variables

In this paper we have developed a data logging and monitoring system, we validated the system by comparing the result from it with the existing one and found that the system performs slightly better than the existing work in the same area. This implies that the data logger and monitoring system is good and can be used to monitor solar energy variables even at the comfort of our homes. We fitted a model to the generated data and found that the meteorological variables considered accounted for 99.88% of the power output in the rainy seasons while 0.12% of the variation was not explained due to other factors. Solar panels inclined at an angle of 5° (Tilt) and facing South Pole perform optimally.

“测井数据处理与解释”课程实验项目设计——以CIFLog软件平台为例

“测井数据处理与解释”是勘查技术与工程专业的本科必修课程之一,基于软件对数据进行处理与解释是该专业学生必须掌握的技能。文章结合行业前沿,基于CIFLog软件平台设计了常规数据处理、成像数据处理和程序开发三组实验项目,可以做到实践与理论、生产相结合。实际教学效果表明,文章中的实验项目设计合理,不仅帮助学生掌握了测井数据处理与解释的基本流程,还帮助学生拓展了思维,从而为日后的科学研究提供了有力支撑。

Integration of Well Logs and Seismic Data for Prospects Evaluation of an X Field, Onshore Niger Delta, Nigeria

Hydrocarbon reservoir beds have been delineated using direct hydrocarbon indicator on seismic sections as well as well logs data in X field, Onshore Niger Delta. The research methodology involved horizon interpretation to produce sub-surface structure map. Geophysical well log signatures were employed in identifying hydrocarbon bearing sand. The well-to-seismic tie revealed that the reservoir tied directly with hydrocarbon indicator (bright spot) on the seismic sections. The major structure responsible for the hydrocarbon entrapment is anticline. The crest of the anticline from the depth structural map occurs at 3450 metres.

基于神经网络模型的水平井破裂压力预测方法

破裂压力是井身结构设计的基础依据,也是水力压裂设备选型和方案设计的基础参数,通常采用测井解释获取破裂压力剖面,但其存在参数准确获取难、计算过程繁琐、普适性较差、计算精度低等问题,机器学习提供了一种解决这些问题的新方法。为此,以测井数据作为输入参数,采用4种不同的神经网络模型,建立水平井测井数据与破裂压力间的非线性关系,通过测试集预测结果的对比分析,优选出最佳的神经网络模型,并优化模型网络结构和超参数,实现水平井破裂压力的直接预测。研究结果表明:1)破裂压力与井斜角、横波时差和纵波时差表现为极强相关性,与井深、岩性密度和补偿中子表现为强相关性,与井径和自然伽马表现为弱相关性;2)不同组合的测井参数对模型预测结果具有显著影响,最优输入参数为井斜角、横波时差、纵波时差、井深、岩性密度和补偿中子;3)对比多层感知机、深度神经网络、循环神经网络和长短期记忆神经网络(LSTM)模型,发现LSTM模型的预测效果最佳;4)优化了LSTM模型的网络结构及超参数,优化后破裂压力预测的平均绝对百分比误差为0.106%、决定系数为0.996。LSTM模型能够有效构建水平井测井参数与破裂压力之间的非线性关系,可以实现水平井破裂压力的准确预测,对于准确预测破裂压力、简化破裂压力计算过程、推广机器学习在石油工程领域的应用具有重要的作用。

MIT测井数据的点云转换及井筒形变诊断

针对多臂井径仪(MIT)采集井筒内壁空间位置参数可视化需求,现提出将其转换为点云数据,再通过对数据模型诊断分析得到井筒的形变类型。建立MIT测井过程可视化模型,通过引入柱面坐标来标定每个测点三维坐标;将每个测点的空间位置信息由极坐标转换为直角坐标,形成点云模型。采用所提方法将SH54井风险段处MIT数据成功转换为点云数据,并对该井470~471 m处的点云模型以类似CT横断扫描诊断的方式进行平铺展开,利用曲线拟合、面积计算得到SH54井在470~471 m处每个横断面的实际轮廓线和实际面积。结果表明:利用该方法生成的点云模型通过图表对比分析,可推断出该井段产生了非对称挤压缩径形变。

基于中子活化瞬发伽马能谱确定地层元素含量的方法

中子技术能够利用中子与物质的相互作用确定其组成等性质,广泛应用于医学、环境科学、核反应堆建设、金属矿产勘查及石油工业中。在石油天然气领域,中子探测技术主要被用于确定井孔中的孔隙度、密度和流体饱和度等参数。随着测井技术的不断发展,基于瞬发伽马射线的中子活化分析技术也已应用于井下确定地层元素含量,并成为复杂岩性和非常规油气储层获得矿物含量的唯一手段。通过归纳地层元素伽马能谱测井的方法,利用蒙特卡罗方法模拟不同地层条件下的伽马能谱,构建地层元素的标准谱库,研究奇异值分解和极大似然估计能谱数据处理方法,并利用得到的元素产额及氧闭合模型实现地层元素含量的确定。利用蒙特卡罗方法构建已知地层的伽马能谱,采用上述数据处理方法得到元素含量与地层真实元素含量误差均在4%之内,Si误差最大为2.8%,Ca最大误差为3.3%,研究结果为井下确定地层元素成分及含量提供了有效的技术支持。

基于日志数据的窗口化异常检测方法

传统的异常检测方法采用不定时巡检和用户反馈等被动方式发现问题,效率低、无法主动发现故障。本文提出了一种基于日志数据的窗口化异常检测方法,首先对历史日志数据进行预处理,获取日志模式库,再将日志数据转换成事件统计矩阵,结合COPOD算法快速定位异常点,及时发现具体异常日志,保证检测高效及准确。经实验数据表明,本文提出的异常检测方法能有效检测出多事件中存在的异常数据,且在大数据处理过程中效率较高。

利用测井资料评价煤层气可采性

精准评价煤层气可采性,对于制定压裂排采方案至关重要。本文以鄂东气田韩城矿区煤储层为研究对象,充分利用测井、煤岩心化验分析及排采动态测试资料,对影响煤储层完井品质的煤体结构指数、煤岩脆性指数、地应力差异系数进行了计算,并构建了煤储层完井品质指数预测模型;详细分析了煤层气排采出水量与各影响因素间的内在关系,建立了煤层气排采出水量预测模型;有机融合煤储层完井品质指数和出水量预测指数,建立了煤层气开采性评价指数预测模型和划分标准,进而基于该套技术方法进行了煤层气开采性评价。研究结果表明:本文所述技术既充分考虑了完井品质对煤层气开采的影响,又兼顾了排采出水量,所评价的煤层气可采性与煤层气开采实际生产情况较为吻合。

△logR技术改进及其在烃源岩评价中的应用

利用测井资料计算岩石中有机碳含量是烃源岩评价中的重要研究领域。此前的△logR方法以固定的叠合系数将声波时差和电阻率曲线叠合，确定基线位置后需读取基线值计算△logR，操作过程繁琐且影响计算精度，同时主观确定有机碳含量背景值误差较大。研究发现，△logR方法计算有机碳含量的精度受声波时差和电阻率间叠合系数影响，并从理论上解释了原因。为此，对原有模型改进，实现自动优选叠合系数，在缺少成熟度参数、无需人为确定有机碳含量背景值及基线值情况下，通过计算机快速、准确地计算有机碳含量。改进模型在海拉尔盆地及松辽盆地的应用结果表明，改进方法使计算有机碳含量与实测有机碳含量相关度达到最高，且方法简单，具有广’泛的应用前景。