Speed Correction of Electrical Imaging Logging Based on Fuzzy Logic

Proceedings of the 2021 4th International Conference on E-Business, Information Management and Computer Science Pub Date : 2021-12-29 DOI:10.1145/3511716.3511726

Jie Liu, Yaochen Deng, Mohammed K. A. Kaabar

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Abstract

Depth’ is taken to be the ‘cable depth’ by logging system that is collected at regular depth intervals. Due to the distortion of log measurement caused by cable stretch, irregular motion, and imaging logging tool sticking, serious distortion of logging image occurs, which affects the preparation and acquisition of geological information. Therefore, speed correction is needed to restore the ‘true depth’ of downhole instrument sampling data. In this paper, the motion state of the imaging logging tool is analyzed. Firstly, the Kalman filter model is constructed, and the noise variance of the Kalman filter is corrected in real-time by using a fuzzy logic controller and ‘tool sticking’ identification results, to improve the output accuracy of the system. Through the analysis of logging data, it is found that the method can eliminate the phenomenon of image compression and stretching caused by tool stuck, and restore the subtle characteristics of the formation such as fractures, pores, and bedding, which proves the effectiveness of the technology.

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基于模糊逻辑的电成像测井速度校正

测井系统将“深度”定义为“电缆深度”，每隔一定深度采集一次。由于测井电缆拉伸、不规则运动、成像测井工具卡钻等造成测井测量失真，导致测井图像失真严重，影响了地质信息的制备和采集。因此，需要进行速度校正以恢复井下仪器采样数据的“真实深度”。本文对成像测井仪器的运动状态进行了分析。首先，建立卡尔曼滤波器模型，利用模糊逻辑控制器和“粘刀”辨识结果实时校正卡尔曼滤波器的噪声方差，提高系统的输出精度;通过对测井资料的分析，发现该方法能够消除因工具卡钻造成的图像压缩和拉伸现象，恢复地层裂缝、孔隙、层理等细微特征，证明了该技术的有效性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Proceedings of the 2021 4th International Conference on E-Business, Information Management and Computer Science

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