Speed correction of electrical imaging logging based on fuzzy logic

• Main Authors: Liu, Jie, Deng, Ya, Kaabar, Mohammed K. A
• Format: Conference or Workshop Item
• Published: 2021
• Subjects: Q Science (General); QA Mathematics
• Online Access: http://eprints.um.edu.my/36045/; https://www.scopus.com/inward/record.uri?eid=2-s2.0-85127576443&doi=10.1145%2f3511716.3511726&partnerID=40&md5=07cd6efc6b7d6357e1d130dbdd37b173

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. © 2021 ACM.