Speed correction of electrical imaging logging based on fuzzy logic
Document Type
Conference Item
Publication Date
1-1-2021
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. © 2021 ACM.
Keywords
Cables, Computer circuits, Fuzzy filters, Image compression, Image reconstruction, Kalman filters, Restoration, Alman filter, Electrical imaging, Fuzzy-Logic, Geological information, Imaging logging, Lectrical imaging, Log measurement, Logging system, Logging tools, Peed correction, Fuzzy logic
Divisions
MathematicalSciences
Funders
Hubei Provincial Department of Education [Grant No: B2019250],Wuhan Business University
Publication Title
ACM International Conference Proceeding Series
Event Title
4th International Conference on E-Business, Information Management and Computer Science, EBIMCS 2021
Event Location
Hong Kong
Event Dates
29-31 December 2021
Event Type
conference