Identification of Stuck Intervals in Imaging Logging Based on Acceleration

Abstract: Depth errors caused by cable stretching and irregular movement may distort the measurement results from sensors at different depths. For high-resolution imaging logging, it is particularly sensitive to depth errors, because their borehole images will be used for subsequent quantitative calculations of dip. Therefore, depth correction must be performed during the preprocessing of logging data, and accurate determination of the stuck section is a key step for depth correction and obtaining clear images. [Process and method] this article introduced a twice traversal well section identification algorithm. Firstly, the accelerometer measurement value is low-pass filtered through a Gaussian filter, and then the actual acceleration value of the tool along the well axis is calculated. Secondly, the Kalman model is constructed to calculate the movement speed of the tool in the well. Finally, the initial judgment of the stuck sections is made according to the accelerometer and velocity of the tool. On this basis, the section with short stuck intervals is further identified by using the correlation of images between pads, and finally, the stuck identification curve of the whole well is output. [Conclusion] through the verification of actual logging data processing, this method can accurately identify the stuck section and process the stuck intervals with duration ranging from a few seconds to a few minutes, which provides a reliable basis for speed correction.