LAUSR

Imaging logging tools can provide us the borehole wall image. The micro-resistivity imaging logging has been used to obtain borehole porosity spectrum. However, the resistivity imaging logging cannot cover the whole borehole wall. In this paper, we propose a method to calculate the porosity spectrum using ultrasonic imaging logging data. Based on the amplitude attenuation equation, we analyze the factors affecting the propagation of wave in drilling fluid and formation and based on the bulk-volume rock model, Wyllie equation and Raymer equation, we establish various conversion models between the reflection coefficient β and porosity ϕ. Then we use the ultrasonic imaging logging and conventional wireline logging data to calculate the near-borehole formation porosity distribution spectrum. The porosity spectrum result obtained from ultrasonic imaging data is compared with the one from the micro-resistivity imaging data, and they turn out to be similar, but with discrepancy, which is caused by the borehole coverage and data input difference. We separate the porosity types by performing threshold value segmentation and generate porosity–depth distribution curves by counting with equal depth spacing on the porosity image. The practice result is good and reveals the efficiency of our method.