Evaluation Method for the Broken Degree of Broken Formations Based on Well Imaging Logging Data

ABSTRACT: With the development of the petroleum industry, drilling has been advancing into ultra-deep formations. Under the long-term influence of tectonic stress in high-temperature, high-pressure (HPHT) environments, such formations tend to develop complex fracture networks that bring challenges to wellbore stability. Therefore, it is essential to evaluate the degree of broken in such formations. To address this issue, a method for evaluating the broken degree of broken formations based on logging data is proposed. First, imaging logging data is processed through image filling, and a segmentation method based on primary color clustering and replacement is applied to segment the images. Noise is then removed using a connectivity analysis-based denoising method. Next, a voting recognition algorithm is employed to identify fracture baselines, and the connectivity domain is used to measure fracture widths, converting the pixel-based width/depth into actual physical width/depth values. Finally, the above algorithms are applied to process imaging logging data from the 8490m to 8630m section of the Shunbei X well. The rock quality designation (RQD) is calculated, and the results are analyzed. For the Shunbei X well, if a 10% borehole enlargement rate is used as the broken threshold, the corresponding RQD value is approximately 80.