Integration of image and dipole sonic logs for identification of natural fractures and stress-induced anisotropy in Asmari reservoir (A case study, SW Iran)
{"title":"Integration of image and dipole sonic logs for identification of natural fractures and stress-induced anisotropy in Asmari reservoir (A case study, SW Iran)","authors":"Maziar Torkaman , Soheila Bagheri , Mahdi Rastegarnia","doi":"10.1016/j.rockmb.2025.100235","DOIUrl":null,"url":null,"abstract":"<div><div>Borehole sonic dispersion analysis is a technique that provides valuable insights into the realm of borehole sonic interpretation. This research involves an analysis of shear-wave anisotropy and ultrasonic image logs to differentiate between types of fractures and their orientations. Evaluating fractures relies on core samples and image logs are limited. This highlights the need for a more affordable and efficient way to analyse fractures. A challenge in the wellbore is distinguishing natural fractures from those caused by drilling. Using oil-based mud often makes it hard to find signs indicating the direction of in-situ stress. A new method has been created to reliably identify natural fractures when image logs are insufficient for mapping fracture networks. The cross-dipole data reveals five main zones exhibiting shear-wave splitting. Higher anisotropy is observed at shallower depths, while the deeper interval shows low porosity accompanied by considerable inhomogeneity, highlighting potential areas of concern. The dominant directions of anisotropy are aligned with NW-SE, WNW-ESE, and N-S orientations. Slowness frequency analysis of rotated flexural waves identifies fracture types. Dispersion profiles show natural and induced fractures, with cross-over patterns indicating stress-induced anisotropy. Significant inhomogeneity is observed in the bottom interval, where the differences between maximum and minimum energy level are pronounced. Wider dispersion curves suggest breakouts are slowing high-frequency flexural waves, indicating mechanical damage. The maximum stress direction is determined by the fast-shear azimuth. In conclusion, this study demonstrates that by integrating acoustic shear dispersion, shear anisotropy, Stoneley analysis, and image log data, fractures within the borehole wall can be effectively investigated.</div></div>","PeriodicalId":101137,"journal":{"name":"Rock Mechanics Bulletin","volume":"5 2","pages":"Article 100235"},"PeriodicalIF":7.0000,"publicationDate":"2025-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Rock Mechanics Bulletin","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2773230425000629","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
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Abstract
Borehole sonic dispersion analysis is a technique that provides valuable insights into the realm of borehole sonic interpretation. This research involves an analysis of shear-wave anisotropy and ultrasonic image logs to differentiate between types of fractures and their orientations. Evaluating fractures relies on core samples and image logs are limited. This highlights the need for a more affordable and efficient way to analyse fractures. A challenge in the wellbore is distinguishing natural fractures from those caused by drilling. Using oil-based mud often makes it hard to find signs indicating the direction of in-situ stress. A new method has been created to reliably identify natural fractures when image logs are insufficient for mapping fracture networks. The cross-dipole data reveals five main zones exhibiting shear-wave splitting. Higher anisotropy is observed at shallower depths, while the deeper interval shows low porosity accompanied by considerable inhomogeneity, highlighting potential areas of concern. The dominant directions of anisotropy are aligned with NW-SE, WNW-ESE, and N-S orientations. Slowness frequency analysis of rotated flexural waves identifies fracture types. Dispersion profiles show natural and induced fractures, with cross-over patterns indicating stress-induced anisotropy. Significant inhomogeneity is observed in the bottom interval, where the differences between maximum and minimum energy level are pronounced. Wider dispersion curves suggest breakouts are slowing high-frequency flexural waves, indicating mechanical damage. The maximum stress direction is determined by the fast-shear azimuth. In conclusion, this study demonstrates that by integrating acoustic shear dispersion, shear anisotropy, Stoneley analysis, and image log data, fractures within the borehole wall can be effectively investigated.