Abstract
Abstract
Wellbore natural fracture systems characterization is a key element to achieve the successful exploitation of tight reservoirs, where one of the dominant aspects is permeability. Carbonate reservoir fracture evaluation is challenging in terms of type, density, aperture, and extension. Traditionally, fractured reservoirs are evaluated based on Borehole imaging (BHI) data. However, the borehole drilled with oil-based mud (OBM) poses constraints in the image quality of the logs. The oil-based mud has higher resistivity than the conductive mud that limits the depth of investigation and reduces the ability to identify surface features and formations. Ultrasonic imaging tools provide higher resolution than OBM imaging tools due to its capability to read deeper into the formation. However, the ultrasonic imaging tools are specialized equipment with high operational cost and the quality of measurement is affected due to noises from drilling or other sources. Moreover, the meaning of features observed from image logs is a matter of interpretation at the borehole wall only. This introduces a degree of uncertainty, which might be greatly reduced by integrating other measurements such as Deep Shear Wave Imaging (DSWI) & Coriolis micro mud-loss detection data. The first is to map the near borehole environment for fractures as well as their extension far away from the borehole (within ~150 ft vicinity), while the latter provides information on the presence of open fractures while drilling by detecting minor well kicks and mud-losses. Therefore, integration of the multiple sources of information significantly enhances the benefits of all.
This paper aim to present an integrated workflow, which combines above-mentioned methods to enhance the confidence of fracture interpretation at & away from the wellbore, resulting in a detailed description of the natural fracture system in a deviated well drilled through a tight carbonate reservoir in Kra Al-Maru (KM) field recently that supports the development strategy.