Li, Bingjian (Schlumberger Oil Field Services) | Chen, Yong-Hua (Southwestern Energy, Woodland, USA) | Gawankar, Kiran (Schlumberger-Doll Research) | Miller, Camron K. (Schlumberger Oil Field Services) | Xu, Weixin (Schlumberger Oil Field Services) | Laronga, Rob J. (Schlumberger Oil Field Services) | Omeragic, Dzevat (Southwestern Energy, Woodland, USA)
Distinguishing open natural fractures from healed fractures has been a significant challenge in shale formations drilled with oil-based mud. Ultrasonic imaging tools can locate open fractures, but such data is seldom acquired due to concerns related to the effects of heavy mud and, in high-angle wells, operational efficiency and tool eccentralization. Until now, the microelectrical image tools in the market were not capable of differentiating open fractures from healed fractures in oil-based mud.
A new, high-definition oil-based mud microelectrical imager has been deployed that operates at high frequencies and provides images with high borehole coverage. This new tool can identify natural fractures, sub-seismic faults, and other geological features in the reservoirs. In addition to high-resolution images of formation resistivity, an advanced inversion processing can be applied to generate resolution-matched images of the quantified standoff between each sensor in the array and the borehole wall. Such standoff images are of special value for differentiating open fractures from healed fractures. The use of these standoff images are presented in several recent case studies from U.S. shale plays. In the first case study from a pilot shale well in the northeast, natural fractures are identified on the new microelectrical imager and then further interpreted as open, partially open or healed fractures based on the inverted standoff images. Such open fracture interpretation has been validated by ultrasonic image data from the same well. In the second case study from an Eagle Ford Shale lateral in south Texas, both natural fractures and sub-seismic faults were detected. Interestingly, one of the interpreted open faults based on standoff images was even evident on dynamic pressure data in a monitoring well nearby during the stimulation process.
Natural fractures can impact the shale reservoir quality, completion quality, or both, depending on the fracture types and intensity. Therefore, it is beneficial to have a reliable dataset to sort fractures by their type: open, partially open and healed.