Expedite processing and interpretation up to 10× faster than conventional methods.
Published: 07/10/2019
Published: 07/10/2019
An operator in West Texas wanted to characterize the occurrence and distribution of natural fractures along the lateral of a well. This information would help to better understand the impact of natural fractures on the well completion and production.
Modeling natural fractures requires knowledge of their orientation and density distribution, aperture, length, and height, among other parameters. The conventional way to characterize these fractures is with high-resolution borehole images. The images provide a photorealistic view of fractures that intersect the wellbore, providing information about orientation, density, and aperture.
However, the images rarely indicate fracture length or height and do not reveal the 3D trend of fracture corridors, which are important for accurate reservoir modeling.
To achieve a complete map of fractures at and around the wellbore, Schlumberger recommended a two-pronged approach: Quanta Geo service would acquire microresistivity images while the Sonic Scanner platform would be configured to also acquire the data necessary to perform a borehole acoustic reflection survey (BARS) for processing using 3D far-field sonic service.
The 3D far-field sonic service workflow automates time picking and event analysis instead of the lengthy conventional manual determination of reflector dip and azimuth. The service rapidly derives the migration parameters from the automated event analysis, which can then be easily integrated with borehole image interpretation. This high-confidence resolution of near-wellbore reflectors is ready to import into 3D geological modeling.
The 3D far-field sonic service mapped the location, orientation, and length of natural fractures up to 40 ft around the wellbore—including fractures that did not intersect the wellbore and thus were not identified by wellbore imaging. The operator was able to import the fracture data into a reservoir model to improve fracturing and stimulation operations.
Challenge: Understand the distribution of natural fractures across the wellbore for guiding the completion design.
Solution:
Results: