Advanced detection of wellbore failure for safe and secure utilization of subsurface infrastructure

September 01, 2021

Edward N. Matteo (1), Don Conley (1), Steven Verzi (1), Barry L. Roberts (1), Casey Doyle (1), Stephen R. Sobolik (1), Samuel Gilletly (1), S.J. Bauer (1), Laura J. Pyrak-Nolte (2), Mahmoud M. Reda Taha (3), John C. Stormont (3), Dustin Crandall (4)
Sandia Report, September 2021. DOI: 10.2172/1820250


The main goal of this project was to create a state-of-the-art predictive capability that screens and identifies wellbores that are at the highest risk of catastrophic failure. This capability is critical to a host of subsurface applications, including gas storage, hydrocarbon extraction and storage, geothermal energy development, and waste disposal, which depend on seal integrity to meet U.S. energy demands in a safe and secure manner. In addition to the screening tool, this project also developed several other supporting capabilities to help understand fundamental processes involved in wellbore failure. This included novel experimental methods to characterize permeability and porosity evolution during compressive failure of cement, as well as methods and capabilities for understanding two-phase flow in damaged wellbore systems, and novel fracture-resistant cements made from recycled fibers.

How Our Software Was Used

Dragonfly was used to extract the fracture geometry from an image stack (.tif file format) of a borehole sample and to segment the image stack into pore space, external/fracture space, and cement medium. It was also used to perform the segmentation on reconstructed images to identify regions in X-ray tomographic images that were cement, wax, air and/or water. Finally, Dragonfly was used to calculate local thicknesses.

Author Affiliation

(1) Sandia National Laboratories.
(2) Purdue University.
(3) University of New Mexico.
(4)National Energy Technology Laboratory.