Computational approaches to evaluate and design wellbore fluid processes for zonal isolation
University of Pittsburgh
Abstract
Properly cementing new oil and gas wells and plugging unprofitable and unproductive abandoned wells is critical for environmental protection and enhances overall operational efficiency, while preventing interference with active operations through fluid migration. As a result, considerable work has focused on improving the placement and performance of isolation materials, such as cement slurries and clay-based materials (e.g., bentonite clay gel). However, the success of these operations is often affected by complex fluid behaviors, material variability, and operational uncertainties that are difficult to capture using current toolsets.
This talk will present strategies actively being investigated to aid in the development of materials and fluid placement processes to ensure effective wellbore zonal isolation. These strategies primarily utilize the Lattice Boltzmann Method, a mesoscale statistical mechanics approach, that is well suited for modeling multi-component, multi-phase, and non-Newtonian fluid processes with complex boundary conditions. Examples will also be provided, demonstrating the applicability and effectiveness of these strategies to evaluate isolation fluid placement and gas migration processes within wellbore systems, and the potential for use within a design optimization framework.
About the speaker
Dr. John Brigham received a B.E. from Vanderbilt University and an M.S. and Ph.D. from Cornell University. He joined the University of Pittsburgh in 2008 in the Department of Civil and Environmental Engineering and with a secondary appointment in the Department of Bioengineering. John then departed Pitt to join the Department of Engineering at Durham University in the United Kingdom in 2016. John was subsequently appointed as a Deputy Executive Dean for the Faculty of Science overseeing the 8 Departments of Science and Engineering at Durham, but decided to return to Pitt in the Fall of 2020. John’s Computational Diagnostics & Inverse Mechanics (CDIM) research group maintains the overall objective of the prediction of life in the broadest sense, encompassing manmade, natural, and biological phenomena. The CDIM group has been and continues to be actively involved in a number of projects covering a diverse array of applications, including novel design concepts and optimal design strategies for adaptive structures, evaluation of wellbore cement integrity, efficient and effective computational nondestructive material characterization algorithms, reduced-order modeling for simulating multi-physics behaviors, and shape and kinematic analysis of medical imaging data for disease diagnosis.
