Numerical Simulation of Subsurface Transport and Groundwater Impacts from Hydraulic Fracturing of Tight/Shale Gas Reservoirs

Friday, 19 December 2014: 9:40 AM
Matthew T Reagan, George J Moridis and Noel D Keen, Lawrence Berkeley National Laboratory, Berkeley, CA, United States
The use of reservoir stimulation techniques, such as hydraulic fracturing, has grown tremendously over the last decade, and concerns have arisen that reservoir stimulation creates environmental threats through the creation of permeable pathways that could connect the stimulated reservoir to shallower groundwater aquifers. This study investigates, by numerical simulation, gas and water transport between a deeper tight-gas reservoir and a shallower overlying groundwater aquifer following hydraulic fracturing operations, assuming that the formation of a connecting pathway has already occurred. We focus on two general transport scenarios: 1) communication between the reservoir and aquifer via a connecting fracture or fault and 2) communication via a deteriorated, preexisting nearby well. The simulations explore a range of permeabilities and geometries over time scales, and evaluate the mechanisms and factors that could lead to the escape of gas or reservoir fluid and the contamination of groundwater resources. We also examine the effects of overpressured reservoirs, and explore long-term transport processes as part of a continuing study.

We conclude that the key factors driving short-term transport of gas include high permeability for the connecting pathway and the overall volume of the connecting feature. Gas production from the reservoir via a horizontal well is likely to mitigate release through the reduction of available free gas and the lowering of reservoir pressure. We also find that fractured tight-gas reservoirs are unlikely to act as a continuing source of large volumes of migrating gas, and incidents of gas escape are likely to be limited in duration and scope. Reliable field and laboratory data must be acquired to constrain the factors and determine the likelihood of these outcomes.