High-Pressure-High-Temperature Coreholder for in-situ failure characterization under thermo-hydro-mechanical loading conditions using ultrasonic monitoring
Instron triaxial load frame for failure characterization
Hydraulic fracture and natural fracture interact mechanically and hydraulically. This interaction can be modeled and upscaled in order to map hydraulic fractures in a naturally fractured rock.
Seismicity induced by fluid injection and withdrawal is an area of study in geophysics and hydrogeology. It is also a matter of public concern due to the hazard posed by earthquakes. We use geological, geophysical, and well data of oilfields and aquifers to model various physical processes in the subsurface for assessment and mitigation of the induced seismicity hazard. The challenge here is the numerical modeling of a multiphysics and multiscale problem. Fluid injection and production leads to stress accumulation around faults for years, and a part of the accumulated stress is released as seismic waves during an induced earthquake in a matter of few seconds. Solving the governing equations of fluid flow, geomechanics, and seismicity in a monolithic solver is computationally challenging and expensive. Sequential solution schemes provide the desired computational speed in such multiphysics problems. Below is an example of results from such a sequentially coupled flow-geomechanics simulator.
A two-dimensional model of injection-induced slip is shown below. Aquifer is pressurized due to carbon dioxide injection, which leads to volumetric expansion of the aquifer. This builds up shear traction and reduces compression on the fault. The ratio of shear to effective normal traction at the bottom intersection point of aquifer with the fault reaches the static friction coefficient, which causes nucleation of slip at that point.
Production of oil and gas from faulted reservoirs requires assessment of the induced slip hazard on critically-stressed faults in the reservoir and in the basement below the reservoir.
We develop new computational frameworks to model coupled multiphase (oil, water, and gas) flow and geomechanics of faulted and fractured reservoirs. The challenges here are related to the mathematical formulation of the coupled problem, space discretization and time integration of the equations, design of numerically stable and fast algorithms to solve the discretized problem, and computer implementations of the algorithms to enable parallel computing required for real-world simulations.
Reservoir characterization refers to the task of estimating spatial distributions of rock properties in the reservoir, such as porosity, permeability, and compressibility. We use ensemble-based methods to assimilate multiple sources of data (well flow rates and pressures, surface deformation measurements from InSAR, GPS and ground leveling stations, and geophone data from seismic events) with coupled flow and geomechanical simulation predictions to estimate these properties. More precisely, we use the measured data to reduce the uncertainty in the rock properties by reducing the variance in prior probability distributions as it learns from the data following the rules of coupled flow and geomechanics.
An example of results from our coupled flow-geomechanical simulation is shown below (Jha et al., IJNAMG, 2015). East-west (Ux) and up-down (Uz) motions of the reservoir surface resulting from seasonal gas injection and production operation in an underground gas storage field is shown in the two videos. During summer months, gas is injected in the field causing the reservoir to expand upward (red Uz values) and sideways (red Ux for eastward motion, blue Ux for westward motion). During winter, gas is produced to meet the demand for heating gas, and this causes the reservoir to shrink (blue color). The seasonal nature of ground motion appears like a beating heart in the videos.
The challenge here is to develop a consistent and robust theory of poromechanical inversion based on realistic datasets that can be available in a field. We used well rate and pressure data, which informs primarily permeability and compressibility, and the InSAR data (calibrated with the GPS station data), which informs primarily Young’s modulus and compressibility, for joint estimation of both hydraulic (permeability) and mechanical (modulus and compressibility) properties. We used the ensemble smoother method, which is faster than the ensemble Kalman filter method, for data assimilation and inversion.
Fluid mixing in porous media
Mixing of fluids is an important phenomenon that controls many natural and industrial processes from gravity current flows to DNA testing. Mixing in porous media and low Reynolds number flows is especially difficult because of the absence of turbulence. Development and control of mixing in such flows is an active area of research.
Mixing from viscous fingering
In enhanced oil recovery techniques such as miscible gas flooding where CO2 is injected to mix with and mobilize crude oil, recovery efficiency can be increased by developing miscibility between the two fluids. We show that viscous fingering, a type of hydrodynamic instability, can be used to induce disorder in the flow and thereby enhance mixing. Tip-splitting and channeling during viscous fingering are two different mechanisms for creation of interfacial area and subsequent mixing across the interface.
We develop a two-equation model for the concentration variance and mean scalar dissipation rate to quantify the evolution of the degree of mixing in a viscously unstable displacement. Fastest mixing is achieved by optimizing the interplay between tip-splitting and channeling mechanisms.
Stokes flow in a Hele-Shaw cell serves as a simple analog for porous media flows. We study spreading and mixing of slugs of different viscosities flowing in the gap between two parallel rigid plates.
Mixing during slug injection
Mixing at low Reynolds number can be enhanced by alternating injection of slugs of the two fluids of different viscosities, for example by solvent-alternating-gas injection during enhanced oil recovery. This is also relevant for achieving fast mixing in microfluidic flows. We show that the synergetic action of alternating injection and viscous fingering leads to a dramatic increase in the mixing efficiency at optimum viscosity contrasts.
Mixing and dilution in heterogeneous formations
Heterogeneity of the porous medium is another source of disorder in the flow that causes spreading and dilution of tracers in groundwater flows. We develop reduced-order models to describe and predict mixing during simulation of such flows.