Epoxy-pore casting is widely used to characterize geological samples. In this study, we present a robust pore imaging approach that applies Confocal Laser Scanning Microscopy (CLSM) to obtain high resolution 3D images of etched epoxy-pore casts of highly heterogeneous carbonates. In our approach, we have increased the depth of investigation for carbonates 20-fold, from 10
Successful exploitation of shale reservoirs largely depends on the effectiveness of hydraulic fracturing stimulation program. Favorable results have been attributed to intersection and reactivation of pre-existing fractures by hydraulically-induced fractures that connect the wellbore to a larger fracture surface area within the reservoir rock volume. Thus, accurate estimation of the stimulated reservoir volume (SRV) becomes critical for the reservoir performance simulation and production analysis. Micro-seismic events (MS) have been commonly used as a proxy to map out the SRV geometry, which could be erroneous because not all MS events are related to hydraulic fracture propagation. The case studies discussed here utilized a fully 3-D simulation approach to estimate the SRV.
The simulation approach presented in this paper takes into account the real-time changes in the reservoir's geomechanics as a function of fluid pressures. It is consisted of four separate coupled modules: geomechanics, hydrodynamics, a geomechanical joint model for interfacial resolution, and an adaptive re-meshing. Reservoir stress condition, rock mechanical properties, and injected fluid pressure dictate how fracture elements could open or slide. Critical stress intensity factor was used as a fracture criterion governing the generation of new fractures or propagation of existing fractures and their directions. Our simulations were run on a Cray XC-40 HPC system.
The studies outcomes proved the approach of using MS data as a proxy for SRV to be significantly flawed. Many of the observed stimulated natural fractures are stress related and very few that are closer to the injection field are connected. The situation is worsened in a highly laminated shale reservoir as the hydraulic fracture propagation is significantly hampered. High contrast in the in-situ stresses related strike-slip developed thereby shortens the extent of SRV. However, far field nature fractures that were not connected to hydraulic fracture were observed being stimulated.
These results show the beginning of new understanding into the physical mechanisms responsible for greater disparity in stimulation results within the same shale reservoir and hence the SRV. Using the appropriate methodology, stimulation design can be controlled to optimize the responses of in-situ stresses and reservoir rock itself.
Enhanced recovery methods have become significant in the industry's drive to increase recovery rates from oil and gas reservoirs. For heavy oil reservoirs, the immobility of the oil at reservoir temperatures, caused by its high viscosity, limits the recovery rates and strains the economic viability of these fields. While thermal recovery methods, such as steam injection or THAI, have extensively been applied in the field, their success has so far been limited due to prohibitive heat losses and the difficulty in controlling the combustion process. Electromagnetic (EM) heating via high-frequency EM radiation has attracted attention due to its wide applicability in different environments, its efficiency, and the improved controllability of the heating process. While becoming a promising technology for heavy oil recovery, its effect on overall reservoir production and fluid displacements are poorly understood. Reservoir history matching has become a vital tool for the oil & gas industry to increase recovery rates. Limited research has been undertaken so far to capture the nonlinear reservoir dynamics and significantly varying flow rates for thermally heated heavy oil reservoir that may notably change production rates and render conventional history matching frameworks more challenging. We present a new history matching framework for EM heated heavy oil reservoirs incorporating cross-well seismic imaging. Interfacing an EM heating solver to a reservoir simulator via Andrade’s equation, we couple the system to an ensemble Kalman filter based history matching framework incorporating a cross-well seismic survey module. With increasing power levels and heating applied to the heavy oil reservoirs, reservoir dynamics change considerably and may lead to widely differing production forecasts and increased uncertainty. We have shown that the incorporation of seismic observations into the EnKF framework can significantly enhance reservoir simulations, decrease forecasting uncertainties and cope with the growing nonlinearity caused by the heating process for efficient and accurate reservoir forecasting.
Allen, Rebecca (King Abdullah University of Science & Technology) | Reis, Tim (Oxford Centre for Collaborative Applied Mathematics) | Sun, Shuyu (King Abdullah University of Science & Technology)
The storage of CO2 in fluid-filled geological formations has been carried out for more than a decade in locations around the world. After CO2 has been injected into the aquifer and has moved laterally under the aquifer's cap-rock, density-driven convection becomes an important transport process to model. However, the challenge lies in simulating this transport process accurately with high spatial resolution and low CPU cost. This issue can be addressed by using the lattice Boltzmann equation (LBE) to formulate a model for a similar scenario when a solute diffuses into a fluid and density differences lead to convective mixing. The LBE is a promising alternative to the traditional methods of computational fluid dynamics. Rather than discretizing the system of partial differential equations of classical continuum mechanics directly, the LBE is derived from a velocity-space truncation of the Boltzmann equation of classical kinetic theory.
We propose an extension to the LBE, which can accurately predict the transport of dissolved CO2 in water, as a step towards fluid-filled porous media simulations. This is achieved by coupling two LBEs, one for the fluid flow and one for the convection and diffusion of CO2. Unlike existing lattice Boltzmann equations for porous media flow, our model is derived from a system of moment equations and a Crank-Nicolson discretization of the velocity-truncated Boltzmann equation. The forcing terms are updated locally without the need for additional central difference approximation. Therefore our model preserves all the computational advantages of the single-phase lattice Boltzmann equation and is formally second-order accurate in both space and time. Our new model also features a novel implementation of boundary conditions, which is simple to implement and does not suffer from the grid-dependent error that is present in the standard "bounce-back" condition.
The significance of using the LBE in this work lies in the ability to efficiently simulate density-driven convection of CO2 through water. From an implementation viewpoint, the locality of our algorithm exploits massively parallel modern computer architectures, including graphics processing units (GPUs), which would lead to very fast computations that scale linearly with the number of processors.
Bao, Kai (King Abdullah University of Science & Technology) | Yan, Mi (IBM) | Lu, Ligang (IBM) | Allen, Rebecca (King Abdullah University of Science & Tech) | Salama, Amgad (King Abdullah University of Science & Technology) | Jordan, Kirk E. (IBM) | Sun, Shuyu (King Abdullah University of Science & Technology)
The present work describes a parallel computational framework for CO2 sequestration simulation by coupling reservoir simulation and molecular dynamics (MD) on massively parallel HPC systems. In this framework, a parallel reservoir simulator, Reservoir Simulation Toolbox (RST), solves the flow and transport equations that describe the subsurface flow behavior, while the molecular dynamics simulations are performed to provide the required physical parameters. Numerous technologies from different fields are employed to make this novel coupled system work efficiently.
One of the major applications of the framework is the modeling of large scale CO2 sequestration for long-term storage in the subsurface geological formations, such as depleted reservoirs and deep saline aquifers, which has been proposed as one of the most attractive and practical solutions to reduce the CO2 emission problem to address the global-warming threat. To effectively solve such problems, fine grids and accurate prediction of the properties of fluid mixtures are essential for accuracy. In this work, the CO2 sequestration is presented as our first example to couple the reservoir simulation and molecular dynamics, while the framework can be extended naturally to the full multiphase multicomponent compositional flow simulation to handle more complicated physical process in the future.
Accuracy and scalability analysis are performed on an IBM BlueGene/P and on an IBM BlueGene/Q, the latest IBM supercomputer. Results show good accuracy of our MD simulations compared with published data, and good scalability are observed with the massively parallel HPC systems. The performance and capacity of the proposed framework are well demonstrated with several experiments with hundreds of millions to a billion cells.
To our best knowledge, the work represents the first attempt to couple the reservoir simulation and molecular simulation for large scale modeling. Due to the complexity of the subsurface systems, fluid thermodynamic properties over a broad range of temperature, pressure and composition under different geological conditions are required, for which the experimental results are limited. Although equations of state can reproduce the existing experimental data within certain ranges of conditions, their extrapolation out of the experimental data range is still limited. The presented framework will definitely provide better flexibility and predictability compared with conventional methods.