Detection and Quantification of Injected Gas Conformance and Breakthrough from Temperature and Pressure Measurements in Deepwater Wells during Gas EOR

Early detection of gas conformance in desired reservoir zones as well as its breakthrough from producing wells is critical for successful implementation of gas EOR projects. The installation of temperature and pressure sensors in deepwater wells are underway as they provide valuable data useful for flow analysis and quantification. Modeling using the sensor data is valuable since interventions in deepwater wells are either not possible or prohibitively expensive. In this study, temperature and pressure sensor data is used to model and monitor the conformance of injected gas. The presented model is further used for two applications 1) conformance of injected gas in an injection well and 2) identification of gas breakthrough from a production well.

In this study, the production from a well producing from multiple reservoirs is modeled as a series of producing (vertical flow along with radial flow from a producing reservoir section) and non-producing (only vertical flow through the production tubing) zones. The energy balance and the momentum balance equations are coupled to quantify flow rates from individual producing reservoir sections. In addition to the sand face temperature measurements, surface temperature, total surface flow rate as well as pressure and temperature measurements in the producing tubing are used as input to the model. A difference between the temperature and pressure data obtained from the sensors and that obtained from the model is used to detect and quantify gas conformance in injection well as well as gas breakthrough in production well.

The temperature data can be used to identify locations of producing and non-producing zones in the reservoir and quantify production from individual producing zones. This model will help determine the number of temperature and pressure sensors required for conformance of gas injected as well as effective detection of gas breakthrough in producing wells. The model can also be adapted to detect water breakthrough during secondary injection. The sensors along with the model have the potential to become an integral part of production monitoring for reservoir management.

Modeling Phase Behavior and Reactive Flow Occurring during Enhanced Oil Recovery Processes

The modeling of geochemical reactions is critical for managing production from reservoirs as they occur in all stages of production from an oil and gas field. Primary production from shale gas fields is modeled as adsorption reactions. Geochemical reactions also impact rock wettability that is making low salinity water flooding, an increasingly popular secondary production process. Tertiary recovery process of gas injection relies on accurate phase behavior analysis of hydrocarbon-injected gas mixture that is also impacted by geochemical reactions. A series of projects have been initiated to model the geochemical reactions for these different applications.

CO2 injection in oil reservoirs has the dual benefit of enhancing oil recovery as well as sequestering a greenhouse gas. CO2 injected in carbonate reservoirs, such as those found in the Middle East, can react with ions present in the brine and the solid calcite in the carbonate rocks. These geochemical reactions impact the phase behavior of in-situ hydrocarbon fluids and prediction of miscibility pressures thereby impacting oil recovery predictions from compositional simulations. Hence, it is important to model the impact of geochemical reactions on real oil during CO2 injection.

A practical method to use the Gibbs free energy function for integrating phase equilibrium computations and geochemical reactions has been developed.  This method has the advantage of combining different thermodynamic models – the hydrocarbon phase components normally characterized using an Equation of State (EOS), while the aqueous phase components usually described using an activity coefficient model.

The first project seeks to quantify how geochemical reactions impact oil recovery predictions during CO2 injection in carbonate reservoirs. A real oil sample (Shell field courtesy * Birol Dindoruk) shall be used to show how a combination of Pitzer activity coefficient model and Peng Robinson (PR) Equation of State can result in changes in oil recovery predictions. In a separate project, the impact of geochemical reactions on the minimum miscibility pressure predictions shall be quantified using this approach. The change in minimum miscibility pressure in the presence of geochemical reactions depends on two factors: 1) the volume ratio (and hence molar ratio) of the aqueous phase to the hydrocarbon phase and 2) the salinity of the brine. The modified phase behavior, arising out of geochemical reactions, will be implemented in our in-house reservoir simulator IPARS (Integrated Parallel Accurate Reservoir Simulator).

In a third project, the convergence properties of different activity coefficient models shall be analyzed to identify the model most suited for compositional simulation. This shall help implement the most appropriate model that can integrate phase behavior computations as well as geochemical reactions.

In addition to above research projects pertaining to gas flooding process, we are initiating projects to help explain the low salinity water flooding project. The objective is to identify and isolate the geochemical reactions that are responsible for changing rock wettability during the low salinity water flooding process. Core flood experimental data for different combination of brine ions and rock types shall be analyzed to isolate the ions that are likely responsible. In case of many ions, principal component analysis shall be used to statistically determine the main ions responsible for the process. Having isolated primary ions, the geochemical reactions responsible for the process shall be determined. An appropriate activity coefficient model shall be used to explain the observation of fluid outlet concentration. This will help make predictions on ion concentrations that should be injected to change rock wettability to enhance oil recovery.

In addition to above projects that focus on oil and gas production, geochemical reactions also have important applications in remediation of aquifers and safe disposal of nuclear wastes. The resulting changes in IPARS and TRCHEM shall be used for applications in these fields.

*This is a joint work with Birol Dindoruk at Shell Oil E&P Company.

Model selection for reservoir characterization in CO2 sequestration

The ideal reservoir characterization is achieved from a closed-loop system that integrates geological modeling, upscaling/downscaling, reservoir simulation, history matching, and production forecasts associated with unbiased uncertainty quantification. The initial step of reservoir characterization is to identify reservoir models from all plausible geologic scenarios reflecting prior uncertainty in reservoir description. CSM has been developing model selection that implements a proxy to image flow and geomechanical responses of geologic models for CO2 sequestration (Figure 1). A fast approximation utilizes a partial coupling scheme to obtain pressure and stress fields sequentially. A particle tracking algorithm mimics flow paths of the models, and a stress-field solver calculates displacements of the models caused by injected CO2.

The prior models showing similar proxy responses are grouped into clusters by multi-dimensional scaling and k-means clustering. Full physics simulations are run for cluster representatives to select the best-fit cluster, which is the group whose representative exhibits the smallest discrepancy between observed and estimated responses. The models in the best-fit cluster constitute the posterior model set. In summary, the posterior ensemble incorporating geophysical time-lapse observations is more representative of the reservoir than the larger prior ensemble.

Figure 1. Reservoir characterization coupled a connectivity-based proxy within a model selection framework

Figure 1. Reservoir characterization coupled a connectivity-based proxy within a model selection framework (above)

Posterior ensemble mean of the permeability field

Figure 2. Posterior ensemble mean of the permeability field for the Krechba field, Algeria: (a) the uppermost layer after matching bottom-hole pressure and (b) the uppermost layer after matching bottom-hole pressure and InSAR (Interferometric Synthetic Aperture Radar) data (above)

Homogenization for Upscaling Reservoir Flow and Transport

Upscaling reservoir properties is pivotal for reducing uncertainty during parameter estimation and history matching. Further the computational cost is also lowered due to a reduced number of degrees of freedom. Upscaling single-phase flow entails estimating coarse scale, effective permeability from a given fine scale permeability distribution. However, this effective reservoir property calculation as an upscaling method holds true only for a single-phase flow process. Upscaling multiphase flow and reactive transport processes require calculation of effective coefficients which are different from known reservoir properties such as permeability, porosity etc. In this work, we use a two-scale homogenization method to evaluate these process dependent effective coefficients. This method consistently upscales the partial differential equations associated with the flow and transport processes from fine to coarse scale in a mass conservative sense. Thus, the approach is physically accurate and mathematically consistent at both reservoir scales.

This is a collaborative effort with Hans van Duijn (Professor, Eindhoven University of Technology, Netherlands) and Dr. Andro Mikelić (Professor, University of Lyon, France).

Advanced Reactive Chemistry Modeling for Reservoir Flow and Transport

The local equilibrium assumption is a well-known simplification to describe instantaneous processes, with widely different time scales when compared to flow time scales. In this proposed work, we employ this assumption for modeling both volumetric and surface processes. This work aims to model physical and chemical processes, which can be broadly categorized as equilibrium and kinetic type. This classification differs from chemical equilibrium and kinetics, which strictly refer to ionic interactions. We propose to develop more general equilibrium and kinetic models, which will account for weak physical interactions such as van der Waals interactions in addition to the ionic interactions. This will allow us to predict wettability alteration due to adsorption/desorption of both polar and non-polar molecules. The model developments will be implemented in IPARS (Integrated Parallel Accurate Reservoir Simulator) under the TRCHEM reactive chemistry module. Application areas include hydrocarbon recovery prediction from low salinity water floods, reservoir characterization and diagnostic techniques using nano-particle injection engineered to mimic specific chemical species behavior.

Nanoparticle transport in a curvilinear reservoir

Figure. Nanoparticle transport in a curvilinear reservoir: Nanoparticle slug injection with adsorption (left) and multiple nanoparticle slug injection (right) without adsorption.

An Improved 3D Polymer Model

This research aims to develop a three-dimensional, shear-thinning, non-Newtonian flow model to simulate field scale polymer flooding as a tertiary oil recovery mechanism. The viscosities are calculated based upon direction dependent shear-rates. This provides an accurate representation of the non-Newtonian flow behavior in a three dimensional porous medium. The model considers a full-tensor permeability (3 x 3 matrix with non-zero off diagonal values) as a measure of resistance (or shearing) to flow. The shear-rate is then calculated as a function of the directional permeability and polymer phase velocity. Consequently, the shear-rate dependent fluid viscosity varies with direction resulting in an accurate physical description of shear thinning flow behavior in a three dimensional porous medium. The form of the velocity dependent permeability tensor, or in other words the coefficient in front of the gradient of pressure, is guided by a pore-scale non-Newtonian, Navier-Stokes flow solution on an assumed representative element volume (REV).

The model developments are being implemented and tested approach in IPARS (Integrated Parallel Accurate Reservoir Simulator). A multi-point-flux mixed finite element (MFMFE) scheme is further used for spatial discretization of the associated partial differential equations. This scheme provides accurate fluid velocities at the faces of each element, which further improves viscosity calculations. A retardation factor, for polymer concentration, is further used to study the effect of polymer adsorption on recovery predictions. Additionally, we also consider viscosity variation due to changes in polymer concentration. Preliminary results show significant differences in sweep efficiencies due to changes in polymer front behavior, when compared to conventional models. The shear-thinning polymer viscosity is shown to decrease in a direction of low permeability and high pressure gradient (high shear rates) resulting in better sweep efficiencies. The results also show that the velocity dependent dispersion of polymer concentration is better represented due to accurate fluid velocities at the grid element faces.

This development is a joint effort being carried out at the Center for Subsurface Modeling in collaboration with Kundan Kumar (Associate Professor, University of Bergen, Norway). We also acknowledge Thomas Wick (Research Scientist, Austrian Academy of Sciences) for his deal.II fluid structure interaction toolset for solving non-Newtonian Navier Stokes flow in the REV.

NETL: Development of Geomechanical Screening Tools to Identify Risk: An Experimental and Modeling Approach for Secure CO2 Storage

(funded by DOE)

Carbon dioxide is a reservoir pore fluid of much interest because of applications to enhanced oil recovery (EOR) and more recently because of the pressing needs for carbon dioxide geological storage as an option to reduce CO2 emissions to the atmosphere. Although CO2 has been used for decades in EOR, successful carbon geological storage at commercial scale requires enhanced storage efficiency and safe CO2 containment over thousands of years.

The main objectives of this project are to:

  • Measure petrophysical and hydro-mechanical properties of rocks in the presence of CO2 in the laboratory. Perform these experiments under varying conditions of temperature and chemical reactivity of rocks with CO2
  • Develop upscaling methods for rock petrophysical and hydro-mechanical properties considering natural heterogeneity and pre-existing fractures
  • Develop advanced and cost-effective coupled solvers for simulations of coupled flow and geomechanics
  • Simulate numerically and perform history matching of CO2 injection results at a field sites
  • Develop schemes for quantifying the residual uncertainty after model calibration and data assimilation
  • Quantify reservoir overpressure and strains caused by pore pressure, thermal and chemical loadings; show the influence of each type of loading and the occurrence of emergent phenomena
  • Predict reservoir fluid composition after injection, which would serve as an input for evaluating geochemical reactivity of CO2 at in potential leaks through fractures and faults
  • Develop guidelines to mitigate the risks of CO2 injection in the subsurface

University of Texas Cockrell Labs

University of Texas Cockrell Engineering Lab University of Texas Cockrell School of Engineering

The NETL Team for CSM

Multiscale Modeling and Simulation of Multiphase Flow Coupled with Geomechanics

 (funded by DOE)

This project develops algorithms that will enable scientists and engineers to readily model complex flow processes in porous media taking into account the accompanying deformations of the porous solids. Fluid motion and solid deformation are inherently coupled, but current major commercial packages for multiphase flow in porous media only model porous flow while solid deformation is normally integrated into a study in an ad hoc manner or must be included through complex iterations between one software package that models fluid flow and a separate package that models solid deformations. There are numerous field applications that would benefit from a better understanding and integration of porous flow and solid deformation. Important applications in the geosciences include environmental cleanup, petroleum production, solid waste disposal, and carbon sequestration, while similar issues arise in the biosciences and chemical sciences as well. Examples of field applications include surface subsidence, pore collapse, cavity generation, hydraulic fracturing, thermal fracturing, wellbore collapse, sand production, fault activation, and disposal of drill cuttings. The above phenomena entail both economic as well as environmental concerns.

Another important related class of problems involves CO2 sequestration, which is proposed as a key strategy for mitigating climate change driven by high levels of anthropogenic CO2 being added to the atmosphere. In a CO2 sequestration project, fluid is injected into a deep subsurface reservoir (rather than being produced or extracted), so that inflation of the reservoir leads to uplift displacement of the overlying surface. As long as a CO2 sequestration site is removed from faults, this uplift is several centimeters, while its wavelength is in tens of kilometers, so that the uplift poses little danger to buildings and infrastructure. Nevertheless the uplift displacements are of great interest for non-intrusive monitoring of CO2 sequestration, which can be measured with a sub-millimeter precision using Interferometric Synthetic Aperture Radar (InSAR) technology. In contrast, intrusive monitoring via drill holes bored into the reservoir is expensive, with costs of several million dollars per well. Furthermore, such wells are the most likely pathway for future leakage of sequestered CO2 back into the atmosphere. Of course, if a CO2 sequestration site is close to a fault, one should be concerned about triggering instability leading to large surface displacements that may result in significant losses.

Collaborative Research: Error Estimation, Data Assimilation and Uncertainty Quantification for Multiphysics and Multiscale Processes in Geological Media

(funded by NSF)

The application of high performance computing to model subsurface processes occurring over multiple spatial and temporal scales is a science grand challenge that has important implications to society at large. Research on this grand challenge is at the confluence of advanced mathematics, computer science, fluid and solid mechanics and applied probability and statistics. We are engaging in a fresh new perspective by investigating and formulating rigorous error estimators for the numerical schemes employed to model multiphysics, multiscale processes in subsurface media. These error estimators, when coupled with advanced computational methods, can significantly speed up the task of uncertainty assessment and feedback control of subsurface processes.

We are also developing a uncertainty quantification scheme that will utilize the error estimators and rigorous quantification of prior geologic uncertainty. Underlying the computational and uncertainty quantification schemes will be a computer framework that rigorously takes into account the dynamic and complex communication and coordination patterns resulting from multiphysics, multinumerics, multiscale and multidomain couplings. In addition, we will investigate realistic physical models such a carbon sequestration in saline aquifers with real field data from the Cranfield Mississippi demonstration site. The ultimate transformative goal is to achieve predictive and decisional simulations, in which engineers reliably predict, control, and manage human interaction with geosystems.

Center for Frontiers of Subsurface Energy Security

(funded by DOE)

Currently mankind extracts most of the fuel for the global economy from underground. The byproducts of consuming this fuel enter the atmosphere or remain on the surface. This situation is no longer tenable. A critical step toward future energy systems will be the ability to cycle fuel byproducts back to their original home: the Earth’s subsurface. Applications of this concept include storing CO2 in deep geologic formations and securing radioactive materials in appropriately engineered repositories. Our goal is to fill gaps in the knowledge base so that subsurface storage schemes are reliable from the moment they open. Two scientific Grand Challenges, which will be investigated in this project, contribute to the gap between forecast and outcome in geologic systems. First, byproduct storage schemes will operate in a far-from-equilibrium state. Second, it is difficult to explain the emergence of patterns and other manifestations of correlated phenomena across length and time scales.

CFSES website