Ian D. Gates

The Origin, Prediction and Impact of Oil Viscosity Heterogeneity on the Production Characteristics of Tar Sand and Heavy Oil Reservoirs

The defining characteristic of heavy and super heavy oilfields is the large spatial variation in fluid properties, such as oil viscosity, commonly seen within the reservoirs. Traditional heavy oil and tar sand exploration and production strategies rely significantly on characterization of key reservoir heterogeneities and assessments of fluid saturations. While it is important to understand how these properties vary, the spatial distribution of fluid properties can often dominate production behavior but surprisingly, are usually ignored! Heavy oil and tar sands are formed by microbial degradation of conventional crude oils over geological timescales. Constraints such as oil charge mixing, reservoirtemperature dependant biodegradation rate and supply of water and nutrients to the organisms ultimately dictate the final distribution of API gravity and viscosity found in heavy oil fields. Large-scale lateral and small-scale vertical variations in fluid properties due to interaction of biodegradation and charge mixing are common, with up to orders of magnitude variation in viscosity over the thickness of a reservoir. These variations are often predictable and can be integrated into reservoir simulation models in a manner similar to specifying geological heterogeneity. In this work, we describe and illustrate quantitative geological controls on fluid property variations and show how petroleum geochemistry can be used to rapidly produce high resolution fluid property images of tar sand and heavy oil reservoirs. The impact of viscosity variations in a heavy oil reservoir on production depends on recovery method. Numerical thermal reservoir simulations reveal that oil viscosity heterogeneity (i.e., a vertical viscosity profile in the reservoir) lowers the oil production volumes from SteamAssisted Gravity Drainage in geologically realistic reservoirs compared to results from equivalent models run with uniform average viscosity profiles. Similar results are found for the Cyclic Steam Stimulation process. In cases with viscosity profiles, the relatively high viscosity at the base of the reservoir slows the growth of steam chambers relative to that in uniform viscosity reservoirs. We also describe how the chemical fluid heterogeneities can be used to predict oil viscosity from well cuttings and/or core or to de-mix produced oils into zonal contributions from different parts of the production well.

Mass transfer limitations in embryoid bodies during human embryonic stem cell differentiation.

Due to their ability to differentiate into cell types from all the three germ layers and their potential unlimited capacity for expansion, embryonic stem cells have tremendous potential to treat diseases and injuries. Spontaneous differentiation of human embryonic stem cells (hESCs) is influenced by the size of the differentiating embryoid bodies (EBs). To further understand the dynamics between nutrient mass transfer, EB size, and stem cell differentiation, a transient mass diffusion model of a single hESC EB was constructed. The results revealed that the oxygen concentration at the centers of large EBs (400-µm radius) was 50% lower when compared to that in smaller EBs (200-µm radius). In addition, the concentration profile of cytokines within an EB depended strongly on their depletion rate, with higher depletion rates resulting in cytokine concentrations that varied significantly throughout the EB. A comparison of the results of our model with published experimental data reveals a close correlation between the fraction of cells that differentiate to a given lineage and the fraction of cells exposed to different oxygen or cytokine concentrations. This, along with other data from the literature, suggests that diffusive mass transfer influences the differentiation of hESCs within EBs by controlling the spatial distribution of soluble factors. This has important implications for research involving the differentiation of embryonic stem cells in EBs, as well as for bioprocess design and the development of robust differentiation protocols where mass transfer could be altered to control the cell differentiation trajectory.

Optimization of Steam Assisted Gravity Drainage in McMurray Reservoir

Many field tests of the steam assisted gravity drainage (SAGD) process have been conducted and have shown that the process is a technically effective one at extracting oil from heavy oil and bitumen reservoirs. However, it has not been firmly established whether the technology is operated at optimized conditions to yield maximum economic returns. This is especially important because typically SAGD depends on the combustion of natural gas to generate steam and this is the dominant cost. The cost of natural gas can be significant when natural gas prices are high. This research evaluates the use of a genetic algorithm optimization scheme to control a commercially available thermal reservoir simulator in order to optimize the steam injection strategy to reduce the cumulative oil to steam ratio (cSOR). The reservoir description is typical of that from a low to medium quality Athabasca reservoir. The results show that the injection strategy can be altered to reduce the cSOR up to 50% from a uniform injection pressure strategy to 1 after the steam injection strategy has been optimized. The optimized profile has high steam injection pressure at the beginning of the process before the steam chamber reaches the top of the oil-rich zone. Before the chamber reaches the oil pay, with high injection pressure, the saturation temperature is high and there are no thermal losses to the overburden. After the chamber reaches the top of the formation, the injection pressure is lowered throughout the remainder of the process. This reduction of injection pressure implies that the saturation temperature falls and consequently the losses to the overburden are lowered. Thus the overall thermal efficiency of the process is enhanced. The optimized strategy is compared to processes operating at 1,000 and 2,000 kPa constant injection pressure.

Design of the Steam and Solvent Injection Strategy in Expanding Solvent Steam-Assisted Gravity Drainage

Steam Assited Gravity Drainage (SAGD) is a commercial in situ recovery technology that is effective at recovering heavy oil and bimen. However generation of steam by combusting natural gas adversely impacts the economics of the process, especially when the natural gas price is high, as has been the case lately. It has been shown that solvent additives can improve oil production rates, or at least maintain similar oil production rates with reduced steam injection This is the basis of the Expanding Solvent Steam-Assisted Gravity Drainage (ES-SAGD)process. The key is that steam plus solvent is better man steam alone to mobilize heavy oil in the reservoir. This implies that ES.SAGD can potrntially use less water and require smaller water handling and moment facilities than those in SAGD. One key capacity of ES-SAGD is that the recevered solvent can be recycled and re-injected into the reservoir. However, if too much solvent is injected and too little is recovered, the process can be uneconomic because the solvent is open more valuable than the prodoced heavy oil. In this research the solvent injection strategy is designed for a single welpair ES.SAGD operation by optimizing the net energy injected to oil into in a detailed and threedimensional heavy oil reservoir. The process parameters for design include the operating pressure and relative amount fo steam and solvent in the injected steam. The results show that the operating pressure and injection strategy must be carefully controlled to ensure high energy effeciency and solvent recovery.

Factorial experimental design for the culture of human embryonic stem cells as aggregates in stirred suspension bioreactors reveals the potential for interaction effects between bioprocess parameters.

Traditional optimization of culture parameters for the large-scale culture of human embryonic stem cells (ESCs) as aggregates is carried out in a stepwise manner whereby the effect of varying each culture parameter is investigated individually. However, as evidenced by the wide range of published protocols and culture performance indicators (growth rates, pluripotency marker expression, etc.), there is a lack of systematic investigation into the true effect of varying culture parameters especially with respect to potential interactions between culture variables. Here we describe the design and execution of a two-parameter, three-level (3(2)) factorial experiment resulting in nine conditions that were run in duplicate 125-mL stirred suspension bioreactors. The two parameters investigated here were inoculation density and agitation rate, which are easily controlled, but currently, poorly characterized. Cell readouts analyzed included fold expansion, maximum density, and exponential growth rate. Our results reveal that the choice of best case culture parameters was dependent on which cell property was chosen as the primary output variable. Subsequent statistical analyses via two-way analysis of variance indicated significant interaction effects between inoculation density and agitation rate specifically in the case of exponential growth rates. Results indicate that stepwise optimization has the potential to miss out on the true optimal case. In addition, choosing an optimum condition for a culture output of interest from the factorial design yielded similar results when repeated with the same cell line indicating reproducibility. We finally validated that human ESCs remain pluripotent in suspension culture as aggregates under our optimal conditions and maintain their differentiation capabilities as well as a stable karyotype and strong expression levels of specific human ESC markers over several passages in suspension bioreactors.

Pore‐network modeling of biofilm evolution in porous media

The influence of bacterial biomass on hydraulic properties of porous media (bioclogging) has been explored as a viable means for optimizing subsurface bioremediation and microbial enhanced oil recovery. In this study, we present a pore network simulator for modeling biofilm evolution in porous media including hydrodynamics and nutrient transport based on coupling of advection transport with Fickian diffusion and a reaction term to account for nutrient consumption. Biofilm has non‐zero permeability permitting liquid flow and transport through the biofilm itself. To handle simultaneous mass transfer in both liquid and biofilm in a pore element, a dual‐diffusion mass transfer model is introduced. The influence of nutrient limitation on predicted results is explored. Nutrient concentration in the network is affected by diffusion coefficient for nutrient transfer across biofilm (compared to water/water diffusion coefficient) under advection dominated transport, represented by mass transport Péclet number >1. The model correctly predicts a dependence of rate of biomass accumulation on inlet concentration. Poor network connectivity shows a significantly large reduction of permeability, for a small biomass pore volume. Biotechnol. Bioeng. 2011;108: 2413–2423.

Real time monitoring of biofilm development under flow conditions in porous media.

Biofilm growth can impact the effectiveness of industrial processes that involve porous media. To better understand and characterize how biofilms develop and affect hydraulic properties in porous media, both spatial and temporal development of biofilms under flow conditions was investigated in a translucent porous medium by using Pseudomonas fluorescens HK44, a bacterial strain genetically engineered to luminesce in the presence of an induction agent. Real-time visualization of luminescent biofilm growth patterns under constant pressure conditions was captured using a CCD camera. Images obtained over 8 days revealed that variations in bioluminescence intensity could be correlated to biofilm cell density and hydraulic conductivity. These results were used to develop a real-time imaging method to study the dynamic behavior of biofilm evolution in a porous medium, thereby providing a new tool to investigate the impact of biological fouling in porous media under flow conditions.

Multiphase Flow in Fractures: Co-Current and Counter-Current Flow in a Fracture

Multiphase flow through fractures is important not only for naturally fractured petroleum reservoirs but also for underground disposal of radioactive waste and geothermal hydrotransport, cap rock integrity, as well as underground water and aquifer flow. For instance, naturally fractured reservoirs located in Northern Alberta contain large quantities of heavy oil and bitumen. It still remains unclear how multiple phases flow in fractures and how to determine the relative permeability of each phase that can be used in reservoir simulators. In typical practice, simulation of fractured reservoirs uses, in general, very crude and unproven hypotheses such as linear relative permeability curves. However, by using inaccurate relative permeability curves, large errors of the predicted oil recovery can result. In this work, a relatively simple flow model is derived to determine analytic functions for the relative permeability curves versus phase saturation in a single fracture. The results show that relative permeability is not just a function of the fluid saturations but also of the fluid properties and flow pattern within the fracture itself. The analysis reveals that at certain viscosity ratios and flow pattern conditions, the relative permeability of one phase can exceed unity owing to lubrication effects. The available experimental data confirms the validity of the proposed model.

Using bacterial bioluminescence to evaluate the impact of biofilm on porous media hydraulic properties.

Biofilm formation in natural and engineered porous systems can significantly impact hydrodynamics by reducing porosity and permeability. To better understand and characterize how biofilms influence hydrodynamic properties in porous systems, the genetically engineered bioluminescent bacterial strain Pseudomonas fluorescens HK44 was used to quantify microbial population characteristics and biofilm properties in a translucent porous medium. Power law relationships were found to exist between bacterial bioluminescence and cell density, fraction of void space occupied by biofilm (i.e. biofilm saturation), and hydraulic conductivity. The simultaneous evaluation of biofilm saturation and porous medium hydraulic conductivity in real time using a non-destructive approach enabled the construction of relative hydraulic conductivity curves. Such information can facilitate simulation studies related to biological activity in porous structures, and support the development of new models to describe the dynamic behavior of biofilm and fluid flow in porous media. The bioluminescence based approach described here will allow for improved understanding and control of industrially relevant processes such as biofiltration and bioremediation.

The effect of fracture aperture and flow rate ratios on two-phase flow in smooth-walled single fracture

This work experimentally examines the co-current flow of oil and water in moderately oil-wet smooth-walled single fractures. The focus of our investigation is on studying the effects of varying fracture aperture and flow rate ratios on relative permeability to oil and water. The phase distribution and flow regimes within the fracture were closely monitored and found to vary with the flow rate ratio and total flow rate, and appeared to have a direct impact on the relative permeability. Experimental relative permeability data exhibited variations in shape indicating the effects of fracture aperture and flow ratios. Also, the data show the effects of oil–water phase interference, and phase saturation changes on the relative permeabilities for each fracture configuration. A couple of two-phase relative permeability models, namely, viscous coupling model, and homogenous single-phase approach, were tested against the experimental relative permeability data. This work provides insight into the nature of two-phase flow in a single fracture and could help in better modeling of more complex fracture networks.