No abstract

Steam foam is a hybrid and novel method of the thermal and chemical flooding to improve the sweep efficiency of steam for producing heavy crude oils. Steam injection is a mature process to substantially reduce the oil viscosity in heavy oil reservoirs to increase its mobility. Steam flooding is an unstable displacement since the gravity of steam causes poor vertical sweep efficiency due to the gravity override in thick high permeability pay zones and poor areal sweep efficiency in high permeability channels with high connectivity. On the other hand foam reduces the mobility of steam by stabilizing the liquid lamellae that cause some or all of the steam to exist as a discontinuous phase. Therefore, foam plugs large pores to divert the flow into the low permeability zones and controls gravity override. Foam increases the pressure gradient slightly in the steam swept regions and leads to heating oil more efficiently when steam diverts into the cold unswept regions. Furthermore, surfactant mobilizes the high viscous oil by emulsification and reduction of interfacial tension. The synergy of steam, surfactant, and foam has the potential to greatly improve the recovery of heavy oil reservoirs.Based on a literature survey, steam foam injection has been conducted in both laboratory corefloods and few field pilots. On the other hand, existing numerical simulators have not been able to capture the mechanisms involved in such a process. In this paper, we present the development and implementation of a new robust steam formulation in a four phase chemical flooding reservoir simulator (UTCHEM) to model and understand the contribution of each mechanism such as viscosity reduction, emulsification, and foam for mobility control. Results illustrate that the steam foam process controls the mobility of steam to avoid incomplete vertical sweep due to gravity segregation. Formation of the emulsion phase by condensing steam along with the presence of water leads to an increase in the emulsion viscosity and thereby decreases water production. The presence of surfactant and emulsification of oil either as water in oil or oil in water emulsions can also impact the displacement and propagation of viscous oil.The mechanistic understanding of steam foam process and improvement of the heat transfer compared to conventional steam flooding is a key finding in this research to optimize the technology that unlocks heavy oil reservoirs with favorable economics.

This paper presents an improved numerical model to predict the onset of reservoir souring in sea-water injected reservoirs. The model is developed to study the effect of temperature, salinity, and pH on the growth of sulfate-reducing bacteria (SRB), which are responsible for hydrogen sulfate generation. Furthermore, we investigate the influence of the environmental factors on the prediction of reservoir souring. First, we model the mechanisms involved in reservoir souring and then identify the parameters that have the crucial effects on the prediction. Previous models assumed that the maximum growth rate is independent and represented by a constant value. They also neglected the competition between different types of substrates. Therefore, we introduce a new mathematical model to express the maximum growth rate of SRB as a function of temperature, salinity, and pH in the first-order Monod kinetics equation. Then, we discuss the modeling of the competition between different types of substrates. Finally, we implement the model into a 3D finite difference non-isothermal reservoir simulator. The new model results are compared to previous model results and validated against experimental data. Next, a comprehensive sensitivity analysis is performed to show the effect of temperature, salinity, and pH on bacterial growth and the prediction of souring in a numerical reservoir (or core) model. Taking the effect of environmental parameters into account shows the deficiency of previous models to estimate the reservoir souring. Previous models underestimate the concentration of hydrogen sulfate generation per mass of biodegraded substrate (H2S generation coefficient). The results suggest that the hydrogen sulfide concentration increases as the reservoir temperature, salinity, and pH reach the optimum temperature, pH, and salinity required for SRB to reach its maximum growth rate. The present work differs from earlier works by explicitly determining parametric values required for a kinetic model. This model is as an effective approach to accurately predict the concentration of hydrogen sulfide and thus facilitating accurate decisions on remedial actions.

Polymer flooding has been commercially applied to a number of viscous oil fields in the past decade and gradually gained more popularity. Due to limited injectivity in viscous-oil reservoirs, a relatively low polymer viscosity is usually used to avoid excessive injection pressure. In such a case, mobility ratio of polymer solution to oil is much greater than one, which implies unstable flow and strong viscous fingering. Existing reservoir simulators lack the capability of modeling such a physical phenomenon. Since many viscous-oil reservoirs have high permeability contrast between layers, we are motivated to study, for the first time, the impact of crossflow between different layers considering the presence of viscous fingering. Numerical modeling polymer floods with crossflow in a layered viscous-oil reservoir is difficult due to two major challenges: first is how to correctly allocate flow rates from the wellbore to multiple layers; and second is how to capture the viscous fingering effect without using excessively fine grids. To address the first issue, we developed an implicit well-rate-allocation model based on the potential method, which fully couples all the wellbore segments of each well with reservoir gridblocks to ensure a physical wellbore pressure. To deal with the second challenge, we implemented the effective fingering model, which is an upscaling model that lumps all the viscous fingers in a coarse grid block into one fictitious finger to allow for accurate estimation of fingering strength and growth during unstable flows. Both models were validated individually against the analytical solution or experimental data. The integrative module including the two new capabilities was used to simulate a polymer flood following a waterflood in a layer-cake reservoir in North America with moderate oil viscosity. We observed the fast propagation of water fronts and small fingering fraction in high permeability layers during the waterflooding phase, indicating active channeling and viscous fingering. The subsequent polymer flooding minimized both factors of oil bypassing and led to stable flow and high sweep efficiency. Without the implicit well-rate-allocation model, crossflow was overestimated and wellbore pressures of different well blocks were not consistent. Without the effective-fingering model, oil recovery was overestimated due to the lack of accounting for viscous fingering. The simulation results indicated that polymer flooding improved both displacement and sweep efficiencies. The model has shown comprehensive capabilities in reservoir simulations of polymer floods including unstable floods and crossflows between layers. This is a major significance to optimization of non-thermal viscous-oil EOR projects and also making more informed operational decisions for field developments.

Chemical enhanced oil recovery (CEOR) of heavy oils is growing in volume and scope due to advances in the technology and field experience. This work describes a new methodology to select a CEOR strategy in a heavy oil reservoir when several viable options exist. We applied this methodology to the Pelican Lake field in Alberta. We evaluated water flooding, polymer flooding, alkaline-surfactant-polymer (ASP) flooding, alkaline-co-solvent-polymer (ACP) flooding and polymer flooding followed by ASP flooding in laboratory tests. We executed new experiments including microemulsion phase behavior, polymer rheology and corefloods representing these various strategies. These experiments were designed to help understand the role of mobility control in chemical flooding of heavy oils. UTCHEM, the University of Texas Chemical Flooding Simulator, was used to model experimental results, and to scale them up in pilot simulations using heterogeneous geological models representative of Pelican Lake. We report results for the selection of promising CEOR strategies for implementation in Pelican Lake based on the new laboratory experiments, reservoir simulations and our qualitative understanding of their various advantages and disadvantages. We present simulation results of a pilot using horizontal wells in a heterogeneous geological model representative of the reservoir. We simulated the various chemical EOR processes using the matched experimental data and evaluated them in terms of total oil production, time to completion and complexity. In-situ oil viscosity and operational injection limits were evaluated as crucial sensitivities. We make recommendations for CEOR implementation based on simulation study results and our understanding of relative process risks and costs.