Al-Rudaini, Ali (Heriot-Watt University) | Geiger, Sebastian (Heriot-Watt University) | Mackay, Eric (Heriot-Watt University) | Maier, Christine (Heriot-Watt University) | Pola, Jackson (Heriot-Watt University)
We propose a workflow to optimise the configuration of multiple interacting continua (MINC) models and overcome the limitations of the classical dual-porosity model when simulating chemically enhanced oil recovery processes. Our new approach captures the evolution of the concentration front inside the matrix, which is key to design a more effective chemically enhanced oil recovery projects in naturally fractured reservoirs. Our workflow is intuitive and based on the simple concept that fine-scale single-porosity models capture fracture-matrix interaction accurately and can hence be easily applied in a commercial reservoir simulator. Results from the fine-scale single-porosity system are translated into an equivalent MINC method that yields more accurate results than the classical dual-porosity model or a MINC method where the shells are arbitrarily selected.
Our approach does not require the tuning of capillary pressure curves ("pseudoisation"), diffusion coefficients, MINC shells, or the generation of recovery type curves, all of which have been suggested in the past to model more complex recovery processes. A careful examination of the fine-scale single-porosity model ("reference case") shows that a number of nested shells emerge, describing the advance of the concentration and saturation fronts inside the matrix. The number of shells is related to the required degree of refinement, i.e. the number of shells, in the improved MINC model. Using the results from a fine-scale single-porosity simulation to set up the shells in the MINC model is easy and requires only simple volume calculations. It is hence independent of the chosen simulator.
Our improved MINC method yields significantly more accurate results compared to a classical dual-porosity model, a MINC method with equally sized shells, or a MINC model with arbitrarily refined shells for a number of recovery scenarios that cover a range of matrix wettabilities and permeabilities. In general, improved results can be obtained when selecting five or fewer shells in the MINC. However, the actual number of shells is case-specific. The largest improvement is observed for cases when the matrix permeability is low.
The novelty of our approach is the easy-to-use method to define shells for a MINC model to predict chemically enhanced oil recovery from naturally fractured reservoirs more accurately, especially in cases where the matrix has low permeability. Hence the improved MINC method is particularly suitable to model chemical EOR processes in (tight) fractured carbonates.
As an enhanced oil recovery method (EOR), chemical flooding has been implemented intensively for some years. Low Salinity WaterFlooding (LSWF) is a method that has become increasingly attractive. The prediction of reservoir behaviour can be made through numerical simulations and greatly helps with field management decisions. Simulations can be costly to run however and also incur numerical errors. Historically, analytical solutions were developed for the flow equations for waterflooding conditions, particularly for non-communicating strata. These have not yet been extended to chemical flooding which we do here, particularly for LSWF. Dispersion effects within layers also affect these solutions and we include these in this work.
Using fractional flow theory, we derive a mathematical solution to the flow equations for a set of layers to predict fluid flow and solute transport. Analytical solutions tell us the location of the lead (formation) waterfront in each layer. Previously, we developed a correction to this to include the effects of numerical and physical dispersion, based on one dimensional models. We used a similar correction to predict the location of the second waterfront in each layer which is induced by the chemical's effect on mobility. In this work we show that in multiple non-communicating layers, material balance can be used to deduce the inter-layer relationships of the various fronts that form. This is based on similar analysis developed for waterflooding although the calculations are more complex because of the development of multiple fronts.
The result is a predictive tool that we compare to numerical simulations and the precision is very good. Layers with contrasting petrophysical properties and wettability are considered. We also investigate the relationship between the fractional flow, effective salinity range, salinity dispersion and salinity retardation.
This work allows us to predict fluids and solute behaviour in reservoirs with non-communicating strata without running a simulator. The recovery factor and vertical sweeping efficiency are also very predictable. This helps us to upscale LSWF by deriving pseudo relative permeability based on our extension of fractional flow and solute transport into such 2D systems.
Pola, Jackson (Heriot-Watt University) | Geiger, Sebastian (Heriot-Watt University) | Mackay, Eric (Heriot-Watt University) | Bentley, Mark (Heriot-Watt University) | Maier, Christine (Heriot-Watt University) | Al-Rudaini, Ali (Heriot-Watt University)
We investigate how efficiently oil can be recovered from a carbonate rock during surfactant based enhanced oil recovery (EOR) at the core-scale, particularly when chemical processes change wettability, and analyse how geological heterogeneities, observed at the next larger scale (centimetre to decimetre) impacts the effectiveness of surfactant-based EOR at the inter-well scale.
To quantify how heterogeneity across scales impacts surfactant flooding, we combine laboratory experiments with simulation studies at the core- and inter-well scale. We first analysed a series of surfactant imbibition experiments at different surfactant concentrations (from 0 to 3 wt. %) using reservoir cores from the Wakamuk field, a carbonate reservoir in Indonesia. We then built a 3D simulation model of the laboratory experiment and matched the experimental data to identify the key physical mechanisms (e.g., reduction in interfacial tension (IFT) and wettability alteration) that lead to increased oil recovery. Next, we parametrised the surfactant models using assisted history-matching methods to calibrate the relative permeability and capillary pressure curves as a function of surfactant concentration. These models were then deployed in high-resolution simulations at the inter-well scale. These simulations captured the small-scale geological heterogeneities that are typical for a carbonate reservoir system, e.g., the Shuaiba formation in the Middle East, but are not resolved in field-scale models.
Our core-scale simulations demonstrate a change from co- to counter-current flow in the laboratory experiments and indicate that the resulting increase in oil recovery is due to a combination of IFT reduction, wettability alteration from oil- to water-wet, and capillary pressure restoration; these processes need to be captured adequately at the inter-well scale model. The increase in surfactant concentration above the critical micelle concentration (CMC) (i.e., from 1 to 3 wt. %) triggered the capillary pressure restoration and dominated recovery at the early-time. The changes in relative permeability and capillary curves during the surfactant floods were best modelled using a concentration-based interpolation. There is uncertainty when calibrating surfactant models using laboratory experiments. A key question hence is if geological heterogeneity at the inter-well scale masks these uncertainties.
Results from our high-resolution simulations show that large-scale heterogeneity impacts recovery predictions, but it is the coarsening of the grid, not the upscaling of permeability, that dominates the error in field-scale recovery predictions during surfactant based EOR. Indeed, the error arising from numerical dispersion during grid coarsening can be as large as the error arising when selecting an inaccurately configured surfactant model due to the lack of quality experimental data. Hence appropriate grid refinement, possibly using adaptive grid refinement, needs to be considered when setting up a surfactant based EOR simulation, along with the appropriate configuration of the surfactant model itself.
Produced water composition analysis provides evidence of what geochemical reactions are taking place in the reservoir. This information can be useful for predicting and managing oilfield mineral scale resulting from brine supersaturation.
This paper presents results of a study of the produced brine compositions from three wells in a field operated in the North Sea, with geochemical modelling complementing the analysis. The findings presented in this work provide evidence of magnesium depletion and sulphate retardation in a sandstone reservoir at 130° C.
This adjusted formation water composition was then used for calculations of the injection water fraction in each of the produced water samples. The Reacting Ions Toolkit was used to plot data in a variety of formats, including ion concentration vs. ion concentration, ion concentration vs. injection water fraction and ion concentration vs. time to identify trends and to examine the extent of involvement of the various ions in geochemical reactions.
The breakthrough of sulphate, a component primarily introduced during seawater flooding, was retarded during injection water breakthrough. Observed sulphate concentrations were lower than predicted for the case of brine/brine interactions only. The implication of this sulphate reduction was lower minimum inhibitor concentration required to control scale formation and longer squeeze treatment lifetimes for the operator.
A brine/rock interaction mechanism was proposed that involves magnesium depletion and is reproduced in the reactive transport model. 1D reactive transport modelling was performed to match possible
CO2 Water-Alternating-Gas injection (CO2 WAG), which involves complex phase and flow behaviour, is still a challenging task to simulate and predict accurately. In this paper, we focus specifically on the regime of viscous fingering flow in CO2 WAG in heterogeneous systems because of its importance. We investigated two key physical processes that occur during near-Miscible WAG (nMWAG) processes, namely oil stripping (Mechanism 1, M1) and low-interfacial-tension (IFT) film flow effects (Mechanism 2, M2). The low IFT effects in M2 manifest themselves in an increased mobility of oil phase due to film flow process (discussed below). The importance of properly simulating the interaction of viscous, compositional (M1), and low-interfacial-tension effects (M2) is clearly demonstrated in this study. Our specific aim is to improve the modelling of CO2 displacement in the transition from immiscible to miscible flows in CO2 WAG processes.
We simulated both immiscible and near-miscible CO2 WAG and also continuous CO2 displacements with unfavourable mobility ratios for 1D and 2D systems. 2D heterogeneous permeability fields were generated with certain Dykstra-Parsons coefficients and dimensionless correlation ranges. IFT (σgo) was calculated by the simulator as part of the compositional simulation using the McLeod-Sugden equation. The consequent IFT effects on relative permeability was imposed using two commonly used models, i.e.
We tested various combinations of oil-stripping effects (M1) and IFT effects (M2) to evaluate the potential impact of each mechanism on the flow behaviour such as the local displacement efficiency, the tracking of tracer flow and the ultimate oil recovery. Oil bypassed by viscous fingering/local heterogeneity, can be efficiently recovered by WAG in the cases where both M1 and M2 are taken into account (as opposed to either mechanism being considered alone). Through tracer analysis, we found that a major recovery mechanism in near-miscible displacement was
WAG (Water-Alternating-Gas) schemes have been applied in Brazilian carbonate reservoirs aiming to minimize residual oil saturation and gas flaring by recycling CO2 naturally being produced alongside hydrocarbon gas. However, applying WAG injection in highly reactive and heterogeneous carbonate rocks can potentially create severe scaling problems. This work develops a reactive transport simulation-based workflow to evaluate the impact of key WAG design parameters on oil recovery, scale deposition risk and CO2 storage to support multi-objective decision-making.
Compositional simulations of WAG scenarios were performed as part of a sensitivity study followed by statistical analysis in order to quantify to what extent the outcomes of interest are sensitive to variations on four WAG design parameters: WAG ratio, CO2 concentration in the injection gas stream, injection rate and solvent slug-size. We established an Equation-of-State (EoS) using PVT data, a representative geochemical model and well constrains designed to control production of injected fluids. Scale risk was assessed by calcite changes around the wells, precipitation in well tubing and surface facilities, and water breakthrough.
Results of this study showed that values of calcite rate constant (
Ultimately, we demonstrate the importance of integrating multiphase miscible displacement with geochemical reactions while modeling complex CO2-EOR in carbonate reservoirs and address how key design parameters impact our desired outcomes, knowledge that promotes a more robust decision-making framework.
Azuddin, Farhana Jaafar (Group Research & Technology, PETRONAS Institute of Petroleum Engineering, Heriot-Watt University) | Davis, Ivan (Institute of Petroleum Engineering, Heriot-Watt University) | Singleton, Mike (Institute of Petroleum Engineering, Heriot-Watt University) | Geiger, Sebastian (Institute of Petroleum Engineering, Heriot-Watt University) | Mackay, Eric (Institute of Petroleum Engineering, Heriot-Watt University) | Silva, Duarte (Institute of Petroleum Engineering, Heriot-Watt University)
When CO2 is injected into an aquifer, the injected CO2 is generally colder than the reservoir rock; this results in thermal gradients along the flow path. The temperature variation has an impact on CO2 solubility and the kinetics of any mineral reactions. Core flood experiments and associated reactive transport simulations were conducted to analyse thermal effects during CO2 injection in a dolomitic limestone aquifer and to quantify how CO2 solubility and mineral reactivity are affected.
The experiments were conducted by injecting acidified brine into an Edwards Limestone core sample. A back pressure of 400 psi and injection rates of 30 mL/hr and 300 mL/hr were used. A range of temperatures from 21 °C to 70 °C were examined. Changes in the outlet fluid composition and changes in porosity and permeability were analysed. A compositional simulation model was used to further analyse the experiments. The simulations were history-matched to the experimental data by changing the reactive surface area and the kinetic rate parameter. The calibrated model was then used to test the sensitivity to CO2 injection rate and temperature.
The impact of temperature on CO2-induced mineral reactions was observed from changes in mineral volume, porosity and permeability. The reaction rate constants estimated from the outlet solution concentrations are much lower than existing data for individual minerals. The estimated specific surface areas for carbonate minerals are in reasonable agreement with published values. The numerical investigations showed that at the lower temperatures, despite the reaction rates being slower, the solubility of the minerals was higher, and so as a result of these competing effects, moderately elevated calcium and magnesium concentrations were observed in the effluent. At higher temperatures, the solubilities of the minerals were lower, but now the reactions rates were higher, so similar effluent concentrations could be achieved. However, at higher flow rates, characterized by a lower Damköhler number, the residence times were shorter, and so lower effluent concentrations were observed. Additionally, the solubilities of calcite and dolomite varied to different extents with temperature, and so the calcium to magnesium molar ratio in the effluent brine increased with increasing temperature.
The change in mineral composition during CO2 injection varies between the near well zone and the deeper reservoir. Near the well where the temperatures will be lower, solubilities are elevated, but the kinetic reaction rates and residence times will be lower, somewhat limiting dissolution. Deeper in the aquifer the solubilities will be reduced and residence times will be longer, enabling an equilibrium to be established. Modelling is thus required to connect these flow regimes.
Vazquez, Oscar (Heriot Watt University ) | Ross, Gill (Chrysaor) | Jordan, Myles Martin (Nalco Champion) | Baskoro, Dionysius Angga Adhi (Heriot-Watt University) | Mackay, Eric (Heriot-Watt University) | Johnston, Clare (Nalco Champion) | Strachan, Alistair (Nalco Champion)
Oilfield-scale deposition is one of the important flow-assurance challenges facing the oil industry. There are a number of methods to mitigate oilfield scale, such as reducing sulfates in the injected brine, reducing water flow, removing damage by using dissolvers or physically by milling or reperforating, and inhibition, which is particularly recommended if a severe risk of sulfate-scale deposition is present. Inhibition consists of injecting a chemical that prevents the deposition of scale, either by stopping nucleation or by retarding crystal growth. The inhibiting chemicals are either injected in a dedicated continuous line or bullheaded as a batch treatment into the formation, commonly known as a scale-squeeze treatment. In general, scale-squeeze treatments consist of the following stages: preflush to condition the formation or act as a buffer to displace tubing fluids; the main treatment, where the main pill of chemical is injected; overflush to displace the chemical deep into the reservoir; a shut-in stage to allow further chemical retention; and placing the well back in production. The well will be protected as long as the concentration of the chemical in the produced brine is greater than a certain threshold, commonly known as minimum inhibitor concentration (MIC). This value is usually between 1 and 20 ppm. The most important factor in a squeeze-treatment design is the squeeze lifetime, which is determined by the volume of water or days of production where the chemical-return concentration is greater than the MIC.
The main purpose of this paper is to describe the automatic optimization of squeeze-treatment designs using an optimization algorithm, in particular particle-swarm optimization (PSO). The algorithm provides a number of optimal designs, which result in squeeze lifetimes close to the target. To determine the most efficient design of the optimal designs identified by the algorithm, the following objectives were considered: operational-deployment costs, chemical cost, total-injected-water volume, and squeeze-treatment lifetime. Operational-deployment costs include the support vessel, pump, and tank hire. There might not be a single design optimizing all objectives, and thus the problem becomes a multiobjective optimization. Therefore, a number of Pareto optimal solutions exist. These designs are not dominated by any other design and cannot be bettered. Calculating the Pareto is essential to identify the most efficient design (i.e., the most cost-effective design).
Low-salinity waterflooding (LSWF) is a promising process that could lead to increased oil recovery. To date, the greatest attention has been paid to the complex oil/water/rock chemical reactions that might explain the mechanisms of LSWF, and it is generally accepted that these result in behavior equivalent to changing oil and water mobility. This behavior is modeled using an effective salinity range and weighting function to gradually switch from high- to low-salinity relative permeability curves. There has been limited attention on physical transport of fluids during LSWF, particularly at large scale. We focus on how the salinity profile interacts with water fronts through the effective salinity range and dispersion to alter the transport behavior and change the flow velocities, particularly for the salinity profile.
We examined a numerical simulation of LSWF at the reservoir scale. Various representations of the effective salinity range and weighting function were also examined. The dispersion of salinity was compared with a theoretical form of numerical dispersion based on input parameters. We also compared salinity movement with the analytical solution of the conventional dispersion/advection equation.
From simulations we observed that salinity is dispersed as analytically predicted, although the advection velocity might be changed. In advection-dominated flow, the salinity profile moves at the speed of the injected water. However, as dispersion increases, the mixing zone falls under the influence of the faster-moving formation water and, thus, speeds up. To predict the salinity profile theoretically, we have modified the advection term of the analytical solution as a function of the formation- and injected-water velocities, Péclet number, and effective salinity range.
This important result enables prediction of the salinity transport by this newly derived modification of the analytical solution for 1D flow. We can understand the correction to the flow behavior and quantify it from the model input parameters. At the reservoir scale, we typically simulate flow on coarse grids, which introduces numerical dispersion or must include physical dispersion from underlying heterogeneity. Corrections to the equations can contribute to improving the precision of the coarse-scale models, and, more generally, the suggested form of the correction can also be used to calculate the movement of any solute that transports across an interface between two mobile fluids. We can also better understand the relative behaviors of passive tracers and those that are adsorbed.
Numerical stability and precision are required when using simulations to predict Enhanced Oil Recovery processes and these can be difficult to achieve for Low Salinity Water Flooding (LSWF). In this paper we investigate the conditions that lead to numerical instabilities when simulating LSWF. We also examine how to achieve more precise simulation results by upscaling the flow behaviour in an effective manner.
An implicit finite difference numerical solver was used to simulate LSWF. The stability and precision of the numerical solution has been examined as a function of changing the grid size and time step. We used the Peclet number to characterise numerical dispersion with these changes. Time step length was compared with the Courant condition. We also investigated some of the nonlinear elements of the simulation model such as the differences between the concentrations of connate water salinity and the injected brine, effective salinity concentration range and the net mobility change on fluids through changing the salt concentration.
We observe that numerical solution of LSWF tends to be conditionally stable, with problems occurring as a function of the range of effective salinity concentration relative to the initial reservoir water and the injected brine concentrations. We observe that the Courant condition is necessary but not sufficient. By definition, the precision of the numerical solution decreased when increasing numerical dispersion but this also resulted in slowing down the low salinity water and increased the velocity of the formation water further reducing precision. These numerical problems mainly depend on fluid mobility as a function of salt concentration. We conclude that the total range and the mid-concentration of effective salinity affect the stability and precision of the numerical solution, respectively. In this work, we have developed two approaches that can be used to upscale simulations of LSWF and tackle the numerical instability problems. The first method is based on a mathematical form that gives the relationship between the fractional flow, effective salinity concentration and the Peclet number. The second method is that we have established an unconventional proxy method that can be used to imitiate pseudo relative permeabilities.
This work enables us for the first time to simulate LSWF by using a single table of pseudo relative permeability data, instead of two tables as traditionally done in previous studies. This removes the need for relative permeability interpolation during the simulation and will help engineers to more efficiently and accurately assess the potential for improving oil recovery using LSWF and optimise the value of the field development. We also avoid the numerical instabilities inherent in the traditional LSWF model.