Lesley A. James

Simultaneous and sequential approaches to joint optimization of well placement and control

Determining optimal well placement and control is essential to maximizing production from an oil field. Most academic literature to date has treated optimal placement and control as two separate problems; well placement problems, in particular, are often solved assuming some fixed flow rate or bottom-hole pressure at injection and production wells. Optimal placement of wells, however, does depend on the control strategy being employed. Determining a truly optimal configuration of wells thus requires that the control parameters be allowed to vary as well. This presents a challenging optimization problem, since well location and control parameters have different properties from one another. In this paper, we address the placement and control optimization problem jointly using approaches that combine a global search strategy (particle swarm optimization, or PSO) with a local generalized pattern search (GPS) strategy. Using PSO promotes a full, semi-random exploration of the search space, while GPS allows us to locally optimize parameters in a systematic way. We focus primarily on two approaches combining these two algorithms. The first is to hybridize them into a single algorithm that acts on all variables simultaneously, while the second is to apply them sequentially to decoupled well placement and well control problems. We find that although the best method for a given problem is context-specific, decoupling the problem may provide benefits over a fully simultaneous approach.

Water Enhancement Using Nanoparticles in Water Alternating Gas (WAG) Micromodel Experiments

Nanotechnology has found widespread application in a diverse range of industries. Researchers are now investigating whether nanotechnology can be applied to enhance oil recovery (EOR). The goal of enhanced oil recovery is to manipulate the fluid-fluid properties (interfacial tension, viscosity), and fluid-rock properties (contact angle, relative permeability) between the injected fluid and the residual oil phase to improve pore scale recovery efficiency. Adding nanoparticles to the injected water has been shown to improve oil recovery. In this study, nanoparticles were added to the water phase of water alternating gas (WAG) and injected into waterflood residual oil in two dimensional glass micromodels to study the effect of the nanoparticles qualitatively at low pressures. Silicon oxide (SiO2) and aluminum oxide (Al2O3) nanoparticles, at different concentrations, were dispersed in the brine and injected as the water phase in WAG followed by air as the gas phase. Response Surface Methodology (RSM) was used to investigate the effect of the factors and interactions between the factors on oil recovery. The results from the micromodel studies indicate that adding a small amount of nanoparticles to the brine can enhance residual oil recovery.

Asphaltene laboratory assessment of a heavy onshore reservoir during pressure, temperature and composition variations to predict asphaltene onset pressure

An Iranian heavy oil reservoir recently encountered challenges in oil production rate, and further investigation has proven that asphaltene precipitation was the root cause of this problem. In addition, CO2 gas injection could be an appropriate remedy to enhance the production of heavy crudes. In this study, high pressure-high temperature asphaltene precipitation experiments were performed at different temperatures and pressures to investigate the asphaltene phase behavior during the natural depletion process and CO2 gas injection. Compositional modeling of experimental data predicted onset points at different temperatures which determine the zone of maximum probability of asphaltene precipitation for the studied heavy oil reservoir. Also, the effect of CO2 gas injection was investigated as a function of CO2 concentration and pressure. It was found that a CO2-oil ratio of 40% is the optimum for limiting precipitation to have the least formation damage and surface instrument contamination.

Experimental Investigation of the VAPEX Process in Vuggy Porous Media

In this paper, the application of the vapor extraction (VAPEX) process was investigated to recover Cold Lake bitumen from vuggy porous media with n-pentane as the hydrocarbon solvent. Seven different sintered glass-bead models were designed and fabricated—four of which were vugular media with different vuggyto total-pore-volume (PV) ratios. The vugs were arranged in aligned and staggered configurations. Three homogeneous sintered glass-bead models of different permeability and porosity were also fabricated to serve as baselines. The vug sizes were controlled in a narrow size-distribution range by embedding wood particles of uniform volumes (20 mm each) in the packing of the glass-bead continuum, sandwiched between two parallel glass plates. The packing assembly was then sintered in the muffle furnace. For each particular VAPEX experiment, the oil-recovery performance was characterized by measurements [e.g., live-oil and dead-oil production rates, live-oil solvent content, and Residual Oil Saturation (ROS) (in the invaded area of the models)]. It was observed that the vugs significantly facilitated the live-oil production from the vuggy models compared with the corresponding homogeneous baseline model with the same matrix permeability. The increase in the vug porosity of the porous space significantly increased the liveand dead-oil production rates, and it slightly decreased the extent of ROS in the model. Unlike the sintered homogeneous models for which the live-oil-production rate remains reasonably constant during the lateral spreading phase of the VAPEX process, the vuggy-porosity models displayed a boost in the live-oil production rate when several vugs were being invaded by the solvent vapor. This behavior was more pronounced in the case of aligned vugs in which the vugs were closer to each other, and more vugs were invaded simultaneously compared with the case of a staggered-vug configuration. The enhanced pore-level mixing of solvent with bitumen, the improved petrophysical properties of the porous medium, and the flow communication of matrix with the vugs were found to enhance the live oil drainage towards the production well.

Simultaneous Optimization of Well Placement and Control Using a Hybrid Global-local Strategy

Optimal placement and control of wells is essential to ensuring maximal net present value (NPV) or total oil recovery when developing an oil field. The majority of academic literature treats optimal placement and control as two separate problems; however, treating the problems simultaneously may allow us to achieve better results. The objective function (i.e. NPV) in this joint problem tends to vary nonsmoothly as positional parameters are varied, but smoothly in the control parameters. This suggests an approach that utilizes both global and local optimization techniques. In this paper we address the placement and control optimization problem simultaneously with two approaches combining a global search strategy (particle swarm optimization, or PSO), which operates over all variables, along with a local generalized pattern search (GPS) strategy, which operates primarily on the control parameters. The first approach is a hybrid PSO/GPS algorithm which optimizes over all positional and control variables simultaneously, while the second approach decouples the problem into separate placement and control problems, and attempts to solve them sequentially. Simulation experiments show that both approaches tend to outperform PSO in simple problems, while the decoupled approach may be the most suitable for more complicated cases.

Resilience Analysis of a Remote Offshore Oil and Gas Facility for a Potential Hydrocarbon Release: Resilience Analysis of a Remote Offshore Operation

Resilience is the capability of a system to adjust its functionality during a disturbance or perturbation. The present work attempts to quantify resilience as a function of reliability, vulnerability, and maintainability. The approach assesses proactive and reactive defense mechanisms along with operational factors to respond to unwanted disturbances and perturbation. This article employs a Bayesian network format to build a resilience model. The application of the model is tested on hydrocarbon-release scenarios during an offloading operation in a remote and harsh environment. The model identifies requirements for robust recovery and adaptability during an unplanned scenario related to a hydrocarbon release. This study attempts to relate the resilience capacity of a system to the systems absorptive, adaptive, and restorative capacities. These factors influence predisaster and postdisaster strategies that can be mapped to enhance the resilience of the system.

A new streamline model for near-well flow validated with radial flow experiments

Streamline simulation is a powerful tool that can be used for full field forecasting, history matching, flood optimization, and displacement visualization. This paper presents the development and the application of a new semi-analytical streamline simulation method in the near-wellbore region in polar/cylindrical coordinate systems. The main objective of this paper is to study the effects of the permeability heterogeneity and well completion details in the near-wellbore region. These effects dictate the streamline geometries, which in turn influence well productivity. Previous streamline applications used a constant flow rate for each stream tube. In this paper, streamline simulation is performed under the assumption of constant pressure boundaries, which is a novel and non-trivial extension of streamline simulation. Solutions are constructed by treating each stream tube as a flow unit by invoking analytical solutions for such geometries. In addition, visualization experiments are conducted to investigate the effect of the heterogeneity. Two-dimensional waterflooding visualization experiments in radial porous media are performed with constant pressure boundaries. The streamline simulator is applied to history match the relative permeabilities using these experiments, thereby validating the new near-well streamline method.

A New Coupled Axial-Radial Productivity Model for Horizontal Wells with Application to High Order Numerical Modeling

For long, highly productive wells, frictional pressure loss cannot be ignored. The axial flow along the well trajectory in the near-well region must therefore also be considered. A new, fully analytical model for coupled radial well inflow and axial reservoir flow has been developed. The new model will be briefly reviewed and solutions to steady state flow summarized. A discussion on the usage of the new model in simulation of horizontal wells together with its numerical performance compared to standard finite difference methods will be presented. The new analytical model has been used in the formulation of a numerical scheme for simulation of coupled well inflow and near-well reservoir flow. The analytical model results in a linear pressure distribution in the axial direction and a logarithmic pressure distribution in the radial direction in each near-well reservoir segment. Therefore, the pressure distribution is piecewise linear/logarithmic, contrary to existing piecewise constant distribution resulting from a standard finite difference method. Calculation examples are presented applying both the new method and the standard finite difference method to determine the pressure profiles and flow rates in both the wellbore and the near-well reservoir. Numerical results show that the new method represents a substantial improvement compared to a standard finite difference method, requiring fewer segments to achieve the same accuracy. The new method is more accurate especially near the heel, where accuracy is most important. This numerical scheme has also been proved to be higher order accurate in space discretization than a standard finite difference scheme. Since the axial flow rate is built into the new model analytically, the need for local grid refinements around the well is reduced.

Characteristic of Permeability and Porosity of a 2D High-Permeable Model with Etched Network Channels

Waterflooding is the most common development method for oil field. However, long-term water injection could result in the formation of high-permeable zone in reservoir. The high-permeable zone would reduce water sweeping efficiency, making water injection ineffective. The accurate understanding of the high-permeable may contribute to the selection of effective and efficient governing methods, which could enhance oil recovery further. The characteristic of permeability and porosity is the crucial parameter to describe high-permeable zone. A customized macroscopic two-dimensional etched network channel model (Khezrnejad et al. Nanofluid enhanced oil recovery–mobility ratio, surface chemistry, or both?, In: International symposium of the Society of Core Analysts, St. John’s Newfoundland and Labrador, Canada, 2015, pp 16–21, [1]) was used to simulate the high-permeable zone by long-term water flooding in the research (Han et al. in Multiscale pore structure characterization by combining image analysis and mercury porosimetry, In: SPE Europec/EAGE annual conference and exhibition, Society of Petroleum Engineers, 2006 [2]). Because of the small pressure difference in the model, the constant head method was conducted to measure the permeability. Meanwhile, the capacity of permeation water was measured by falling head method, with the coefficient of permeability obtained. Tiab and Donaldson (Petrophysics: theory and practice of measuring reservoir rock and fluid transport properties, Gulf professional publishing, Houston, Texas, 2015, [3]) To simulate the primitive formation condition, the kerosene was saturated with the model and the porosity was calculated after the pore fulfilled. The experimental results showed that the macroscopic model could represent the condition of high-permeable zone after waterflooding. The measurement of permeability and coefficient of permeability was feasible. Comparing the two different methods derived from Darcy`s equation which characterized the permeable and discussing the experimental results in details, the constant head method to characterize the permeability was more accurate. The result of porosity measurement indicated that the use of kerosene was more representative with precise porosity of two-dimensional etched network channel model.

Hybrid connectionist model determines CO2–oil swelling factor

In-depth understanding of interactions between crude oil and CO2 provides insight into the CO2-based enhanced oil recovery (EOR) process design and simulation. When CO2 contacts crude oil, the dissolution process takes place. This phenomenon results in the oil swelling, which depends on the temperature, pressure, and composition of the oil. The residual oil saturation in a CO2-based EOR process is inversely proportional to the oil swelling factor. Hence, it is important to estimate this influential parameter with high precision. The current study suggests the predictive model based on the least-squares support vector machine (LS-SVM) to calculate the CO2–oil swelling factor. A genetic algorithm is used to optimize hyperparameters (γ and σ2) of the LS-SVM model. This model showed a high coefficient of determination (R2 = 0.9953) and a low value for the mean-squared error (MSE = 0.0003) based on the available experimental data while estimating the CO2–oil swelling factor. It was found that LS-SVM is a straightforward and accurate method to determine the CO2–oil swelling factor with negligible uncertainty. This method can be incorporated in commercial reservoir simulators to include the effect of the CO2–oil swelling factor when adequate experimental data are not available.