Enhanced Oil Recovery Processes Research Articles

Adsorption reduction of a gemini surfactant on carbonate rocks using formic acid: Static and dynamic conditions

Surfactant flooding improves oil recovery by lowering the interfacial tension and/or altering the reservoir rock’s wettability. However, surfactant losses caused by adsorption on the surface of the rock weaken the efficiency of this chemical enhanced oil recovery process. This study focuses on reducing the adsorption of a cationic gemini surfactant on carbonate rocks using formic acid. High-performance liquid chromatography integrated with an evaporative light scattering detector was employed to quantify both static and dynamic surfactant adsorptions. The results showed that the surfactant’s adsorption on carbonate rocks was reduced dramatically by adding 1% formic acid to the surfactant solution. Static adsorption was reduced from 2.44, 1.62, and 1.51 mg/g-rock to 0.16, 0.14, and 0.13 mg/g-rock on Guelph dolomite, Guff dolomite, and Indiana limestone, respectively. The dynamic adsorption of the surfactant on Indiana limestone was reduced from 0.269 to 0.041 mg/g-rock. It is believed that the carboxyl group released by the formic acid-rock reaction shields the surfactant from the rock surface resulting in lower adsorption. This is evidenced by the surfactant solution’s pH dropping below the point of zero charge of the rock, causing the repulsion of the cationic surfactant molecules off the surface. This study provides a low-cost option that provides a remarkable reduction in cationic surfactant adsorption on carbonate rocks.

Static adsorption of a novel cationic gemini surfactant: A mineralogical study

Surfactants are deemed as an advantageous chemical in enhanced oil recovery (EOR) because of their potential of lowering the interfacial tension and modifying the wettability. However, the surfactant loss by adsorption on the rock surface is one of the major shortcomings of surfactant-based flooding techniques. The static adsorption of an in-house synthesized cationic gemini surfactant (GS12) is investigated as a function of mineral type, salinity, and concentration. Both clay and non-clay minerals have been examined. Surfactant adsorption was increased continuously by the increase of concentration till 1000 ppm and then an adsorption plateau was observed in all minerals except montmorillonite and kaolinite. It was found that clay minerals may cause more detrimental effects as compared to silicate minerals and carbonate minerals showed the least adsorption. The maximum amount of surfactant adsorbed on the mineral surface was in the order of montmorillonite > kaolinite > illite > K-feldspar > quartz > dolomite > calcite. Lower adsorption of GS12 was detected because of the presence of multivalent ions (Ca2+ and Mg2+). Methylene blue (MB) has been revealed as a novel adsorption inhibitor for cationic GS12 on various minerals. MB adsorbs on the negative binding sites of both clay and non-clay minerals. Therefore, an electrostatic repulsion takes place between the cationic dye (MB) and cationic GS12, leading to the reduction of GS12 adsorption on the mineral surface. Only the addition of 100 ppm of MB in the surfactant solution at the highest concentration (1500 ppm) reduced GS12 adsorption on quartz surface to 0.67 mg/g-rock. This study will help in designing the chemical EOR process using GS12 on carbonate formation containing silica and clay minerals as impurities.

Functionalized silica nanoparticles within a multicomponent oil emulsion by molecular dynamic study

Molecular dynamics simulations were employed to study hydroxylated and functionalized SiO2 nanoparticles (NPs) within a light crude oil under different temperatures. The model oil comprised a combination of aromatics, alkanes, and cycloalkanes, while the hydroxylation, PEGlyation, and sulfonation of the NPs were evaluated. The effects of functional size were considered for PEGlyated NPs. Interestingly, benzene clusters dispersed in the oil phase were formed for all systems studied; clusters of 9 and 11 molecules were the most common. The benzene clusters adsorbed onto the NPs, forming a surrounding shell approximately 10 Å in width. The agglomeration of aromatic molecules was more evident for hydroxylation covering: the density of benzene molecules in the first shell of aromatic molecules surrounding the NPs decreased in the order NP-H, NP-SA, NP-EG, and NP-PEG2 and reached a maximum for hydroxylated NPs, where the hydrocarbons form a first shell of molecules ∼25 Å in width. The density of benzenes is 24% greater than in pristine oil. Compared to other coverings, this effect reduces the NP–oil interfacial tension for the hydroxylated NPs by about 15%. Our results indicated that the adsorption of benzene on NPs and the NPs–oil interfacial tension could be tuned by the NP covering. This degree of control is highly desirable for applications of NPs in enhanced oil recovery processes.

Gas channeling control with an in-situ smart surfactant gel during water-alternating-CO2 enhanced oil recovery

Undesirable gas channeling always occurs along the high-permeability layers in heterogeneous oil reservoirs during water-alternating-CO2 (WAG) flooding, and conventional polymer gels used for blocking the “channeling” paths usually suffer from either low injectivity or poor gelation control. Herein, we for the first time developed an in-situ high-pressure CO2-triggered gel system based on a smart surfactant, N-erucamidopropyl-N,N-dimethylamine (UC22AMPM), which was introduced into the aqueous slugs to control gas channeling in WAG processes. The water-like, low-viscosity UC22AMPM brine solution can be thickened by high-pressure CO2 owing to the formation of wormlike micelles (WLMs), as well as their growth and shear-induced structure buildup under shear flow. The thickening power can be further potentiated by the generation of denser WLMs resulting from either surfactant concentration augmentation or a certain range of heating, and can be impaired via pressurization above the critical pressure of CO2 because of its soaring solvent power. Core flooding tests using heterogeneous cores demonstrated that gas channeling was alleviated by plugging of high-capacity channels due to the in-situ gelation of UC22AMPM slugs upon their reaction with the pre- or post-injected CO2 slugs under shear flow, thereupon driving chase fluids into unrecovered low-permeability areas and producing an 8.0% higher oil recovery factor than the conventional WAG mode. This smart surfactant enabled high injectivity and satisfactory gelation control, attributable to low initial viscosity and the combined properties of one component and CO2-triggered gelation, respectively. This work could provide a guide towards designing gels for reducing CO2 spillover and reinforcing the CO2 sequestration effect during CO2 enhanced oil recovery processes.

Performance assessment of a novel bio-based polymer for enhanced oil recovery in high salinity sandstone reservoirs

Polymer flooding is arguably the oldest chemical oil recovery method. The use of natural polymers in enhanced oil recovery process has gained wide acceptance due to their excellent viscosity, high resistance to challenging reservoir conditions ranging from increased salinities, temperatures and divalent cations. In recent times, research into the efficiency of green natural polymers is gaining attention as an eco-friendly, readily available and cost-effective option. In this study, the displacement efficiency of Abelmoschus esculentus as a natural polymer in recovering heavy crude from sandstone reservoirs was examined and a simulation model was built to replicate the laboratory model. Abelmoschus esculentus was cleaned, sun-dried, and grinded into powder form and enclosed in an airtight bag. The various phases were analyzed to ascertain the fluid-fluid compatibility and consistency. Polymer rheological studies was conducted at varied temperatures. Core flooding at optimum polymer concentration was considered in an oil-wet sandstone core under reservoir conditions. Results showed that the solubility of the fluids is a function of temperature. Furthermore, polymer viscosity showed a direct relationship to the polymer concentration and temperature. Polymer flooding resulted in additional recovery of 16.26 % oil initially in place (OIIP), thus affirming the efficiency of this natural polymer in recovering heavy oil. However, a viscosity enhancer is required for improved performance. The simulation model was built, and the recovery factors of both models was successfully matched.

Well Placement Optimization through the Triple-Completion Gas and Downhole Water Sink-Assisted Gravity Drainage (TC-GDWS-AGD) EOR Process

Gas and downhole water sink-assisted gravity drainage (GDWS-AGD) is a new process of enhanced oil recovery (EOR) in oil reservoirs underlain by large bottom aquifers. The process is capital intensive as it requires the construction of dual-completed wells for oil production and water drainage and additional multiple vertical gas-injection wells. The costs could be substantially reduced by eliminating the gas-injection wells and using triple-completed multi-functional wells. These wells are dubbed triple-completion-GDWS-AGD (TC-GDWS-AGD). In this work, we design and optimize the TC-GDWS-AGD oil recovery process in a fictitious oil reservoir (Punq-S3) that emulates a real North Sea oil field. The design aims at maximum oil recovery using a minimum number of triple-completed wells with a gas-injection completion in the vertical section of the well, and two horizontal well sections—the upper section for producing oil (from above the oil/water contact) and the lower section for draining water below the oil/water contact. The three well completions are isolated with hydraulic packers and water is drained from below the oil–water contact using the electric submersible pump. Well placement is optimized using the particle swarm optimization (PSO) technique by considering only 1 or 2 TC-GDWS-AGD wells to maximize a 12-year oil recovery with a minimum volume of produced water. The best well placement was found by considering hundreds of possible well locations throughout the reservoir for the single-well and two-well scenarios. The results show 58% oil recovery and 0.28 water cut for the single-well scenario and 63.5% oil recovery and 0.45 water cut for the two-well scenario. Interestingly, the base-case scenario using two wells without the TC-GDWS-AGD process would give the smallest oil recovery of 55.5% and the largest 70% water cut. The study indicates that the TC-GDWS-AGD process could be more productive by reducing the number of wells and increasing recovery with less water production.

A Perspective Review on the Current Status and Development of Polymer Flooding in Enhanced Oil Recovery Using Polymeric Nanofluids

The globally increasing demand for crude oil has prompted the oil industry to enhance oil production from primary, secondary, and tertiary recovery methods to fulfill the global requirement. Therefore, enhanced oil recovery (EOR) is expected to increase its importance in the coming years. Because of limited efficiency, applicability, and higher gas and thermal injection costs, chemical EOR processes have been considered as an alternative in some special cases. Chemical EOR processes are accepted widely because of their higher efficiency, economic and technical feasibility, and optimum capital cost. Therefore, research of novel chemical compounds is immense in the oil industry. Research of nanotechnology in the petroleum industry has attracted attention among all novel chemical compounds in the past few years. This work focuses on the review of previous research regarding the current scenario of polymer flooding, challenges of polymer flooding, polymeric nanofluid in EOR, recent developments in polymer flooding, characteristics of polymeric nanofluids, prospects, and economic feasibility for polymeric nanofluids’ applications in EOR. This paper also reviews the characterization of polymeric nanofluids such as rheology, stability, wettability alteration, interfacial tension reduction, and absorption control. It has been found from a literature review that polymeric nanofluids are more effective in oil recovery considering viscosity modification, stability enhancement, and chemical adsorption control. Oil recovery can be additionally increased by up to 10–15% original-oil-in-place applying polymeric nanofluids.

Experimental study of viscous fingering in sand-pack model for heavy oil reservoir

Viscous fingering phenomenon in porous media has a great impact on industrial processes, such as enhanced oil recovery processes. The previous experimental works mainly used Hele-Shaw models and micromodels to investigate viscous fingering mechanisms. However, Hele-Shaw models simulate porous media flow in a narrow gap with no pore structure. Micromodels’ pore structures are simplified, and the material used to make micromodel generally has different wettability compared with real rocks. Therefore, a large-dimensions of 40 cm × 20 cm× 0.5 cm sand-pack model with a vertical well in the center is used in this study to mimic real reservoir in terms of pore structure, wettability conditions and real radial flow. To the best of our knowledge, there is no reported literature on viscous fingering experimental study for radial flow in real sand-pack models. Immiscible flooding processes with high viscosity ratios ranging from 853.9 to 32080 and different injection rates ranging from 0.01 to 0.5 ml·min−1 were conducted. The viscous fingering phenomena were captured and analyzed qualitatively and quantitatively. As capillary number increases, more unstable interfaces and complicated finger structures were visually observed and validated through fractal dimension analysis. These experimental results are in well agreement with previously reported results obtained from Hele-Shaw models and micromodels. The dimensionless number (Ca*µr2) analysis suggests viscosity has a greater effect on viscous fingering compared with injection rate, which was consistent with the conclusion of micromodel studies. Besides critical injection rate (0.01–0.05 ml∙min−1), increasing the viscosity ratio to a critical viscosity ratio (2946) leads to a significant decrease of breakthrough time, which was not reported in the literature. And different from linear displacement in which the viscous fingering followings two stages, additional pseudo-stable displacement could be generated after the rapid finger generation stage and combination stage for the radial displacement.

Feasibility of implementation of solar thermal energy in steam-assisted gravity drainage (SAGD) in extra-heavy oil field in Colombia

The feasibility of implementing solar thermal energy in enhanced oil recovery (EOR) projects in Colombia has been practically avoided mainly owing to its high operating cost. However, Solar thermal energy can enable generating steam to be used for the EOR process with SAGD. Based on the amount of steam needed for an extra-heavy oil project, a solar thermal parabolic trough heat plant of 76.6 MWt for field application was designed to produce up to 261 MMBTU/h from computer simulated studies. This plant can generate injection steam during day hours and can be complemented with a steam conventional generation system for operating during night hours and on highly cloudy days. The obtained results showed the generated solar steam can contribute an average of 37.5% total daily steam requirement. By applying System Advisor Model (SAM), the produced solar steam can generate a saving of US$ 27602/day, which is signification saving of US$ 10.07 MM in one year. Therefore, the solar thermal parabolic trough heat technology can be a suitable option to implement in the Colombian Eastern Llanos Basin for thermal EOR.

IMPROVING THE PERFORMANCE OF ZNO NANOPARTICLES FOR EOR IN HIGH-TEMPERATURE AND HIGH SALINITY CARBONATE RESERVOIRS

The main challenge of the application of nanofluids for enhanced oil recovery (EOR) in carbonate reservoirs is to maintain colloidal stability under reservoir conditions with high salinity and high temperature. In this study, we address this issue by increasing the stability and hydrophilicity of ZnO nanoparticles by adding TTIP. Adding TTIP on the surface of ZnO nanoparticles results in an increase in the hydrophilic heads in the final product. Then, these nanoparticles are used to coat carbonate rock surfaces to change their wettability. The coated rock plates are obtained by aging them in nanofluids. The modified ZnO-based coatings show to be more effective for wettability alteration purposes compared to the conventional ZnO coating. The un-coated rock plate is strongly oil-wet, where the water and n-heptane droplets contact angles on this surface are 168° and 0°, respectively. After aging the rock samples in nanofluids, superhydrophilic coatings form on the superhydrophobic surfaces. The rock surface before and after treatment, as well as the synthesized nanoparticles, are characterized by scanning electron microscope (SEM), x-ray diffraction (XRD), and Fourier-transform infrared spectroscopy (FTIR) analyses. Results of this study indicate the possibility of using the materials for wettability alteration of oil-wet carbonate rock in the EOR process. The results of core flooding tests demonstrate that the oil recovery enhances significantly through the nanofluid flooding.

EXPERIMENTAL INVESTIGATION OF TWO-PHASE PRESSURE DROP IN THE STRAIGHT ADIABATIC TUBES

The pressure drop is the significant constraint in designing the single or multiphase flow systems. Innovative technologies, such as nuclear power plants and enhanced oil recovery processes, can be designed more efficiently with the knowledge of the multiphase pressure drop phenomenon. The higher pressure drop induces the lower system efficiency. There is a scarcity of literature representing the steam-water flow at atmospheric system pressure in the adiabatic tubes. The experiments are performed to get the two-phase pressure drop in the adiabatic tube for the effective design of heat transfer equipment used for diverse applications. The adiabatic tubes of 8, 13.7, and 18 mm diameter, having 15 × 10<sup>2</sup> mm length, are experimented for 32-495 kg/m<sup>2</sup>s mass flux and 0-1 vapor quality. The pressure drop in the adiabatic tubes increases nonlinearly with the increase of vapor quality. The pressure drop is influenced significantly by the diameter of the tube. The pressure drop is lesser in the 18 mm tube compared to the 8 and 13.7 mm tubes for constant vapor quality and mass flow rate. The increase of the mass flux increases the pressure drop monotonically. The pressure drop is higher at higher mass flux and higher vapor quality in the lesser diameter tube. The experimental pressure drop is compared to various correlations. A correlation is suggested to measure the two-phase pressure drop during steam-water flow at atmospheric system pressure in the adiabatic tubes.

A review on EOR methods to improve heavy oil recovery

Any well's oil production goes through three stages. Under well pressure, oil is naturally extracted in the first stage; the second stage begins when the well pressure drops. In the second stage, sea or brackish water is pumped into the well, forcing oil upward. Twenty to thirty percent of the well reserve is removed after the well's primary and secondary oil production stages. More than 70 percent of the oil is still present in the well, despite claims to the contrary. The third stage, often known as enhanced oil recovery or tertiary recovery, begins at this point. It is predicted that just one-third of the available oil is produced globally. Therefore, as demand rises and there is a supply shortfall, we should be able to produce more oil by adopting EOR processes. This paper presents a brief review of Enhanced Oil Recovery (EOR) processes. It is anticipated that EOR technologies will be essential in supplying the world's energy needs in the years to come given the drop in oil finds over the past few decade.

THE STUDY OF THE EFFECT OF TEMPERATURE AND PH VALUE ON ADSORPTION CHARACTERISTICS OF UREA BASED SACRIFICIAL AGENT IN CLAY MINERALS

The Enhanced Oil Recovery (EOR) process has grown within the time oil exploration was conducted, and many recovery methods were invented to maximize production. One of the promising recovery techniques is carbon dioxide (CO2) flooding. However, CO2 flooding has its disadvantages where due to different mobility and heterogeneity between CO2 and reservoir, the sweep efficiency is reduced because of gas channelling and viscous fingering. Thus, the application of surfactant is introduced to solve the problem. But, by using surfactants in CO2 flooding, loss of surfactant to the formation is observed. Due to this setback, the cost of the EOR process increased significantly as more surfactants must be injected due to the loss. To reduce surfactant loss, sacrificial agents are introduced within the application of surfactant in CO2 flooding. The sacrificial agent would be adsorbed onto the clay minerals instead of surfactants. However, the application of sacrificial agent needs to be optimized to ensure a more cost-effective process. Therefore, this study, the adsorption rate of urea-based sacrificial agent in montmorillonite and kaolinite was tested under different pH values and temperatures using a UV-Vis spectrometer. Through the adsorption test, it is observed that the adsorption rate of urea is higher in montmorillonite than in kaolinite. The adsorption rate of urea in montmorillonite and kaolinite are optimized in high-temperature alkaline environment with 1.50 mg/g and 1.46 mg/g of urea adsorbed, respectively.Keywords: CO2 flooding, montmorillonite, kaolinite, sacrificial agent, urea, adsorption rate

Bayesian averaging sensitivity analysis of reservoir heterogeneity and anisotropy of carbon dioxide assisted gravity drainage of a large clastic oil reservoir

Identifying the specific reservoir properties that influence oil production is an essential part of field development planning. Distinguishing the relative influence of variables and eliminating those that have no influence assists the design of enhanced oil recovery processes. The conventional approach to identify the most influential variables is the multiple linear regression (MLR) step-wise elimination. Bayesian averaging (BA), a stochastic method, offers a novel alternative approach by generating fifty models compared to each other to select the best one with of the most influential parameters based on the highest R2 and posterior probability with the lowest value of Bayesian information criterion (BIC). BA and MLR step-wise elimination are compared in the evaluation of a simulated immiscible carbon dioxide-assisted gravity drainage (CO2-AGD) system applied to the multi-layered, heterogeneous, upper sandstone oil reservoir of the South Rumaila field. A history-matched compositional simulation covering the nearly 57 years of prior production is used for sensitivity analysis of reservoir variables in relation to CO2-AGD implementation over 10 future years with 22 additional CO2 injection wells and 11 new production wells. Oil is displaced downwards towards the new horizontal production wells installed above the oil water contact. The influential variables evaluated are permeability (K), permeability anisotropy (Kv/Kh) and porosity (ɸ) considered separately across multiple heterogeneous reservoir layers. BA and step-wise elimination methods identify K as the most influential variable in all reservoir layers. Kv/Kh is moderately influential in the production layers and underlying water zone but not in injection or transition reservoir layers. ɸ in all reservoir layers has no influence on oil recovery from the CO2-AGD producing wells. More specifically, the BA-based influential parameters were determined after selecting the best model among the fifty generated models. The best model achieved that highest values of R2 of 0.848 and posterior probability of 0.234, and the lowest value of BIC of −149 with 12 identified influential geological parameters across the reservoir layers. Based on validation tests, varying K, Kv/Kh. and ɸ substantially across all reservoir layers confirms these findings and agrees more closely with the BA-derived reduced variable models than those generated by MLR step-wise elimination.

Experimental Evaluation of Zwitterionic and Cationic Surfactants to Optimize Bulk Foam Properties for Gas Mobility Control in High-Salinity Carbonates

Foam injection has been acknowledged as a promising technology to control gas mobility by establishing the flow resistance during gas enhanced oil recovery (EOR) processes. For applications in challenging carbonate formations, the development of well-matched foaming agents is required. In this paper, the foam performance established by different switchable and zwitterionic surfactants along with their combinations in controlling gas mobility and displacing the residual oil is investigated. The stable solutions of commercial amine-based and/or zwitterionic surfactants were prepared in 20 wt % salinity. A series of foamability and foam stability tests were conducted as initial screening at high temperatures in the presence and absence of crude oil. Foam texture and foam stability were also investigated at different gas/liquid fractions under high-temperature and high-pressure conditions. The best-performing formulation at optimum foam quality was evaluated in coreflooding experiments in terms of mobility reduction factor (MRF) and residual oil recovery. Bulk foam results demonstrated the superior foamability and foam stability of a betaine (B1235) surfactant. Foam endurance of B1235 was found comparable to the diamine (DTTM) produced foam; however, the DTTM surfactant showed insignificant foamability. Among all tested surfactants and their mixtures, B1235 was found most effective in maintaining foam properties in a crude oil environment, and no synergistic effect was observed in the use of surfactant mixtures. The optimum concentrations for B1235 with and without crude oil were 0.25 and 0.5 wt %, respectively. The results obtained from the experiments in a pressurized view cell indicated a prolonged decay profile at 90% gas fraction in bulk. During dynamic flow in carbonate rocks, the optimum quality of foam stabilized by the selected surfactant was found at 70%. At this quality, the pregenerated foam injection pronouncedly increased the MRF to 48. The cumulative oil recovery after foam injection was 67%, providing 25% incremental recovery. The overall performance of the betaine-based surfactant-stabilized foam in high-salinity carbonates was found effective in controlling the gas mobility during the foam EOR process.

Effect of Rheological Properties of Polymer Solution on Polymer Flooding Characteristics.

Polymer flooding is an appropriate enhanced oil recovery (EOR) process that can increase macroscopic sweep efficiency. We examined two polymeric superpushers at different salinities (10,000 and 42,000 ppm of NaCl and 18,000 ppm of CaCl2) and temperatures (30 to 75 °C) as polymer-flooding agents for the EOR process. Rheological and thixotropic tests were attempted to find shear viscosity change when the polymer solutions were introduced under different salinity and temperatures, followed by describing the rheological behavior with the two most common rheological models used for polymer solutions, and then a quadratic model with Design-Expert to detect the effective parameters. Core flooding tests were conducted afterward to determine the final proposed fluid. An increase in the concentration of monovalent ions and the addition of divalent ions adversely affected both types of polymers used, which was similar to the effects of a temperature increase. The Flopaam 3630S at 1000 ppm has more stability under harsh conditions and enables 22% and 38% oil recovery in carbonate and sandstone core rocks, respectively. Consequently, Flopaam 3630S can be the perfect polymer agent for different chemical flooding procedures in high-salinity oil reservoirs.

Use of AI tools to understand and model surface-interaction based EOR processes

Enhanced Oil Recovery (EOR) is as a key tertiary recovery strategy that aims at enhancing the oil recovery from the earth's subsurface of existing oilfields. One such EOR process that is dependent on multiple variables of complex surface interactions between the formation brine, injected brine, hydrocarbon and rock surface is different composition water flood. This specific EOR technique has been gaining wide focus in research due to its ease of implementation both in terms of logistic and cost albeit the complex interactions that leads to its success is still not clear. Due to the variables of the different phases playing a prominent role in the outcome of this EOR technique, the resulting complexity necessitates the need for Artificial Intelligence (AI) tools to be able to understand, model and screen this EOR technique. There are numerous AI tools based on supervised, unsupervised and reinforcement strategies that can be used in understanding the prominence of different parameters of this surface-interaction based EOR process. In this research work several data analysis methods followed by use of machine learning methods (a subset of AI) are used to analyse the different parameters and their impact on the outcome of the EOR process. Based on these AI tools the prominent parameters are discerned and their correlation with respect to the success of the EOR process is determined. This is followed by evaluation of the AI tools for screening of the EOR process prior to making investment decisions involving commitment to huge capital, resources, and time. This research determines that the key parameters of brine composition, salinity at initial and final conditions, oil API and initial recovery achieved which is a function of the wettability are key for the success of this EOR process. Through this work findings, the industry has a valuable tool to make early decisions that ensure greater probability of success of screening and selecting this EOR technology before commitment of resources for detailed design and implementation.

Experimental study on the rise of aqueous foams in vertical pipes

In this paper we report experiments on the growth of dry foams and their rise in vertical pipes of different circular cross-sectional radii with length over diameter ratios in the interval 25 ≤ h/D ≤ 80 for applications in the study of fracture stimulation in enhanced oil recovery processes. Air injection at the bottom of the pipes is performed at a constant flow rate by means of a single capillary tube. The formation and rising of the foam was investigated for two different cases: 1) when the top cap of the vertical pipes is open and 2) when it is closed. We find that the position and velocity of the foam front as well as the foam dispersivity are both dependent on the pipe diameter and on whether its top end is open or capped. When the top is open, the foam column grows faster compared to the case when it is sealed. In pipes with h/D ≥ 30, the growth rate is non-linear and faster than in pipes with h/D < 30 in which cases the foam rises at an almost constant rate. As the diameter of the pipe increases, the size of the produced bubbles also increases. In closed-top pipes the foams tend to be more homogeneous than in open top pipes. The experimental observations indicate that under foam drainage driven by gravity, the liquid flow velocity across the Plateau borders is indicative of a drainage model based on a plug-like flow in channels with fully mobile interfaces, where viscous dissipation occurs only in the nodes.

An assessment of ensemble learning approaches and single-based machine learning algorithms for the characterization of undersaturated oil viscosity

BackgroundPrediction of accurate crude oil viscosity when pressure volume temperature (PVT) experimental results are not readily available has been a major challenge to the petroleum industry. This is due to the substantial impact an inaccurate prediction will have on production planning, reservoir management, enhanced oil recovery processes and choice of design facilities such as tubing, pipeline and pump sizes. In a bid to attain improved accuracy in predictions, recent research has focused on applying various machine learning algorithms and intelligent mechanisms. In this work, an extensive comparative analysis between single-based machine learning techniques such as artificial neural network, support vector machine, decision tree and linear regression, and ensemble learning techniques such as bagging, boosting and voting was performed. The prediction performance of the models was assessed by using five evaluation measures, namely mean absolute error, relative squared error, mean squared error, root mean squared error and root mean squared log error.ResultsThe ensemble methods offered generally higher prediction accuracies than single-based machine learning techniques. In addition, weak single-based learners of the dataset used in this study (for example, SVM) were transformed into strong ensemble learners with better prediction performance when used as based learners in the ensemble method, while other strong single-based learners were discovered to have had significantly improved prediction performance.ConclusionThe ensemble methods have great prospects of enhancing the overall predictive accuracy of single-based learners in the domain of reservoir fluid PVT properties (such as undersaturated oil viscosity) prediction.

Non-Darcian Displacement of Oil by a Micellar Solution in Fractal Porous Media

A Buckley–Leverett analysis with capillary pressure to model the oil displacement in fractal porous media is herein presented. The effective permeability for a non-Newtonian micellar fluid is calculated by a constitutive equation used to describe the rheological properties of a displacement fluid. The main assumption of this model involves a bundle of tortuous capillaries with a size distribution and tortuosity that follow fractal laws. The BMP model predicts two asymptotic (Newtonian) regions at low and high shear and a power-law region between the two Newtonian regions corresponding to a stress plateau. Both the stress at the wall and the fluidity are calculated using an imposed pressure gradient in order to determine the mobility of the solution. We analyze different mobility ratios to describe the behavior of the so-called self-destructive surfactants. Initially, the viscosity of the displacing fluid (micellar solution) is high; however, interactions with the porous media lead to a breakage process and degradation of the surfactant, producing low viscosity. This process is simulated by varying the applied pressure gradient. The resulting equation is of the reaction–diffusion type with various time scales; a shock profile develops in the convective time scale, as in the traditional Buckley-Leverett analysis, while at longer times diffusion effects begin to affect the profile. Predictions include shock profiles and compressive waves. These results may find application when selecting surfactants for enhanced oil recovery processes in oilfields.