Hybrid EOR Methods Utilizing Low-Salinity Water

Low-salinity water (LSW) flooding has been applied in sandstone and carbonate formations to improve oil recovery. Wettability alteration by LSW has been identified as the dominant driving mechanism for the incremental oil recoveries. LSW flooding has been combined with other EOR methods to develop new hybrid approaches to improve crude/brine/rock (CBR) interactions with the objective of overcoming some of the LSW flooding downsides, which include oil trapping and fine migration. Hybrid methods can provide higher oil recovery than each stand-alone technique. For instance, changes in gas solubility during LSW injection positively affect the performance of LSW/gas hybrid injection. LSW/surfactant flooding can contribute to incremental recovery by simultaneously lowering interfacial tension (IFT) and wettability alteration. The synergistic effect of fluid redistribution by LSW and enhanced water mobility by polymer flooding improves oil detachment and displacement in porous media through the application of the hybrid approach LSW/polymer flooding. Nanoparticles (NPs), mainly SiO2, can alter wettability toward more water wetness in combination with LSW, and hot LSW can improve heavy oil production by reducing viscosity. Hence, the synergistic effect of hybrid EOR methods based on LSW flooding is considered a novel EOR approach to improve oil recovery

Effect of Initial Wettability on Performance of Smart Water Flooding in Carbonate Reservoirs—An Experimental Investigation with IOR Implications

In this paper, the effects of salinity and active ions on wettability alteration in carbonate reservoirs with different initial wettability conditions with implications in smart water flood design, optimization, and performance analysis are experimentally investigated. Contact angle measurement was used as the main tool to study the alteration in wettability. Other analytical techniques such as pH measurements along with energy-dispersive X-ray spectroscopy (EDS) were used to support the analysis. Initial wettability of the tested carbonate samples ranges from strongly water wet to preferentially water wet, neutral wet, oil wet, and strongly oil wet (5 cases or groups) condition. Four different synthetic brines, namely high salinity (Hsal), low salinity (Lsal), and smart waters 1 and 2 (SW1 = a Mg brine, and SW2 = a Mg and sulfate brine) were prepared and used by adjusting the salinity and ion concentration to study their effects on wettability alteration. Low-salinity brine (Lsal) proved to be more effective than high-salinity brine (Hsal) for the wettability alteration of calcite surfaces at intermediate (neutral) or oil-wet conditions. The smart brine containing only the Mg2+ ion (SW1) was able to alter the wettability of calcite surfaces in intermediate or oil-wet states. The sulfate ion played a catalytic role in wettability alteration by the magnesium ion, and the process was faster, as indicated by higher wettability alteration index values. High-salinity brine (Hsal) is a good choice for design of water floods in reservoir rocks with initial wettability in the range of strongly water wet to neutral wet conditions. In the wettability alteration process of oil-wet samples, brine with a high magnesium ion concentration was slower than brine containing high concentrations of both magnesium and sulfate ions. This can be attributed to the catalytic role of the sulfate ion compared to that of the magnesium ion. Finally, the results showed that the initial wettability of the reservoir rock plays a major role in design of a proper water flood to maximize oil recovery from carbonate reservoirs. The results obtained from this research work suggests that some effective smart water flooding scenarios can be developed and executed incorporating different smart brines to manage the reservoir rock wettability and maximize the oil recovery from carbonate oil reservoirs

INVESTIGATION OF BRINE PH EFFECT ON THE RHEOLOGICAL AND VISCOELASTIC PROPERTIES OF HPAM POLYMER FOR AN OPTIMIZED ENHANCED OIL RECOVERY DESIGN

A novel approach to improve viscous and viscoelastic properties by exploiting the pH and salinity sensitivity of HPAM polymer is proposed in this paper. Polymer flooding is a welldeveloped and effective enhanced oil recovery technique. The design of the makeup brine is one of the most critical phases of a polymer flood project, since the brine composition, salinity, and pH directly influence the polymer viscosity and viscoelasticity. However, the viscoelastic properties of hydrolyzed polyacrylamide polymers have not been given much consideration during the design phase of polymer flood projects. Our experimental study focuses on the optimization of the makeup water design for polymer flooding by evaluating the optimum solution salinity and pH for better stability and improved viscoelastic behavior of the polymer. Initially, the brine salinity and ionic composition is adjusted and then hydrolyzed polyacrylamide (HPAM) polymer solutions of varying pH are prepared using the adjusted brine. Rheological experiments are conducted over a temperature range of 25−80 °C and at different aging times. Polymer thermal degradation as a function of pH is assessed by examining the solutions at 80 °C for 1 week. Amplitude sweep and frequency sweep tests are performed to determine the viscoelastic properties such as storage modulus, loss modulus, and relaxation time. A 15−40% increase in the polymer solution viscosity and a 20 times increase in relaxation time is observed in the pH range of 8−10 in comparison to the neutral solution. This can be attributed to the low-salinity ion-adjusted environment of the makeup brine and further hydrolysis and increased repulsion of polymer chains in an alkaline environment. These results indicate that the viscoelastic properties of a polymer are tunable and a basic pH is favorable for better synergy between the brine and the polymer. Alkaline low-salinity polymer solutions have exhibited 60% higher thermal stability in comparison to acidic solutions and thus can be successfully applied in high-temperature reservoirs. The results of this study show that polymer solutions with an optimum pH in the basic range exhibit a higher viscoelastic character and an increased resistance toward thermal degradation. Hence, the polymer solution salinity, ionic composition, and pH should be adjusted to obtain maximum oil recovery by the polymer flooding method. Finally, this study shows that more effective polymer solutions can be prepared by adjusting the pH and designing a low-salinity water/polymer recipe to get the additional benefit of polymer viscoelasticity. The optimized low-salinity alkaline conditions can reduce the residual oil saturation by stronger viscous and viscoelastic forces developed by more viscous polymers. The findings of this study can be employed to design an optimum polymer recipe by tuning the brine pH and salinity for maximum incremental oil recovery, particularly in high-temperature and high-salinity formations

The effect of cations on gelation of cross-linked polymers

The effects of different cation concentrations and types on rheological property and stability of Guar, Xanthan, and Partially Hydrolyzed Polyacrylamide (HPAM) cross-linked gels were analyzed through experiments. Also, a new approach was developed to reduce the negative effects of cation by application of multi-walled carbon nano-tubes (MWCNTs). The presence of cations in cross-linked gel system will reduce the viscosity of gel, the higher the cation concentration is, the lower the viscosity will be. The bivalent cation has a greater viscosity reduction effect on gel than monovalent cation. The stability of cross-linked gels is worse with cations, this situation becomes more serious under higher salinity. MWCNTs were added to HPAM gel, cross-linked by (3-Aminopropyl) triethoxysilane (APTES), they surrounded cations and removed them from polymers and reduced the reaction possibility. This method enhances the viscosity and breakdown pressure of cross-linked gels, improves the stability of HPAM cross-linked gel under different operating conditions, and can be applied to related drilling projects

SPONTANEOUS IMBIBITION OIL RECOVERY BY NATURAL SURFACTANT/NANOFLUID: AN EXPERIMENTAL AND THEORETICAL STUDY

Organic surfactants have been utilized with different nanoparticles in enhanced oil recovery (EOR) operations due to the synergic mechanisms of nanofluid stabilization, wettability alteration, and oil-water interfacial tension reduction. However, investment and environmental issues are the main concerns to make the operation more practical. The present study introduces a natural and cost-effective surfactant named Azarboo for modifying the surface traits of silica nanoparticles for more efficient EOR. Surface-modified nanoparticles were synthesized by conjugating negatively charged Azarboo surfactant on positively charged amino-treated silica nanoparticles. The effect of the hybrid application of the natural surfactant and amine-modified silica nanoparticles was investigated by analysis of wettability alteration. Amine-surfactant-functionalized silica nanoparticles were found to be more effective than typical nanoparticles. Amott cell experiments showed maximum imbibition oil recovery after nine days of treatment with amine-surfactant-modified nanoparticles and fifteen days of treatment with amine-modified nanoparticles. This finding confirmed the superior potential of amine-surfactant-modified silica nanoparticles compared to amine-modified silica nanoparticles. Modeling showed that amine surfactant-treated SiO2 could change wettability from strongly oil-wet to almost strongly water-wet. In the case of amine-treated silica nanoparticles, a strongly water-wet condition was not achieved. Oil displacement experiments confirmed the better performance of aminesurfactant- treated SiO2 nanoparticles compared to amine-treated SiO2 by improving oil recovery by 15%. Overall, a synergistic effect between Azarboo surfactant and amine-modified silica nanoparticles led to wettability alteration and higher oil recovery

Continuous Gas Lift Optimization Using Genetic Algorithm

Abstract: Gas lift is one of a number of processes used to artificially lift oil or water from wells where there is insufficient reservoir pressures to produce the well. The process involves injecting gas through the tubing-casing annulus. Injected gas aerates the fluid to reduce its density; the formation pressure is then able to lift the oil column and forces the fluid out of the wellbore. Gas may be injected continuously or intermittently, depending on the producing characteristics of the well and the arrangement of the gas-lift equipment. Being somehow an ancient tool with an age of over a century, gas lift is though still a challenging problem when overall optimization is the concern. When the injection gas is of a limited supply the problem is finding the best gas allocation scheme. However there are increasingly emerging cases in certain geographic localities where the gas supplies are usually unlimited. The optimization problem then totally travels to the wellbore and completion string and fully engages with multiphase flow concepts. In the present study an intelligent genetic algorithm has been developed to simultaneously optimize all effective factors namely, gas injection rate, injection depth and tubing diameter towards the maximum oil production rate with the water cut and injection pressure as the restrictions. The computations and real field data are mutually compared

A systematic approach for modeling of waterflooding process in the presence of geological uncertainties in oil reservoirs

The final publication is available at Elsevier via http://dx.doi.org/10.1016/j.compchemeng.2017.12.012 © 2018. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/In this paper, a systematic approach which is able to consider different types of geological uncertainty is presented to model the waterflooding process. The proposed scheme, which is based on control and system theories, enables the experts to apply suitable techniques to optimize the production. By using the developed methodology, a reasonable mapping between defined system inputs and outputs in frequency domain and around a specific operating point is established. In addition, a nominal model for the process as well as a lumped representation for uncertainty effects are provided. Based on the proposed modeling mechanism, reservoir management goals can be pursued in the presence of uncertainty by utilization of complicated control and optimization strategies. The developed algorithm has been simulated on 10th SPE-model#2. Observed results have shown that the introduced methodology is able to effectively model the dynamics of waterflooding process, while taking into account the assumed induced geological uncertainty

Modelling of continuous surfactant flooding application for marginal oilfields: A case study of Bentiu reservoir

Enhanced oil recovery (EOR) is a proven method to increase oil production from the brown fields. One of the efficient EOR methods is injecting surfactants to release the trapped oil. However, few unconsolidated behaviours were observed in both field and laboratory practice. In this study, a new framework was adapted to evaluate the continuous surfactant flooding (CSF) in Bentiu reservoir. The study aims to quantify the expected range of the oil production, recovery factor and residual oil saturation (Sor). The motivation came from the oil demand in Sudan and the insufficient cores. The framework adopted in the study includes numerical simulation modelling and proxy modelling. Thirty-six cores obtained from the field were revised and grouped into five main groups. The interfacial tension (IFT) data were obtained experimentally. The CSF sensitivity study was developed by combining different experimental design sets to generate the proxy model. The CSF numerical simulation results showed around 30% additional oil recovery compared to waterflooding and approximately oil production between (20–30) cm3. The generated proxy model extrapolated the results with concerning lower ranges of the input and showed an average P50 of oil production and recovery of 74% and 17 cm3, respectively. Overall, the performance of CSF remained beneficial in vast range of input. Moreover, the generated proxy model gave an insight on the complexity of the interrelationship between the input factors and the observants with a qualitative prospective factors. Yet, the results confirmed the applicability of CSF in core scale with an insight for field scale application

A coupled wellbore/reservoir simulator to model multiphase flow and temperature distribution

Hydrocarbon reserves are generally produced through wells drilled into reservoir pay zones. During production, gas liberation from the oil phase occurs due to pressure decline in the wellbore. Thus, we expect multiphase flow in some sections of the wellbore. As a multi-phase/multi-component gas-oil mixture flows from the reservoir to the surface, pressure, temperature, composition, and liquid holdup distributions are interrelated. Modeling these multiphase flow parameters is important to design production strategies such as artificial lift procedures. A wellbore fluid flow model can also be used for pressure transient test analysis and interpretation. Considering heat exchange in the wellbore is important to compute fluid flow parameters accurately. Modeling multiphase fluid flow in the wellbore becomes more complicated due to heat transfer between the wellbore fluids and the surrounding formations. Due to mass, momentum, and energy exchange between the wellbore and the reservoir, the wellbore model should be coupled with a numerical reservoir model to simulate fluid flow accurately. This model should be non-isothermal to consider the effect of temperature. Our research shows that, in some cases, ignoring compositional effects may lead to errors in pressure profile prediction for the wellbore. Nearly all multiphase wellbore simulations are currently performed using the "black oil" approach. The primary objective of this study was to develop a non-isothermal wellbore simulator to model transient fluid flow and temperature and couple the model to a reservoir simulator called General Purpose Adaptive Simulator (GPAS). The coupled wellbore/reservoir simulator can be applied to steady state problems, such as production from, or injection to a reservoir as well as during transient phenomena such as well tests to accurately model wellbore effects. Fluid flow in the wellbore may be modeled either using the blackoil approach or the compositional approach, as required by the complexity of the fluids. The simulation results of the new model were compared with field data for pressure gradients and temperature distribution obtained from wireline conveyed pressure recorder and acoustic fluid level measurements for a gas/oil producer well during a buildup test. The model results are in good agreement with the field data. Our simulator gave us further insights into the wellbore dynamics that occur during transient problems such as phase segregation and counter-current multiphase flow. We show that neglecting these multiphase flow dynamics would lead to unreliable results in well testing analysis.Petroleum and Geosystems Engineerin