A comprehensive review on Enhanced Oil Recovery by Water Alternating Gas (WAG) injection

Afzali, Shokufe; Rezaei, Nima; Zendehboudi, Sohrab

doi:10.1016/j.fuel.2018.04.015

Cited by 218 publications

(112 citation statements)

References 91 publications

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“…Complexity of the WAG process is mainly related to the WAG physical process and WAG optimization. Afzali et al (2018) demonstrated that the complexity of the WAG physical process is mainly related to three-phase flow, inter-phase mass transfer, swelling, oil trapping, and water blocking by the injected gas that are not well understood by scientist and researchers.…”

Section: Introductionmentioning

confidence: 99%

Novel approach for predicting water alternating gas injection recovery factor

Belazreg

Mahmood

Aulia

2019

J Petrol Explor Prod Technol

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Water alternating gas (WAG) injection process is a proven EOR technology that has been successfully deployed in many fields around the globe. The performance of WAG process is measured by its incremental recovery factor over secondary recovery. The application of this technology remains limited due to the complexity of the WAG injection process which requires time-consuming in-depth technical studies. This research was performed for a purpose of developing a predictive model for WAG incremental recovery factor based on integrated approach that involves reservoir simulation and data mining. A thousand reservoir simulation models were developed to evaluate WAG injection performance over waterflooding. Reservoir model parameters assessed in this research study were horizontal and vertical permeabilities, fluids properties, WAG injection scheme, fluids mobility, trapped gas saturation, reservoir pressure, residual oil saturation to gas, and injected gas volume. The outcome of the WAG simulation models was fed to the two selected data mining techniques, regression and group method of data handling (GMDH), to build WAG incremental recovery factor predictive model. Input data to the machine learning technique were split into two sets: 70% for training the model and 30% for model validation. Predictive models that calculate WAG incremental recovery factor as a function of the input parameters were developed. The predictive models correlation coefficient of 0.766 and 0.853 and root mean square error of 3.571 and 2.893 were achieved from regression and GMDH methods, respectively. GMDH technique demonstrated its strength and ability in selecting effective predictors, optimizing network structure, and achieving more accurate predictive model. The achieved WAG incremental recovery factor predictive models are expected to help reservoir engineers perform quick evaluation of WAG performance and assess a WAG project risk prior launching detailed time-consuming and costly technical studies.

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Section: Introductionmentioning

confidence: 99%

Novel approach for predicting water alternating gas injection recovery factor

Belazreg

Mahmood

Aulia

2019

J Petrol Explor Prod Technol

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“…Employing foam in various industries such as pharmacy and cosmetics, medical, firefighting, and petroleum and gas industries is a common occurrence in today's world. Gas injection, in other words the injection of gasses such as carbon dioxide, nitrogen, air, and hydrocarbon to an oil reservoir, is one of the most popular techniques to enhance oil recovery . However, this recovery method suffers from poor volumetric efficiency due to phenomena such as channelling, viscous fingering, and gravity segregation, in some cases.…”

Section: Introductionmentioning

confidence: 99%

Monitoring the behaviour of anionic polymer‐anionic surfactant stabilized foam in the absence and presence of oil: Bulk and bubble‐scale experimental analyses

2019

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The present study aims at monitoring the bulk and bubble-scale behaviour of anionic polyacrylamide-sodium dodecyl sulphate stabilized foam in the absence and presence of oil. Dynamic stability tests provided results indicating that polymer increases the foam dynamic stability and decreases the drainage. Oil slows down the drainage rate of polymer-surfactant foam. In the absence of oil, foam is drained gradually/smoothly whereas remarkable fluctuations are evident in drainage graphs when oil is present. The Hele-Shaw cell was employed to conduct bubble-scale as well as statistical analyses on how foam texture is influenced by a polymer-surfactant system and hydrocarbon. Bubble-scale analyses, taken right after foam generation in the absence of oil, revealed that foam bubble sizes and their standard deviation increase by polymer concentration. The coefficient of variation of foam bubble sizes drops with polymer concentration in the absence/presence of oil, meaning the growth of foam texture uniformity. Oil increases the bubble size diversity in the foam texture. Disproportionation/Ostwald ripening is hindered by increasing the foam bubble distribution uniformity by adding polymer to the foaming solution. At polymer concentrations higher than 13 Â 10 À4 g/g, a polymersurfactant mixture generates foam in the presence of oil as stable as foam in the absence of oil, while at the polymer concentrations lower than 7 Â 10 À4 g/g, bubbles are highly unstable when oil is present. Results of this study help to gain a better understanding about the extent to which polymer could enhance the foam stability in bulk/bubble-scale, which might be applicable for enhanced oil recovery operations.

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“…Total oil recovery efficiency is then a result of a combination of displacement and volumetric efficiencies (Thakur and Satter, 1998). A WAG injection tends to combine high macroscopic sweep efficiency of the waterflooding operation with high displacement efficiency of the gas injection process to improve oil recovery (Kulkarni and Rao, 2005;Afzali et al, 2018).…”

Section: Introductionmentioning

confidence: 99%

“…Then, the combined use of water slugs along with gas injection can improve the overall sweeping efficiency. Afzali et al (2018) show that the flow rate in each region of the reservoir is proportional to the local flow capacity (i.e., the local conductivity). At high WAG ratios, gas tends to enter the highly permeable zones.…”

Section: Introductionmentioning

confidence: 99%

Numerical Assessment Of Water Alternating Gas Practices In The Presence Of Hysteresis Effects On Relative Permeability

Ranaee¹,

Inzoli²,

Riva³

et al. 2018

Proceedings

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Water Alternating Gas (WAG) injection is one of the most successful enhanced oil recovery approaches. Properly accounting for the hysteretic effects of relative permeabilities is a critical issue encountered in numerical simulations of WAG at the mesoscale. Ranaee et al. (2015) proposed a sigmoid-based model for three-phase oil relative permeability, incorporating key physical effects taking place at the pore scale. The model can then be jointly used with the Larsen and Skauge (1998) model, accounting for gas relative permeability hysteresis, to develop a formulation for three-phase relative permeability suitable for reservoir simulation. In this study we illustrate the impact of this joint formulation on a field scale setting through a suite of numerical simulations of WAG injection targeting a reservoir model inspired to real life cases. The analysis is performed by embedding the illustrated relative permeability models in the black oil model implemented in the Matlab Reservoir Simulation Toolbox (Lie et al., 2011). We assume non-hysteretic behavior for water relative permeability under water-wet conditions and characterize it upon relying on corresponding laboratory-scale data. As a baseline, the results are compared against a scenario in the absence of three-phase relative permeability hysteresis. The computational domain is heterogeneous, the spatial distributions of porosity and absolute permeability varying across the ranges of [0.02 -0.3] and [0.1 -2600 mD], respectively. The model is set at equilibrium conditions, production being driven by three peripheral injectors and five up-dip producers. A given flow rate is assigned to each injector and a target value of liquid production rate is imposed at the producing wells. The numerically evaluated production rates constitute our target state variables. The schedule of the injectors is set to achieve a preliminary waterflooding phase followed by a WAG injection scheme. The latter is implemented by periodically switching the injected phase between water and gas for two injectors, the third injector continuously injecting water. The numerical simulations are performed through a fully implicit discretization of the equations governing the system dynamics. To minimize computational costs, we employ an algebraic multi-grid method and resort to a multi-processor high performance clustered computer system. Our results suggest that hysteretic effects are important across significant portions of the studied reservoir system. Field production responses are associated with a simultaneous increase of ultimate oil recovery and a corresponding decline of the gas-oil ratio when hysteretic effects are included in the simulations.

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A comprehensive review on Enhanced Oil Recovery by Water Alternating Gas (WAG) injection

Cited by 218 publications

References 91 publications

Novel approach for predicting water alternating gas injection recovery factor

Novel approach for predicting water alternating gas injection recovery factor

Monitoring the behaviour of anionic polymer‐anionic surfactant stabilized foam in the absence and presence of oil: Bulk and bubble‐scale experimental analyses

Numerical Assessment Of Water Alternating Gas Practices In The Presence Of Hysteresis Effects On Relative Permeability

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