Predicting the incremental recovery factor with an enhanced oil recovery (EOR) technique is a very crucial task. It requires a significant investment and expert knowledge to evaluate the EOR incremental recovery factor, design a pilot, and upscale pilot result. Water-alternating-gas (WAG) injection is one of the proven EOR technologies, with an incremental recovery factor typically ranging from 5 to 10%. The current approach of evaluating the WAG process, using reservoir modeling, is a very time-consuming and costly task. The objective of this research is to develop a fast and cost-effective mathematical model for evaluating hydrocarbon-immiscible WAG (HC-IWAG) incremental recovery factor for medium-to-light oil in undersaturated reservoirs, designing WAG pilots, and upscaling pilot results. This integrated research involved WAG literature review, WAG modeling, and selected machine learning techniques. The selected machine learning techniques are stepwise regression and group method of data handling. First, the important parameters for the prediction of the WAG incremental recovery factor were selected. This includes reservoir properties, rock and fluid properties, and WAG injection scheme. Second, an extensive WAG and waterflood modeling was carried out involving more than a thousand reservoir models. Third, WAG incremental recovery factor mathematical predictive models were developed and tested, using the group method of data handling and stepwise regression techniques. HC-IWAG incremental recovery factor mathematical models were developed with a coefficient of determination of about 0.75, using 13 predictors. The developed WAG predictive models are interpretable and user-friendly mathematical formulas. These developed models will help the subsurface teams in a variety of ways. They can be used to identify the best candidates for WAG injection, evaluate and optimize the WAG process, help design successful WAG pilots, and facilitate the upscaling of WAG pilot results to full-field scale. All this can be accomplished in a short time at a low cost and with reasonable accuracy.
One of the techniques to increase oil recovery from hydrocarbon reservoirs is the injection of low salinity water. It is shown that the injection of low salinity water changes the wettability of the rock. However, there are argumentative debates concerning low salinity water effect on changing the wettability of the oil/brine/rock system in the oil reservoirs. In this regard, molecular dynamics simulation (MDS) as a tool to simulate the phenomena at the molecular level has been used for more than a decade. In this study, the Zisman plot (presented by KRUSS Company) was simulated through MDS, and then, contact angle experiments for n-decane interactions on the Bentheimer substrate in the presence of different concentrations of sodium ions were conducted. MDS was then used to simulate experiments and understand the wettability trend based on free-energy calculations. Hereafter, a new model was developed in this study to correlate free energies with contact angles. The developed model predicted the experimental results with high accuracy (R2 ∼ 0.98). A direct relation was observed between free energy and water contact angle. In contrast, an inverse relation was noticed between the ion concentration and the contact angle such that an increase in the ion concentration resulted in a decrease in the contact angle and vice versa. In other terms, increasing brine ionic concentrations in the presence of n-decane is linked to a decrease in free energies and an increase in the wetting state of a sandstone. The comparison between the developed model's predicted contact angles and experimental observations showed a maximum deviation of 14.32%, which is in satisfactory agreement to conclude that MDS can be used as a valuable and economical tool to understand the wettability alteration process.
Copolymers of acrylamide with the sodium salt of 2-acrylamido-2-methylpropane sulfonic acid-known as sulfonated polyacrylamide polymers-had been shown to produce very promising results in the enhancement of oil recovery, particularly in polymer flooding. The aim of this work is to develop an empirical model through the use of a design of experiments (DOE) approach for bulk viscosity of these copolymers as a function of polymer characteristics (i.e., sulfonation degree and molecular weight), oil reservoir conditions (i.e., temperature, formation brine salinity and hardness) and field operational variables (i.e., polymer concentration, shear rate and aging time). The data required for the non-linear regression analysis were generated from 120 planned experimental runs, which had used the Box-Behnken construct from the typical Response Surface Methodology (RSM) design. The data were collected during rheological experiments and the model that was constructed had been proven to be acceptable with the Adjusted R-Squared value of 0.9624. Apart from showing the polymer concentration as being the most important factor in the determination of polymer solution viscosity, the evaluation of the model terms as well as the Sobol sensitivity analysis had also shown a considerable interaction between the process parameters. As such, the proposed viscosity model can be suitably applied to the optimization of the polymer solution properties for the polymer flooding process and the prediction of the rheological data required for polymer flood simulators.
Throughout the application of enhanced oil recovery (EOR), surfactant adsorption is considered the leading constraint on both the successful implementation and economic viability of the process. In this study, a comprehensive investigation on the adsorption behaviour of nonionic and anionic individual surfactants; namely, alkyl polyglucoside (APG) and alkyl ether carboxylate (AEC) was performed using static adsorption experiments, isotherm modelling using (Langmuir, Freundlich, Sips, and Temkin models), adsorption simulation using a state-of-the-art method, binary mixture prediction using the modified extended Langmuir (MEL) model, and artificial neural network (ANN) prediction. Static adsorption experiments revealed higher adsorption capacity of APG as compared to AEC, with sips being the most fitted model with R2 (0.9915 and 0.9926, for APG and AEC respectively). It was indicated that both monolayer and multilayer adsorption took place in a heterogeneous adsorption system with non-uniform surfactant molecules distribution, which was in remarkable agreement with the simulation results. The (APG/AEC) binary mixture prediction depicted contradictory results to the experimental individual behaviour, showing that AEC had more affinity to adsorb in competition with APG for the adsorption sites on the rock surface. The adopted ANN model showed good agreement with the experimental data and the simulated adsorption values for APG and AEC showed a decreasing trend as temperature increases. Simulating the impact of binary surfactant adsorption can provide a tremendous advantage of demonstrating the binary system behaviour with less experimental data. The utilization of ANN for such prediction procedure can minimize the experimental time, operating cost and give feasible predictions compared to other computational methods. The integrated workflow followed in this study is quite innovative as it has not been employed before for surfactant adsorption studies.
The viscosity of four new polymers was investigated for the effect of aging at high temperature, with varying degrees of salinity and hardness. The four sulfonated based polyacrylamide co-polymers were FLOCOMB C7035; AN132 VHM; SUPERPUSHER SAV55; and THERMOASSOCIATIF copolymers. All polymer samples were aged at 80 °C for varying times (from zero to at least 90 days) with and without isobutyl alcohol (IBA) as an antioxidant. To see the effect of divalent ions on the polymer solution viscosity, parallel experiments were performed in a mixture of CaCl₂-NaCl of the same ionic strength as 5 wt % NaCl. The polymers without IBA showed severe viscosity reduction after aging for 90 days in both types of preparation (5 wt % NaCl or CaCl₂-NaCl). In the presence of IBA, viscosity was increased when aging time was increased for 5 wt % NaCl. In CaCl₂-NaCl, on the other hand, a viscosity reduction was observed as aging time was increased. This behavior was observed for all polymers except AN132 VHM.
This research aims to test four new polymers for their stability under high salinity/high hardness conditions for their possible use in polymer flooding to improve oil recovery from hydrocarbon reservoirs. The four sulfonated based polyacrylamide co-polymers were FLOCOMB C7035; SUPERPUSHER SAV55; THERMOASSOCIATIF; and AN132 VHM which are basically sulfonated polyacrylamide copolymers of AM (acrylamide) with AMPS (2-Acrylamido-2-Methylpropane Sulfonate). AN132 VHM has a molecular weight of 9⁻11 million Daltons with 32 mol % degree of sulfonation. SUPERPUSHER SAV55 mainly has about 35 mol % sulfonation degree and a molecular weight of 9⁻11 million Daltons. FLOCOMB C7035, in addition, has undergone post-hydrolysis step to increase polydispersity and molecular weight above 18 million Daltons but it has a sulfonation degree much lower than 32 mol %. THERMOASSOCIATIF has a molecular weight lower than 12 million Daltons and a medium sulfonation degree of around 32 mol %, and also contains LCST (lower critical solution temperature) type block, which is responsible for its thermoassociative characteristics. This paper discusses the rheological behavior of these polymers in aqueous solutions (100⁻4500 ppm) with NaCl (0.1⁻10 wt %) measured at 25 °C. The effect of hardness was investigated by preparing a CaCl₂-NaCl solution of same ionic strength as the 5 wt % of NaCl. In summary, it can be concluded that the rheological behavior of the newly modified co-polymers was in general agreement to the existing polymers, except that THERMOASSOCIATIF polymers showed unique behavior, which could possibly make them a better candidate for enhanced oil recovery (EOR) application in high salinity conditions. The other three polymers, on the other hand, are better candidates for EOR applications in reservoirs containing high divalent ions. These results are expected to be helpful in selecting and screening the polymers for an EOR application.