The objective of this study is to investigate the feasibility of steam flooding (SF) as an alternative method for offshore heavy oil reservoirs after water flooding (WF). A series of experiments was performed by using specially designed one-dimensional (1-D) and three-dimensional (3-D) experimental systems to prove the feasibility of SF and to study the effects of the timing of SF, the steam injection rate, and the addition of chemical agents (the nitrogen foams and displacing agents) on the performance of SF after WF. The results showed that, for offshore heavy oil reservoirs after WF processes, the SF process is a viable enhanced oil recovery method, which should start as early as possible if the economic conditions permit. It is extremely important to choose an appropriate steam injection rate for SF after the WF process. Compared with the pure SF process, the final oil recovery of the SF process with the addition of the nitrogen foam or the displacing agent increased by 12.83% and 7.58% in the 1-D experiments, respectively. The nitrogen foam and displacing agent have synergistic effects on the performance of the SF after WF processes. The final oil recovery of the SF process with the addition of the two chemical agents at the steam injection rate of 10 mL/min was 37.64%, which was 5.47% higher than that of the pure SF process in the 3-D experiments.

The diffusion coefficient of CO2 significantly influences the dissolution behavior of CO2 in nanofluids, playing a crucial role in phenomena such as viscous finger formation and instability onset. Acquiring empirical measurements of the CO2 diffusion coefficient(D) presents substantial technical and economic challenges. To address these challenges, this study employs Molecular Dynamics (MD) simulation to accurately calculate the D in nanofluids over a wide range of temperatures (293–343 K) and pressures (6–24 MPa). This systematic approach enables the creation of a comprehensive dataset, thereby enhancing the existing knowledge base. The results indicate that the increase in pressure functions as the driving force behind the diffusion of CO2, resulting in an enhancement of D. Regarding the temperature variation effects, elevated temperatures lead to a concurrent increase in the D. However, the increased thermal motion of cations at higher temperatures facilitate the formation of hydration shells, which hampers the diffusion of CO2.

Nanoparticle-enhanced carbonated water (NP-enhanced CW) is a novel and promising injection agent for coupled enhanced heavy oil recovery and CO2 storage. However, the adsorption behavior of nanoparticles at the heavy oil/CW interface under reservoir conditions is still unknown. The main objective of this study is to investigate the adsorption behavior of nanoparticles at the heavy oil/CW interface by using molecular dynamics simulations. The influences of nanoparticles on the interfacial properties of heavy oil/CW systems and CO2 molecular transfer were studied. Then, the influences of nanoparticle types, nanoparticle concentrations, CO2 concentrations, pressures, and temperatures were investigated, and the EOR mechanisms of NP-enhanced CW were also discussed. Finally, the oil displacement tests were conducted to verify the feasibility of nanoparticles to improve the performance of the CWI process in enhancing heavy oil recovery and CO2 storage. The results revealed that, compared with the CuO, Al2O3, TiO2, and Fe nanoparticles, the SiO2 nanoparticles resulted in the lowest interface tension (29.62 mN/m) and the largest interfacial thickness (28.23 & Aring;), and the most stable interface. An optimal SiO2 nanoparticle concentration and reservoir temperature existed. The CO2 solubility and injection pressure of SiO2 NP-enhanced CW should be increased as much as possible during a practical application of NP-enhanced CWI processes. The final recovery factor and CO2 storage efficiency of SiO2 NP-enhanced CWI were 55.62 % and 54.73 %, respectively, which increased 8.69 % and 10.62 %, and 37.37 % and 22.65 %, respectively, than those of the CWI process and CO2 flooding process. SiO2 NP-enhanced CWI process is a technically viable recovery process for enhancing heavy oil recovery and CO2 storage. This research represents the first time that the adsorption behavior of nanoparticles at the heavy oil/CW interface under reservoir conditions has been reported. These findings can offer valuable information for practical applications of NPenhanced CW in enhancing heavy oil recovery and CO2 storage.

Steam-assisted gravity drainage (SAGD) is a highly efficient thermal recovery technique for producing extra-heavy oil. However, it is still faced with the challenges of high steam usage, high energy losses, and adverse environmental impact. A novel method, called methane-assisted multi-lateral injector SAGD process (MAM-SAGD) was developed in this study for improving the performance of SAGD processes in heterogeneous reservoirs. In this study, for the first time, the large-scale experiments were conducted to study the production performance of MAM-SAGD processes, to clarify the underlying enhanced oil recovery mechanisms of MAM-SAGD processes, and to analyze the impacts of key parameters on the performance of MAM-SAGD processes. The results indicated that the MAM-SAGD process is a feasible method for extra-heavy oil recovery in heterogeneous reservoirs due to the combined mechanisms of multi-lateral injector and methane (CH4). The highest oil recovery factor of the MAM-SAGD processes was 49.05 %, which was more than 3 times that of the SAGD process. The contributions of multi-lateral injector and CH4 were 70.8 % and 29.2 %, respectively. The adverse impact degree of the mudstone barrier was ranked as follows: SAGD > multi-lateral injector SAGD > MAM-SAGD. The CH4 should be co-injected with steam at the late phase of a MAM-SAGD process. An intermediate amount of CH4 and a reasonable vertical distance between the main and lateral wellbores could significantly enhance the performance of MAM-SAGD processes. The results provide valuable experimental data that can be used to design practical applications of this novel process for producing the extra-heavy oil in heterogeneous reservoirs. More researches including designing application schemes of the MAM-SAGD process and verifying the performance of MAM-SAGD process by reservoir numerical simulations will be required in the future.

SiO2 nanoparticle-enhanced carbonated water (NCW) injection has great potential for improving recovery of heavy oil (HO) and CO2 geological storage. However, the CO2 mass transfer behavior between SiO2 NCW and HO under reservoir conditions remains elusive. Pressure-volume-temperature experiments were conducted in this study to explore the CO2 mass transfer behavior between SiO2 NCW and HO under reservoir conditions. A novel mathematical model was subsequently developed to simultaneously determine two CO2 diffusion coefficients in the SiO2 NCW and HO (DNCW and DHO), considering the movement of the interface position. Finally, the impacts of the operational and model parameters were thoroughly examined. These results demonstrated that the SiO2 NPs can enhance CO2 diffusion from the SiO2 NCW to HO. The DNCW and DHO for the SiO2 NCW/HO system are 4.35 x 10-9 m2/s and 1.33 x 10-10 m2/s, respectively, which are 2.59 % and 8.13 % higher than those in the CW/HO system, respectively, under the same conditions. A higher SiO2 NP concentration, CO2 diffusion time, initial pressure, and temperature have a more favorable impact on CO2 diffusion between the SiO2 NCW and HO systems. However, an excessive SiO2 NP concentration and temperature decrease the capacity of SiO2 NPs to enhance CO2 diffusion. SiO2 NCW injection can achieve better performance in a reservoir with HO with fewer heavy components. The initial CO2 concentration in SiO2 NCW should be increased as much as possible. These findings will offer valuable information for applications of SiO2 NCW injection techniques in enhancing HO recovery and CO2 geological storage.

The SAGP (steam and gas push) process is an effective enhanced oil recovery (EOR) method for heavy oil reservoirs. Understanding the microscopic interactions among steam, non-condensable gasses (NCGs), and heavy oil under reservoir conditions in SAGP processes is important for their EOR applications. In this study, molecular simulations were performed to investigate the microscopic interactions among steam, NCG, and heavy oil under reservoir conditions in SAGP processes. In addition, the microscopic EOR mechanisms during SAGP processes and the effects of operational parameters (NCG type, NCG–steam mole ratio, temperature, and pressure) were discussed. The results show that the diffusion and dissolution of CH4 molecules and the extraction of steam molecules cause the molecules of saturates with light molecular weights in the oil globules to stretch and gradually detach from one another, resulting in the swelling of heavy oil. Compared with N2, CH4 has a stronger ability to diffuse and dissolve in heavy oil, swell the heavy oil, and reduce the density and viscosity of heavy oil. For this reason, compared with cases where N2 is used, SAGP processes perform better when CH4 is used, indicating that CH4 can be used as the injected NCG in the SAGP process to improve heavy oil recovery. As the NCG–steam mole ratio and injection pressure increase, the diffusion and solubility abilities of CH4 in heavy oil increase, enabling CH4 to perform better in swelling the heavy oil and reducing the density and viscosity of heavy oil. Hence, increasing the NCG–steam mole ratio and injection pressure is helpful in improving the performance of SAGP processes in heavy oil reservoirs. However, the NCG–steam mole ratio and injection pressure should be reasonably determined based on actual field conditions because excessively high NCG–steam mole ratios and injection pressures lead to higher operation costs. Increasing the temperature is favorable for increasing the diffusion coefficient of CH4 in heavy oil, swelling heavy oil, and reducing the oil density and viscosity. However, high temperatures can result in intensified thermal motion of CH4 molecules, reduce the interaction energy between CH4 molecules and heavy oil molecules, and increase the difference in the Hildebrand solubility parameter between heavy oil and CH4–steam mixtures, which is unfavorable for the dissolution of CH4 in heavy oil. This study can help readers deeply understand the microscopic interactions among steam, NCG, and heavy oil under reservoir conditions in SAGP processes and its results can provide valuable information for the actual application of SAGP processes in enhancing heavy oil recovery.

Steam channeling significantly affects the production performance of cyclic steam stimulation (CSS) wells in offshore heavy oil reservoirs. However, there remains a lack of effective methods for evaluating the steam channeling severity between CSS wells in offshore heavy oil reservoirs. This study develops a novel evaluation model to quantitatively evaluate the steam channeling severity between CSS wells in offshore heavy oil reservoirs via the improved AHP-CRITIC (IAHP-CRITIC) method and the cloud model. The results indicated that, compared with the reservoir survey results for the three typical reservoirs, the accuracies of the results obtained by the AHP, CRITIC, AHP-CRITIC, and IAHP-CRITIC methods were 88%, 52%, 92%, and 100%, respectively. Therefore, the IAHP-CRITIC method was more reliable than the other methods in terms of calculating the indicator weights and evaluating the steam channeling severity between the CSS wells. The Lw7 and Lw12 in the L reservoir and Rw2, Rw3, and Rw6 in the R reservoir exhibited strong steam channeling. It is necessary to control the steam channeling of these CSS wells. This is the first study to report the evaluation of steam channeling severity between CSS wells in offshore heavy oil reservoirs. This study provides an effective model to quantitatively evaluate the steam channeling severity between CSS wells and offers valuable insights for the selection of effective strategies to control the steam channeling between CSS wells and enhance offshore heavy oil recovery.

Recently, maximum reservoir contacting (MRC) wells have attracted more and more attention and have been gradually applied to CO2 WAG injections. During the use of MRC wells for CO2 WAG injections, intelligent completions are commonly considered to control CO2 breakthroughs. However, the design of the operational and intelligent completion parameters is a complicated process and there are no studies on the co-optimization of the operational and intelligent completion parameters for CO2 WAG processes. This study outlines an approach to enhance the oil recovery from CO2 WAG injection processes through the co-optimization of the operational and intelligent completion parameters of MRC wells in a carbonate reservoir. First, a simulation method is developed by using Petrel and Intersect. Then, a series of simulations are performed to prove the viability of intelligent completions and to investigate the effects of the timing and duration of the CO2 WAG injection, as well as the type, number, and placement of intelligent completion devices on the performance of a CO2 WAG injection by MRC wells. Finally, the imperialist competitive algorithm is used to co-optimize the operational and intelligent completion parameters for MRC wells. The results show that compared with the spiral inflow control device (SICD), autonomous inflow control device (AICD), labyrinth inflow control device (LICD), and annular interval control valve (AICV), the nozzle inflow control device (NICD) is the best type of intelligent completion device for MRC wells. There is an optimal installation timing, inflow area, and number of NICDs for a CO2 WAG injection by MRC wells. The NICDs need to be placed based on the permeability distribution. The oil recovery for the optimal case with the NICDs reached 46.43%, which is an increase of 3.8% over that of the base case with a conventional completion. In addition, compared with the non-uniformity coefficient of the base case (11.7), the non-uniformity coefficient of the optimal case with the NICDs decreased to 4.21. This is the first time that the co-optimization of the operational and intelligent completion parameters of a CO2 WAG injection has been reported, which adds more information about the practical applications of MRC wells in CO2 WAG injections for enhancing oil recovery in carbonate reservoirs.

Infill drilling is one of the most effective methods of improving the performance of polymer flooding. The difficulties related to infill drilling are determining the optimal numbers and placements of infill wells. In this study, an improved Archimedes optimization algorithm with a Halton sequence (HS-AOA) was proposed to overcome the aforementioned difficulties. First, to optimize infill well placement for polymer flooding, an objective function that considers the economic influence of infill drilling was developed. The novel optimization algorithm (HS-AOA) for infill well placement was subsequently developed by combining the AOA with the Halton sequence. The codes were developed in MATLAB 2023a and connected to a commercial reservoir simulator, Computer Modeling Group (CMG) STARS, Calgary, AB, Canada to carry out infill well placement optimization. Finally, the HS-AOA was compared to the basic AOA to confirm its reliability and then used to optimize the infill well placements for polymer flooding in a typical offshore oil reservoir. The results showed that the introduction of the Halton sequence into the AOA effectively increased the diversity of the initial objects in the AOA and prevented the HS-AOA from becoming trapped in the local optimal solutions. The HS-AOA outperformed the AOA. This approach was effective for optimizing the infill well placement for polymer flooding processes. In addition, infill drilling could effectively and economically improve the polymer flooding performance in offshore oil reservoirs. The net present value (NPV) of the polymer flooding case with infill wells determined by HS-AOA reached USD 3.5 × 108, which was an increase of 7% over that of the polymer flooding case. This study presents an effective method for optimizing infill well placement for polymer flooding processes. It can also serve as a valuable reference for other optimization problems in the petroleum industry, such as joint optimization of well control and placement.

A well-defined development sequence of each fault block in a fault-block oilfield is the prerequisite for field development plan design. Where there are very few fault-block oilfields, the method of numerical simulation in combination with economic evaluation is acceptable for comparison. However, with the increase in the number of fault-block oilfields, there will be enormous arrangements and combinations that require massive data, heavy workload, high cost and long time. In response, an improved BP neural network model based on imperialist competitive algorithm (ICA) was proposed to predict the net present value (NPV) of each fault-block oilfield in the fault-block oilfields, allowing the determination of production sequence and prioritized producing range of fault block exploitation according to NPV. Based on the actual geological reservoir database, this method avoids human subjectivity and overcomes the limitations of the existing methods, so it is of great significance to enhance the overall benefit of the development of fault-block oilfields.

Recently, discontinuous polymer flooding has been proposed and successfully applied in some offshore oilfields. The performance of discontinuous polymer flooding depends on various operational parameters, such as injection timing, polymer concentrations, and crosslinker concentrations of four types of chemical slugs. Because the number of the operational parameters are large and they are nonlinearly related, the traditional reservoir numerical simulation might not simultaneously obtain the optimal results of these operational parameters. In this study, to simulate the discontinuous polymer flooding processes, a simulation model was built using a commercial reservoir simulator (CMG STARS), in which the mechanisms of the four types of chemical slugs were considered, such as polymer viscosification, adsorption, and degradation. Then, a PSO–ICA algorithm was developed by using the PSO algorithm to improve the exploration ability of the ICA algorithm. The codes were written with MATLAB and linked to CMG STARS to perform optimization processes. Finally, the PSO–ICA algorithm was compared with the ICA and PSO algorithms on benchmark functions to verify its reliability and applied to optimize a discontinuous polymer flooding process in a typical offshore oilfield in Bohai Bay, China. The results showed that the developed PSO–ICA algorithm had lower iteration numbers, higher optimization accuracy, and faster convergence rate than these of PSO and ICA, indicating that it was an effective method for optimizing the operational parameters of discontinuous polymer flooding processes. Compared to the continuous polymer flooding, the discontinuous polymer flooding had a higher oil production rate, a lower water cut, and a lower residual oil saturation. The net present value of the optimal scheme of discontinuous polymer flooding reached 7.49 × 108 $, which is an increase of 6% over that of the scheme of continuous polymer flooding. More research including selecting more reasonable parameters of the PSO–ICA algorithm to increase its optimization accuracy and convergence rate, comparing with other available optimization algorithms, and verifying the performance of the optimal scheme of discontinuous polymer flooding in the practical offshore oilfield will be required in the future.

Infill drilling is one of the most effective methods to improve the performance of poly-mer flooding. The difficulties related to infill drilling are determining the optimal numbers and placements of infill wells. In this study, an improved archimedes optimization algorithm with Halton sequence (HS-AOA) was proposed to overcome the aforementioned difficulties. First, to optimize the infill well placement for polymer flooding, an objective function that considered the economic influence of infill drilling was developed. Then, the novel optimization algorithm (HS-AOA) for infill well placement was developed by combining the AOA with the Halton se-quence. The codes were developed in MATLAB and connected to a commercial reservoir simula-tor CMG STARS to carry out the infill well placement optimization. Finally, the HS-AOA was compared to the basic AOA to confirm its reliability and then used to optimize the infill well placements for polymer flooding in a typical offshore oil reservoir. The results showed that the introduction of the Halton sequence into AOA effectively increased the diversity of the initial ob-jects in the AOA and avoided the HS-AOA trapping into the local optimal solutions. The HS–AOA outperformed the AOA. It was an effective approach to optimize the infill well placement for polymer flooding processes. In addition, infill drilling could effectively and economically im-prove the polymer flooding performance in offshore oil reservoirs. The NPV of the polymer flooding case with infill wells determined by HS-AOA reached 3.5 × 108 $, which was an increase of 7% over that of the polymer flooding case. This study presents an effective method for opti-mizing infill well placement for polymer flooding processes. It also can serve as a valuable refer-ence for other optimization problems in the petroleum industry, such as joint optimization of well control and placement.

Depletion process or the so-called cold production from some heavy oil reservoirs in Venezuela and Canada presents foamy oil behavior. The formation and displacement mechanism of foamy oil have been extensively studied. Maintaining a certain pressure drop rate is a prerequisite for the formation of stable foamy oil flow in situ and for favorable cold production performance in such reservoirs. However, for discontinuous depletion process in such reservoirs, the occurrence state and displacement characteristics of foamy oil flow are still not clear. A specific 1D long core displacement experimental device with micro-visualization function was designed. Three 1D core pressure depletion experiments were conducted using a typical heavy oil sample collected from the Heavy Oil Belt in Venezuela, and the displacement characteristics and oil/gas occurrence state during the continuous and discontinuous depletion processes for foamy oil were compared. In addition, the influence of pressure drop rate on production performance and the microscopic characteristics of foamy oil flow after the resumption of discontinuous depletion process was investigated. The experimental results show that small dispersed gas bubbles tend to coalesce into large bubbles and form free gas at the shut-in stage during the discontinuous depletion process. Compared to the case of continuous depletion process, after the discontinuous depletion process was resumed, the foamy oil displacement efficiency became lower, the peak oil production rate decreased, the pseudo bubble-point pressure increased, and the recovery factor became lower. The practice of increasing the pressure drop rate properly can reduce the pseudo bubble-point pressure and improve the foamy oil displacement efficiency to a certain extent. The study provides a theoretical basis for improving the performance of the discontinuous depletion process in foamy oil reservoirs.

Supercritical water (SCW) has emerged as a promising thermal agent for enhancing heavy oil recovery, yet its recovery mechanisms have not been fully understood, thereby limiting its practical application. To address this knowledge gap, this study conducted pyrolysis and sand pack flooding experiments to study the feasibility and mechanisms of SCW flooding. Subsequently, a novel simulation model dedicated to SCW flooding was developed and its accuracy was validated through fitting the experimental results. Furthermore, sensitivity studies were performed using the developed model to explore the impact of various factors on SCW flooding. The findings revealed that in SCW, the heavy oil upgrading was found to effectively reduce oil viscosity, thereby playing a pivotal role in enhancing oil recovery. Compared to steam flooding, SCW flooding led to a remarkable 14

The frustratingly fragile nature of neural network models make current natural language generation (NLG) systems prone to backdoor attacks and generate malicious sequences that could be sexist or offensive. Unfortunately, little effort has been invested to how backdoor attacks can affect current NLG models and how to defend against these attacks. In this work, by giving a formal definition of backdoor attack and defense, we investigate this problem on two important NLG tasks, machine translation and dialog generation. Tailored to the inherent nature of NLG models (e.g., producing a sequence of coherent words given contexts), we design defending strategies against attacks. We find that testing the backward probability of generating sources given targets yields effective defense performance against all different types of attacks, and is able to handle the one-to-many issue in many NLG tasks such as dialog generation. We hope that this work can raise the awareness of backdoor risks concealed in deep NLG systems and inspire more future work (both attack and defense) towards this direction.

In this work, phase structures of a supercritical water (SCW)/supercritical carbon dioxide (scCO2)/heavy oil system are evaluated and characterized by performing molecular dynamics (MD) simulations. The MD simulation processes are initialized with structures of an oil droplet-in-SCW + scCO2 mixture, and its resultant structure, radial distribution function (RDF), solvation free energy, and cohesive energy density (CED) were then integrated to analyze the simulation results. The SCW and scCO2 are found to disperse into the oil drop and induce the oil swelling through stretching the oil molecules. Both saturates and aromatics can be easily dissolved in an SCW + scCO2 mixture due to the attractive interaction between them, whereas resins and asphaltenes are intended to conduct self-assembly due to their repulsion to the SCW + scCO2 mixture and high CED, resulting in a pseudo-one phase structure of an SCW/scCO2/heavy oil system. The presence of scCO2 can enhance the miscibility of heavy oil with an SCW + scCO2 mixture through intensifying the affinity between heavy oil and solvent(s) as well as destroying the hydrogen bonds by diluting the SCW. Elevating temperature is adverse to the miscible process between heavy oil with an SCW + scCO2 mixture on account of the reduced density of such a mixture. A moderate increase in pressure facilitated dissolution of heavy oil in an SCW + scCO2 mixture; however, an excess increase in pressure can lead to a suppressed miscibility between heavy oil and an SCW + scCO2 mixture since the hydrogen bonding is significantly recovered.

The suitable concentration of mobility-controlled oil displacement agent was selected through laboratory experiments, and the development mechanism of mobility-controlled oil displacement agent in the water flooding process was studied. The results show that when the concentration of mobility control oil displacement agent is 0.15 %, the viscosity reduction effect is the best. Fluid injection pressure can be reduced by mobility controlled oil displacement agent. The mobility control oil displacement agent can improve the oil displacement efficiency, and the recovery rate of Tuha heavy oil is increased from 36.58 % to 65.13 %. The mobility control oil displacement agent has a strong effect of solubilization and viscosity reduction at low shear rate of the formation, and has a viscosity increase for water, so it can improve the development effect.

Cyclic steam injection is widely applied in the development of heavy oil reservoirs. However, as reservoir development continues, steam channeling phenomena become increasingly severe, Serious impact on development effectiveness. Slug combinations of gel and foam is more effective than using gel and foam alone for steam channeling control. In this study, taking a steam channeling well in the A oilfield as an example, a numerical simulation model is established using CMG software. Based on this model, the effects of foaming agent concentration, foaming agent injection rate, gel injection timing, and nitrogen injection quantity on the development performance in the gel foam slug steam channeling plugging system are investigated. The research results indicate that higher foaming agent concentration, faster injection rate, and earlier gel injection timing lead to increased oil production. The nitrogen injection quantity exhibits an optimal value. Comparing the performance of gel foam slug system assisted cyclic steam injection with steam huff and puff alone, the results show that the gel foam slug system assisted cyclic steam injection achieves an incremental oil production of 9104 m3 over four cycles, as compared to steam huff and puff alone.

Summary For steamflooding processes, steam quality plays a crucial role because it affects enhanced oil recovery mechanisms and production performance. Many numerical simulations have been performed on the role of steam quality. However, few studies have evaluated the role of steam quality on steamflooding performance by experimental measurements because of the lack of a generalized experimental methodology to accurately generate and measure steam with different qualities under reservoir conditions. The objective of this study is to propose a generalized experimental methodology for investigating the role of steam quality on steamflooding performance. A steam quality controlling box was newly designed and fabricated to generate steam with different qualities, and its reliability was verified by a novel steam quality measurement system together with a developed theoretical method. Then, a series of experiments were conducted by our designed 1D and 2D sandpack models to evaluate the steamflooding performance under different steam qualities. The results showed that the developed methodology could accurately generate and measure steam with different steam qualities. The maximum errors between desired, measured, and calculated steam qualities were 4.39% under the experimental conditions in this study. The steam quality substantially affected the steamflooding performance. A higher steam quality led to a lower water cut, a lower maximum pressure difference between the inlet and outlet of the sandpack model, a lower water/oil ratio (WOR), a lower steam/oil ratio (SOR), a higher oil recovery, and a higher oil production rate. However, there is an optimal value of steam quality from the view of heat efficiency in this study. The oil recoveries of 2D steamflooding experiments increased from 36.30 to 45.02% when the steam quality increased from 0 to 0.8. However, the optimal steam quality of 0.6 had the maximum heat efficiency at 3.16×10−5 kJ−1. This research contributes to a better understanding of steam quality on steamflooding performance and also provides a generalized methodology for other steam injection processes.

Supplementary Table 1. RT-PCR primers for Wnt16, AKT1 and GAPDH, and primers for Wnt16 and AKT1 3'-UTR in the luciferase report assay Supplementary Table 2. Differentiated dysregulation of miRNAs in T-LBL Supplementary Table 3. The corresponding cutoff score of miR-374b expression for each clinicapathological feature according to ROC curve analysis Supplementary Table 4. Association of miR-374b downregulation with clinicopathological features of 58 L-TBL patients