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There have been numerous studies on predicting the production performance of the steam assisted gravity drainage (SAGD) process by data‐driven models with different machine learning algorithms since their introduction into industry. Similar efforts on SAGD infill wells, nevertheless, remain rare for this advanced alteration in improving the classical SAGD performance. On the other hand, predictive tools to optimize an infill well start time is useful in maximizing bitumen production and minimizing its costs. In this paper, a series of SAGD infill well models are constructed with selected ranges of operational conditions. Three SAGD infill well production performance indicators, namely, an increased ratio (Rincrease), a total steam–oil ratio (SORtotal), and a stolen ratio (RStolen) for each SAGD infill well, are calculated based on simulated infill well cases and control models. Five different machine learning algorithms (an artificial neural network [ANN] algorithm, three gradient boosting decision tree [GBDT] algorithms, and a support vector machine [SVM] algorithm) are trained, tested, and evaluated for their effectiveness in predicting those three indicators as output parameters, given seven SAGD relevant parameters as input parameters. Comparisons of different data sets show that the ANN is the best in predicting all three performance indicators under different infill well start times among all the above machine learning algorithms, while the GBDT algorithms have a better ability to learn a variation trend in the SAGD infill well performance. [ABSTRACT FROM AUTHOR]

Many studies have analyzed the cumulative production performance in the SAGD (steam assisted gravity drainage) process by data-driven models but a study based on these models for a dynamic analysis of a SAGD production period is still rare. It is important for engineers to define the production period in a SAGD process as it has a stable and high oil production rate and engineers need to reset operational conditions after the production period starts. In this paper, a series of SAGD models were constructed with selected ranges of reservoir properties and operational conditions. Three SAGD production period parameters, including the start date, end date, and duration, are collected based on the simulated production performances. artificial neural network, extreme gradient boosting, light gradient boosting machine, and catboost were constructed to reveal the hidden relationships between twelve input parameters and three output parameters. The data-driven models were trained, tested, and evaluated. The results showed that compared with the other output parameters, the R2 of the end date is the highest and it becomes higher with a larger training data set. The extreme gradient boosting algorithm is a better choice to predict the Start date while the artificial neural network generates better prediction for the other two output parameters. This study shows a significant potential in the use of data-driven models for the SAGD production dynamic analysis. The results also serve to support the utilization of the data-driven models as efficient tools for predicting a SAGD production period.

The work is devoted to methods of solving multiphase nonisothermal fluid flow problems in reservoirs with a large number of horizontal wells. A nonlinear law with a limiting pressure gradient is used for the oil. Methods for solving multiphase nonisothermal fluid flow problems in a porous medium based on the decomposition methods are developed. The proposed methods are implemented in heterogeneous computing systems. [ABSTRACT FROM AUTHOR]

An integral model of the steam assisted gravity drainage of an oil field has been developed on the basis of the law of conservation of the masses of the phases and the law of conservation of their energy. A verification of the results of calculations performed by this model has been performed, and it was established that they are in satisfactory agreement with the corresponding field data. It is shown that the final oil recovery factor for the Senlac oil field comprises 32% and that the optimization of the development system of the Fengcheng field increases its oil recovery factor by 7%. [ABSTRACT FROM AUTHOR]

The world's petroleum consumption is projected to increase steadily, with most of the oil discovered worldwide remaining unrecovered. Thermal Enhanced Oil Recovery (TEOR) techniques have been found to be effective in increasing the oil recovery from mature reservoirs. This paper compares the two most commonly used TEOR methods, InSitu Combustion (ISC) and hot fluid injection, in the Sudanese Oil Field, Orion Field. The reservoir properties, operating conditions, production performance, technical challenges, and opportunities, including depth limitations, conventional completion problems, and reservoir heterogeneity, were analyzed for each method. Economic feasibility and environmental impacts are also discussed, including factors such as capital and operating costs, oil recovery rates, and carbon emissions. This study offers valuable insights into the practical aspects of implementing TEOR projects in the Sudanese oil field and can inform decision-making in the oil and gas industry, particularly in reservoir engineering, production optimization, and environmental management. [ABSTRACT FROM AUTHOR]

The work is devoted to the methods of solving multiphase nonisothermal fluid flow problems in the reservoirs with a large number of horizontal wells. The model of steam assisted gravity drainage is considered. Darcy's linear law is used. The methods for solving multiphase nonisothermal fluid flow problems in porous medium based on the decomposition methods are proposed. The proposed methods are implemented on the heterogeneous computing systems. [ABSTRACT FROM AUTHOR]

As the price of oil decreases, it is becoming increasingly important for oil companies to operate in the most cost-effective manner. This problem is especially apparent in Western Canada, where most oil production is dependent on costly enhanced oil recovery (EOR) techniques such as steam-assisted gravity drainage (SAGD). Therefore, the goal of this study is to create an artificial neural network (ANN) that is capable of accurately predicting the ultimate recovery factor of oil reservoirs by steam-assisted gravity drainage (SAGD). The developed ANN model featured over 250 unique entries for oil viscosity, steam injection rate, horizontal permeability, permeability ratio, porosity, reservoir thickness, and steam injection pressure collected from literature. The collected data set was entered through a feed-forward back-propagation neural network to train, validate, and test the model to predict the recovery factor of SAGD method as accurate as possible. Results from this study revealed that the neural network was able to accurately predict recovery factors of selected projects with less than 10% error. When the neural network was exposed to a new simulation data set of 64 points, the predictions were found to have an accuracy of 82% as measured by linear regression. Finally, the feasibility of ANN to predict the recovery performance of one of the most complicated enhanced heavy oil recovery techniques with reasonable accuracy was confirmed.

A deep study of the mechanism and processes of development of the bitumen and heavy oil deposits, as well as oil in tight and shale reservoirs, was conducted in the special test facilities in North America. These studies served as the basis for a technological leap for the transfer of these resources to the category of recoverable reserves. Based on the development of new technologies for horizontal drilling, multi-stage hydraulic fracturing, and the SAGD method in various modifications, commercially attractive results have been achieved, which allow stable development of fields with unconventional reserves at low oil prices. Marginal reserves in a deep crisis environment are the main reason for the write-off of reserves and their transition to large diversified companies.

Copyright of Journal of China University of Petroleum is the property of China University of Petroleum and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Special Oil & Gas Reservoirs is the property of Special Oil & Gas Reservoirs Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Steam injection distribution optimization refers to the process of distributing steam injection in steam assisted gravity drainage (SAGD) oil field to maximize the total oil production. A novel optimization method that integrates long short-term memory (LSTM) neural network and dynamic programming is presented in this paper to solve the steam injection distribution optimization problem for the first time. In the proposed method, LSTM is used to construct the prediction model to predict oil production of the wells. With the prediction result, dynamic programming optimizes steam injection distribution in the oil field to maximize total oil production. Convergence stability and computational complexity of the dynamic programming method have been analyzed and presented in this research. A web-based geographical information system called Petroleum Explorer is also developed based on the proposed method. Experiments on two pads of a real-world SAGD project demonstrate that LSTM model gives better prediction result than other five existing models and production improvement of the proposed method is highly related to parameter setting of the optimization process • An optimization method is proposed for steam assisted gravity drainage oil field. • Long Short-Term Memory models are constructed to predict future oil production. • Dynamic programming is used to optimize the steam injection distribution problem. • A web-based system is developed to implement the experiments of the method. • Oil production of two case studies can be improved by 12.25% and 24.07% separately. [ABSTRACT FROM AUTHOR]

Water is critically important, because its supply is under stress. In oil fields, the ratio-of-water-to-oil (WCUT%) can be 95% or higher. Managing this produced water is a great challenge whereas the best opportunity to reduce costs, improve profitability and preserve the natural environment. The oil industry is looking for more effective ways to reduce water consuming and improve the recovery rates. Nano materials are an obvious place to look. This study provides new insights into ZnO nanoparticles effects on residual oil saturation (SOR) and WCUT% through steam assisted gravity drainage (SAGD) process by experimental work. Laboratory tests were conducted in two experiments through the use of 2 dimensional scaled SAGD cell from an Iranian heavy oil reservoir. In the first experiment, the SAGD cell was saturated with heavy oil and in the second one, the cell was flooded with nanoparticles before saturation with oil. The amount of recoveries were monitored during 12 hours. Results show that the ultimate oil recoveries increase from 52.43% to 87.93% by adding ZnO nanoparticles, respectively. The experimental results provide the nanoparticles ability to reduce produced water and minimize fresh water use can contribute to water conservation.

Highlights • PCLR appears to be a promising option for the production of diluent at SAGD facilities. • Partial reduction of ilmenite ore to Fe2.5+ and Fe2+ containing species is required to avoid the production of CO2. • Steam and diluent requirements can be met, with excess power generation, at lower costs than traditional syngas technologies. • CO2 emissions targets can be met, while reducing boiler feed water (BFW) make-up. Abstract Chemical looping reforming is a promising option for the conversion of gaseous fuels to high quality syngas suitable for gas-to-liquids (GtL) processes. This work evaluates the potential for syngas, heat, power, and steam generation for diluent production at steam assisted gravity drainage (SAGD) facilities using low cost ilmenite ore pressurized chemical looping reforming (PCLR). Preliminary fixed-bed reactor testing on a naturally occurring Canadian ilmenite ore was performed to determine the optimal operating regime for syngas generation. Based on SEM characterization, EDX elemental mapping, XRD, and Mössbauer spectroscopy measurements it was demonstrated that partial reduction to Fe2.5+ and Fe2+ containing species is required to avoid the production of CO 2. Additionally, the reduction to Fe° containing species should be minimized to limit the formation of carbon and metal carbides. These results were used to generate material and energy balances via Aspen HYSYS V9 process simulation software of the entire PCLR process for SAGD applications using a Canada's Oil Sands Innovation Alliance (COSIA) SAGD facility template. Thorough energy integration of the combined PCLR-SAGD process using Pinch Analysis suggests that steam and diluent requirements can be met, with excess power generation, at lower costs than more traditional syngas generation technologies, while meeting CO 2 emissions targets and reducing boiler feed water (BFW) make-up. Having shown that process performance is attractive, a techno-economic assessment to establish the most economical design for the PCLR-SAGD process is now required. [ABSTRACT FROM AUTHOR]

Chemical looping combustion is a promising option for the conversion of fossil fuels with inherent separation of CO 2 and efficient use of energy. Nevertheless, key process challenges such as oxygen carrier reaction rates, costs, and environmental concerns still exist. We expected that these challenges would be overcome by operating chemical looping combustors at elevated pressures with ilmenite ore as the oxygen carrier. This work describes a design study that was performed to examine the potential for replacement of once-through steam generators (OTSGs) at steam assisted gravity drainage (SAGD) facilities for bitumen production with near zero CO 2 emission pressurized chemical looping combustors. In order to minimize capital costs for the systems, design was constrained to ensure that all major components could be shop built. Heat and material balances for many different process configurations were generated using Aspen HYSYS process simulation software allowing for a range of options to be evaluated. We determined that operating pressures should be restricted to between 4 and 7 bar(g) to achieve very high steam generation efficiencies, while avoiding high power demand. Energy integration of pressurized chemical looping combustion with a Canada’s Oil Sands Innovation Alliance (COSIA) typical SAGD plant using Pinch analysis was performed resulting in a significant decrease in natural gas and boiler feed water (BFW) make-up requirements, while at the same time reducing CO 2 emissions by over 95% down to 2.85 kg CO 2 /bbl bitumen. Having established that process performance is attractive, an economic study to establish the most economical design for pressurized chemical looping combustion for steam generation is now required. [ABSTRACT FROM AUTHOR]

In this work, we present the development of a mathematical model and simulation algorithm for the three key constituents of the steam assisted gravity drainage (SAGD) process, namely the steam generator, the steam injector, and the steam chamber. The modeling equations are derived by applying the conservation principle and adopting several empirical/algebraic correlations that support state estimation. In order to avoid the excessive design complexity and the computational load involved in existing models in the current literature, we attempt to develop the reduced-complexity models so that they can be compatible with the state estimation schemes and useful for control related applications. The developed models for the steam injector and the steam chamber are validated through either the simulation results of Petroleum Expert as a reservoir simulator or the similar models in the literature. [ABSTRACT FROM AUTHOR]

Oil sands resource is the third largest oil reserve, and 70% of the oil sands are in Canada. The emerging of Steam Assisted Gravity Drainage technology has made the commercial development of oil sands economically feasible. However, with the recent oil price crash, the development of oil sands has faced an uphill battle. A realistic and integrated evaluation model is highly needed to overcome difficulties from the low oil price and provide meaningful and valuable information for operators as well as investors to make the right decision. The existing evaluation models have considerable limitations (i.e., the incapability of evaluating integrated oil sands development with Steam Assisted Gravity Drainage technology, the lack of investigation into the input parameters with historical data, and ignoring the effect of the subsurface reservoir, etc.). This study developed an integrated evaluation model through the analyses of a significant amount of actual historical data. This integrated model includes six subcomponent models, ranging from the subsurface reservoir to infield flowline. Data from 35 Canadian oil sands development with 15 internal and external parameters were collected and investigated. The oil price effect was analyzed and quantified through simulations. The breakeven Western Canada Select oil price of $39/bbl. (equal to the West Texas Intermediate oil price of $55/bbl.) and other key price points and distributions were identified. Also, the top seven geological and technical parameters that contribute 86% of the net present value variations were identified and investigated. These quantified effects of external and internal parameters are useful findings for decision making. Considering various price scenarios and uncertainties of the input parameters, this study has concluded that developing oil sands resources with the Steam Assisted Gravity Drainage technology is economically feasible and socially beneficial after we take all stakeholder interests into consideration, which is true even with the sustainable and realistic oil price in the foreseeable future. [ABSTRACT FROM AUTHOR]

In McMurray Formation, steam assisted gravity drainage is used as the primary in-situ recovery technique to recover oil sands. Different geological reservoir settings and long horizontal wells impose limitations and operational challenges on the implementation of steam-assisted gravity drainage (SAGD). The dual-string tubing system is the conventional completion scheme in SAGD. In complex reservoirs where dual-string completion cannot improve the operation performance, operators have adopted flow control devices (FCDs) to improve project economics. FCDs secure more injection/production points along the horizontal sections of the SAGD well pairs, hence, they maximize ultimate bitumen recovery and minimize cumulative steam-oil ratio (cSOR). This paper will focus on the optimization of outflow control devices (OCDs) in SAGD reservoirs with horizontal wellbore undulations. We present the detailed optimization workflow and show the optimization results for various scenarios with well pair trajectory undulation. Comparing the results of the optimized OCDs case with a dual-string case of the same SAGD model shows improvements in steam distribution, steam chamber growth, bitumen production, and net present value (NPV).

The high heterogeneity of petroleum reservoirs, represented by their spatially varying rock properties (porosity and permeability), greatly dictates the quantity of recoverable oil. In this work, the estimation of the spatial permeability distribution, which is crucial for predicting the future performance of a reservoir, is carried out through a history matching technique based on constrained ensemble Kalman filtering (EnKF). The main contribution in this work is the novel implementation of hard and soft constraints in the recursive EnKF estimation methodology for petroleum reservoirs. Hard data is obtained from the actual values of the reservoir parameters at discrete locations obtained by core sampling and well logging, while the soft data considered is obtained from correlograms, which characterize the spatial correlation of the rock properties in a reservoir. In each time update, the parameter estimates obtained from the unconstrained EnKF are modified by one of two novel algorithms. In the first, the correlation matrix obtained after the unconstrained EnKF update is transformed to honour the true correlation structure from the correlogram by applying a projection-based method. The second algorithm involves the use of a technique for soft constrained covariance localization. We observe that the soft data constrained localization method results in the best estimates of the permeability and also reduces the computational time significantly. We quantify the improvement in estimation performance of each of the constrained methods over unconstrained estimation. The method, while developed for estimation in petroleum reservoirs, is also generally applicable to systems with spatial heterogeneity and underlying spatial correlations. [ABSTRACT FROM AUTHOR]

Unconventional heavy oil resource plays are important contributors to oil and gas production, as well as controversial for posing environmental hazards. Monitoring those reservoirs before, during, and after operations would assist both the optimization of economic benefits and the mitigation of potential environmental hazards. This study investigates how gravity gradiometry using superconducting gravimeters could resolve depletion areas in steam assisted gravity drainage (SAGD) reservoirs. This is achieved through modelling of a SAGD reservoir at 1.25 and 5 years of operation. Specifically, the density change structure identified from geological, petrological, and seismic observations is forward modelled for gravity and gradients. Three main parameters have an impact on the resolvability of bitumen depletion volumes and are varied through a suitable parameter space: well pair separation, depth to the well pairs, and survey grid sampling. The results include a resolvability matrix, which identifies reservoirs that could benefit from time-lapse gravity gradiometry monitoring. After 1.25 years of operation, during the rising phase, the resolvable maximum reservoir depth ranges between the surface and 230 m, considering a well pair separation between 80 and 200 m. After 5 years of production, during the spreading phase, the resolvability of depletion volumes around single well pairs is greatly compromised as the depletion volume is closer to the surface, which translates to a larger portion of the gravity signal. The modelled resolvability matrices were derived from visual inspection and spectral analysis of the gravity gradient signatures and can be used to assess the applicability of time-lapse gradiometry to monitor reservoir density changes. [ABSTRACT FROM AUTHOR]

Recently, steam assisted gravity drainage (SAGD) has been widely adopted in thermal recovery for heavy oil. However, challenges remain in SAGD development: the close distance between injector and producer makes it easy to cause steam breakthrough, which means lower thermal efficiency as well as higher investment. It is generally acknowledged that there is a liquid level existing between the injector and producer, a reasonable liquid level could prevent steam from being produced directly. The existence of liquid level generates a temperature difference between two wells, i.e., subcool. Subcool has generally been used to describe liquid level in practice and in many researches, yet it is inaccurate. In order to characterize the liquid level precisely, it is necessary to fully clarify the relationship among subcool, liquid level and pressure difference between injector and producer. By analyzing the features of subcool and pressure difference shown in SAGD experiments, it is found that the value of subcool may be not directly relevant with the distance between injector and producer, considering the huge difference between experiments and the measured data from actual oilfield. Correspondingly, liquid level is supposed to be treated as a dimensionless variable, to be specific, named as dimensionless liquid level, defined as liquid level divided by the distance between two wells. Afterwards, over 40 cases of CMG numerical simulations are run to investigate the liquid levels with different injector-producer distances and different subcools. Based on the analysis of simulation results, the dimensionless liquid level increases with subcool, while for a given subcool, dimensionless liquid level is inversely proportional to pressure difference between injector and producer. Accordingly, liquid level could be accurately controlled under a given subcool and pressure gradient, which is applicable and be of great significance for the SAGD operation on the field. [ABSTRACT FROM AUTHOR]

The oil sands industry in Canada is under increasing pressure to simultaneously reduce greenhouse gas (GHG) emissions and water consumption. As a consequence, new trade-offs are emerging that require an integrated analysis. This paper applies Process Integration (PI) tools to investigate opportunities to improve efficiencies in the steam assisted gravity drainage (SAGD) process. The goal of the paper is to design a distributed effluent treatment system to minimize cost and explore the economic-environmental trade-offs based on concepts of Process Integration. Different configurations of water treatment technologies and steam generation options in SAGD operations are assessed and cost, GHG emissions, water and energy consumption are compared across these configurations. The results of the study show that there are potential cost and electricity savings of up to 19.5% and 12% respectively in the water treatment system of SAGD operations relative to “typical” configurations. These results can help oil sands operators make informed decisions about investments in water treatment technologies for SAGD operations. [ABSTRACT FROM AUTHOR]

[Display omitted] • TIC and SVI can be used as additional performance indicators. • Poly-DADMAC dose and mixing time with softeners only were the most important factors. • 99.4 % particulate hardness removal and 38.1 mL/g SVI were obtained at optimal condition. • SFA results verified adsorption and bridging between polymers and particles. • Temperature could affect the removal mechanism by changing floc structure and component. Effective removal of colloidal impurities from steam-assisted gravity drainage (SAGD) produced water is essential for enhancing water recycling in industry. Response surface methodology (RSM) was employed to optimize the thermal softening-coagulation-flocculation-sedimentation process with softeners (Ca(OH) 2 , MgO and Na 2 CO 3), poly-DADMAC as coagulant, and cationic polyacrylamide (PAM) as flocculant, and assess the interaction effects of operational variables for sludge volume index (SVI) and the removal efficiency of turbidity (TSS), particulate hardness, silica, total organic carbon (TOC) and total inorganic carbon (TIC) in synthetic SAGD produced water. The optimal conditions at 0.93 desirability were 67 mg/L poly-DADMAC dose, 14 min mixing time with softeners only, 200 rpm coagulation speed, and 16 min flocculation time. At this condition, the predicted maximum removal of turbidity, TSS, particulate hardness, silica, TOC and TIC were 99.2 %, 99.1 %, 99.4 %, 27.0 %, 69.0 %, and 30.3 %, respectively, and the value of SVI was 38.1 mL/g. Our results indicated that poly-DADMAC dose and mixing time with softeners only were the most influential factors for the treatment process. Furthermore, the temperature effect on removal mechanisms was investigated at optimal conditions under room temperature and high temperature (80 °C). The results of floc characterization and surface force measurement indicated that temperature could facilitate the removal of colloidal impurities via forming larger and denser flocs and changing their surface composition. The results also provided confirmation that adsorption and subsequent bridging are the main removal mechanisms in the coagulation-flocculation process. This study illuminates the importance of the interactions among operational variables and provides in-depth insights into the mechanism for the removal of colloidal impurities under high temperature. [ABSTRACT FROM AUTHOR]

Steam-assisted gravity drainage (SAGD) is a primary commercial in-situ thermal recovery method for oil sands/bitumen in Alberta, Canada. Evidence of initial water mobility during the SAGD processes has been observed by previous studies, yet little research has been done on its effects on SAGD performance. In this study, initial water movement ahead of the steam chamber is investigated and its effects on the steam chamber development, as well as well production performance are quantified. Initial water mobility is firstly classified into two categories (low and high) based on the shapes of their steam chambers. Results show that initial water mobility can change the shape of steam chamber, pressure distribution in the reservoir and the steam condensate flow pattern along steam chamber edge. Cumulative oil production in nine years for the low initial water mobility scenario is 18.1% higher than that of the immobile initial water scenario due to the convective heat transfer induced by initial water flow ahead of the steam chamber. On the other hand, cumulative oil production in nine years of the high initial water scenario is 34.6% lower than that of immobile scenario. For the adjacent well pairs located in the same pad, compared to immobile initial water case, low initial water mobility case with the same injection pressure has the highest NPV, while high initial water mobility has a negative impact on SAGD performance. An injection pressure difference of only 200 kPa for the high initial water mobility case can reduce NPV by 40%. [ABSTRACT FROM AUTHOR]

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To assess the ecological impacts of two independent accidental bitumen releases from two steam assisted gravity drainage (SAGD) wells in the Athabasca oil sands region, a multiple lines of evidence (LOE) approach was developed. Following the release in 2010, action was taken to minimize environmental impact, including the selective removal of the most highly impacted vegetation and the use of oil socks to minimize possible runoff. An ecological risk assessment (ERA) was then conducted based on reported concentrations of bitumen related contaminants in soil, vegetation, and water. Results of biological assessments conducted at the site were also included in the risk characterization. Overall, the conclusion of the ERA was that the likelihood of long-term adverse health effects to ecological receptors in the area was negligible. To provide evidence for this conclusion, a small mammal sampling plan targeting Southern red-back voles ( Myodes gapperi ) was carried out at two sites and two relevant reference areas. Voles were readily collected at all locations and no statistically significant differences in morphometric measurements (i.e., body mass, length, foot length, and adjusted liver weight) were found between animals collected from impact zones of varying levels of coverage. Additionally, no trends corresponding with bitumen coverage were observed with respect to metal body burden in voles for metals that were previously identified in the source bitumen. Hepatic ethoxyresorufin-O-deethylase (EROD) activity was statistically significantly elevated in voles collected from the high impact zones of sites compared to those collected from the reference areas, a finding that is indicative of continued exposure to contaminants. However, this increase in EROD was not correlated with any observable adverse population-wide biological outcomes. Therefore the biological sampling program supported the conclusion of the initial ERA and supported the hypothesis of no significant long-term population-wide ecological impact of the accidental bitumen releases. [ABSTRACT FROM AUTHOR]

In this study, a combined system for syngas, bitumen, hydrogen and electricity production is developed and analyzed. The proposed system consists of steam assisted gravity drainage (SAGD), underground coal gasification (UCG), solid oxide fuel cell (SOFC), integrated gasification combined cycle (IGCC) and an electrolyser. The present system offers significant practical advantages for the regions, containing both coal and oil reserves such as Alberta region. Coal, as an alternative to natural gas for generating steam, is gasified using high temperature and pressurized steam in underground cavity. The produced syngas is utilized in both IGCC and SOFC systems. By using the excess steam in IGCC, SAGD process is run, and bitumen is extracted as in-situ extraction. In addition, a part of generated power is used in an electrolyser to produce hydrogen. The present system is analyzed in terms of energy and exergy methodologies to assess the performance of the cycles. Additionally, the effects of various system parameters, such as ambient temperature and pressure, syngas temperature, coal and syngas lower heating values, air and steam injection rates on energy and exergy efficiencies of the subsystems and overall system are evaluated. The energy and exergy efficiencies of the overall system are calculated as 19.6% and 17.3%, respectively. [ABSTRACT FROM AUTHOR]

Steam assisted gravity drainage (SAGD) has become a preferred in-situ recovery technology for oil sands and bitumen deposits in Canada. In some production history matching studies, the initial water was found to be mobile in SGAD projects, which could cause high steam loss, difficult pressure control, high steam oil ratio (SOR), etc. It is crucial to determine the initial water mobility in order to optimize SAGD performance. In this paper, a novel method is presented to effectively determine the mobility of initial water existing as the continuous wetting phase in the bitumen reservoirs. More specifically, wax was used as the oil phase, for the first time, to simulate the immobile oil phase in bitumen reservoirs and oil sands. Experimental results indicated that the interstitial water could still flow when the water saturation was as low as 5% in the simulated bitumen-water system. A triangular tube bundle model was constructed and tuned to match the experimental results. The model was used to simulate the water relative permeability curves at different initial water saturations. A correlation of the initial water mobility with the initial water saturations was developed through data analysis. The impact of initial water movement on SAGD operations was illustrated using an analytical approach, and the associated energy loss was calculated. The results showed that the initial water mobility can lead to severe energy loss. [ABSTRACT FROM AUTHOR]

The application of molten carbonate fuel cell (MCFC) technology for carbon capture at a thermal in situ oil sands facility has been studied. A steam assisted gravity drainage (SAGD) facility with once-through steam generator (OTSG) was used as a base case. Engineering modelling was conducted to compare the base case with no carbon capture, and with carbon capture from an OTSG facility using MCFC or amine-based carbon capture. The results indicate that MCFC has the potential to significantly reduce the carbon capture cost at a SAGD facility and to export low GHG intensity electric power. For a 33,000 barrels of oil per day (or 99,000 barrels of steam per day) production facility, a 76 MW sized MCFC would be required to capture 90% of CO 2 from the OTSG. Of the 76 MW power from MCFC, approximately 48 MW can be exported. If reliably produced, excess power generation may provide CO 2 credits by offsetting Alberta grid electricity, possibly leading to a negative carbon footprint in bitumen production. Excess power would also provide a revenue stream to cover some of the cost of capture. The carbon capture cost of MCFC would be about 30% of that for amine-based chemical solvent process. [ABSTRACT FROM AUTHOR]

In oil sands reservoirs, it is difficult to predict the production reliably because a steam chamber continues to expand with time and the affected area keeps changing. This article proposes a new approach for history matching and uncertainty analysis in oil sands reservoirs. The first step is to set an area affected by the expansion of the steam chamber. Then some features are extracted and plotted in metric space using 2D discrete Fourier transform and principal component analysis. Several realizations are selected based on the same interval sampling and ranked with similar levels in production curve. The sampling weights are assigned proportional to the rankings and one realization is selected accordingly. A flow simulation performs the nearest point (realization) around the selected one in metric space. The most dissimilar realization is replaced in the candidates. The previous step is repeated until the objective function meets a stop criterion. In the result of uncertainty analysis, it could lead to a fast convergence and preserve geological reality. The mean facies map of the candidates generates successfully the position of the shale barrier in the reference field. [ABSTRACT FROM PUBLISHER]

Uncertainty in oil sands reservoirs can be quantified by generating multiple realizations using geostatistical methods. However, it requires huge computing time to simulate all of the realizations. This article proposes a new approach for features modeling of oil sands reservoirs in metric space. As the first step, an area affected by the expansion of a steam chamber is set and converted to the polar coordinate system. The converted area is expressed as an image matrix consisting of 0 or 1 value. Then the matrix is transformed using two-dimensional discrete Fourier transform. Key features in the front columns and rows of the transformed matrix are extracted. These features in metric space are plotted using principal component analysis. Self-organizing map algorithm is used to select representative models of realizations for performing full flow simulations. In the result of grouping, each cluster group distributes separately in metric space according to reservoir productivity, but there are mixes of a small portion among the adjacent groups due to similar productivity. [ABSTRACT FROM PUBLISHER]

Abstract: Interstitial water in a water-wet bitumen reservoir can form a continuous water network, which allows reservoir water to flow throughout the reservoir. A primary objective of the paper was to develop an experimental method to measure the water effective permeability of the continuous water network in an unconventional oil–water system. In experiments, semi-permeable membranes were installed at the production end of sandpacks to create a stationary oil phase condition. Experimental results showed that the water phase could flow under low permeability at initial water saturations. A cylindrical capillary tube model was developed to analyze experimental results and it showed that different wetting film thicknesses inside a porous medium could alter the overall effective permeability under the same initial water saturation. In the case study, different reservoir simulation operations were performed to compare influences of initial water movement. It was concluded that, under a small amount of initial water movement across the boundary, the pressure profiles and flow patterns of reservoir water changed. [Copyright &y& Elsevier]

Abstract: In order to realize the effective development of buried hill light oil reservoirs, mid-deep massive heavy oil reservoirs with interbeds, and ultra-deep massive heavy oil reservoirs in the Liaohe Oilfield, three tridimensional development models are established: superposition of horizontal wells in multi-intervals and multi-layers, steam assisted plane displacement (vertical wells) with combination of vertical gravity drainage (horizontal wells), and steam assisted liquor drainage by two superposed horizontal wells and production by vertical wells. The development mechanisms for these three tridimensional development models have been studied by field test, physical simulation and numerical simulation. The tridimensional development mechanisms of buried hill light oil reservoirs are uniform compaction action, vertical gravity action and joint supply action. The tridimensional development mechanisms of mid-deep massive heavy oil reservoir with interbeds are gravity drainage and steam flooding, and the tridimensional development mechanisms of ultra-deep massive heavy oil reservoir are gravity water drainage, reduction of heat losses and enhancement of production injection ratio. The field tests in the light oil reservoir of the Xinggu buried hill, mid-deep massive heavy oil reservoir in Xing VI oil layer of Block Du 84 and ultra-deep massive heavy oil reservoir of Block Wa 59 in the Liaohe Oilfield showed that tridimensional development can significantly improve crude oil production, and realize efficient development of oilfield. [Copyright &y& Elsevier]

Abstract: The vapour–liquid phase behaviour of steam–solvent (light hydrocarbon) systems used in an oil sands recovery process called steam assisted gravity drainage (SAGD) is examined. Analysis shows that condensation occurs over a temperature range and that a concentration gradient exists between the liquid and vapour phases. In a large range of solvent concentrations, water condenses first from the vapour phase. Solvent only condenses first from the vapour phase at extremely high solvent volume fractions. Due to water condensing first at most concentrations, the ability of the solvent to directly contact the bitumen in the reservoir depends on the orientation of the vapour–liquid interface and the relative position in the vapour chamber. Addition of solvent into a mature SAGD operation can also cause a temporary suppression of the steam–oil ratio (SOR) due to the change in the temperature at the vapour–liquid interface. This effect must be taken into account in interpreting experimental or simulation results. The addition of solvent not only changes the temperature but also decreases the heat of condensation of the mixture. As the concentration of solvent changes, the SOR is also expected to change. [Copyright &y& Elsevier]

Steam Assisted Gravity Drainage (SAGD) is a typical thermal recovery process consisting of an upper horizontal injector and a lower horizontal producer, which heats and removes bitumen from oil sands deposits by steam. Serious research has been conducted on data-driven models to analyze the cumulative production performance of the SAGD process, and one of the most common machine learning methods utilized is the Artificial Neural Network (ANN). It is important to test other machine learning methods like Extreme Gradient Boosting (XGBoost) and Light Gradient Boosting Machine (LightGBM) in different conditions of data samples. In this paper, a series of SAGD models based on typical oil sands reservoir properties and operational conditions were constructed. Three different data groups were simulated by the Computer Modelling Group (CMG) thermal software STARS. Three different machine learning methods, including ANN, XGBoost, and LightGBM were constructed to calibrate a relationship between the input parameters and the output parameters in the different simulated data groups. A series of final models were tested and compared. The conclusion shows that data-driven training improves as the number and randomness of the data samples increase, and the LightGBM has the best prediction performance with such data samples. The ANN model may be the best choice with data samples of the worst randomness. • A series of data-driven models were developed to predict SAGD production performance. • Three different machine learning methods were compared with different data groups. • Gradient Boosting Decision Tree methods are better with a better sample data condition. • The Artificial Neural Network is better with a worse sample data condition. [ABSTRACT FROM AUTHOR]

Steam-assisted gravity drainage (SAGD) has been widely proven to enhance heavy oil recovery effectively. However, the performance evaluation of SAGD in heavy oil reservoirs usually involves time-consuming and tedious static and dynamic numerical simulations, which is not suitable for practical decision-making and prediction. As a reliable alternative modeling tool, the deep learning-based model has great potential for comprehensive data analysis and system prediction of machine learning methods. Still, it has not been widely used in SAGD development planning. In this paper, a recurrent neural network model is applied to the prediction of SAGD production information. A large number of simulation results are collected using CMG software to build a training database, which includes static parameters describing various characteristics of the reservoir and dynamic parameters for production control. The deep learning-based model is divided into two parts. One part is responsible for predicting the thermal communication in the preheating stage, and the other part is responsible for predicting the production information in the production stage, using the principal component analysis method to reduce the dimension of the input vector, limiting the overfitting and improving the quality of the prediction. Besides, an intelligent history matching technology for oilfield SAGD production is proposed. The model is designed to be controlled by a user-friendly graphical interface for user convenience and can be directly integrated into reservoir management programs. This research highlights the enormous potential of replacing traditional modeling tools with neural network models for decision-making and predicting SAGD production projects in oilfields. [ABSTRACT FROM AUTHOR]

Although there are many studies regarding the effect of temperature on relative permeability, there is no consensus on this issue. Here we examine the role of oil/water viscosity ratio in making the measured oil/water relative permeability dependent on temperature. Two-phase oil/water relative permeability was carefully measured over a wide range of temperature between 23 °C and 210 °C using a poly-alpha-olefin (PAO) oil and deionized water in a clean unconsolidated sand-pack at confining pressure of 800 psi. A sophisticated experimental setup that is capable of measuring the pressure drop and monitoring the temperature in four different length segments of the sand-pack was used. Both the Johnson, Bossler and Neumann (JBN) method and the history match approach were employed to obtain the relative permeability from the results of isothermal oil displacement tests. Furthermore, high-temperature and high-pressure interfacial tension (IFT) and contact angle measurements were also carried out. The results show that the two-phase oil/water relative permeability, in this ultra-clean system, is practically insensitive to the temperature, even though the oil/water viscosity ratio changes by two orders of magnitude. The slight variation in oil endpoint relative permeability and irreducible water saturation, especially at ambient condition, was attributed to the uncertainty in the oil viscosity measurement and reproducibility of the sand packing procedure. The IFT of this system declined from 41.1 mN/m at 23.5 °C to 20.9 mN/m at 185.2 °C and contact angle decreased from 80.7° at 23.5 °C to 56.9° at 150 °C. Changes of this level do not significantly affect the oil displacement behavior. [ABSTRACT FROM AUTHOR]

In steam assisted gravity drainage (SAGD) operations, skim oil recycled to a free water knockout (FWKO) often results in poor water quality and rag formation at the oil/water interface. To improve water quality and demulsification efficiency in the presence of skim oil recycle, it is necessary to understand the status of oil and solids in the produced water throughout the process. In this paper, the effect of skim oil on the water/oil separation in SAGD operations was studied. Dynamic optical fluid imaging (DOFI) technology was used to characterize oil and solids concentrations, oil droplet sizes, and the associated size distributions in the produced water collected from various vessels in a SAGD process. The DOFI analyses show that skim oil recycle caused more oil and solids to be sent to the FWKO, treater and induced gas flotation (IGF) outlet waters and finally to oil removal filters (ORF). The increased oil in water led to more oil droplets, especially more numerous small oil droplets remaining in the produced water. These small oil droplets are more challenging to remove than larger oil droplets, resulting in deteriorated water quality. Skim oil recycle decreased the oil removal efficiency of the IGF vessel and increased fouling of ORF filters by oil and solids. Fourier transform infrared spectroscopy analysis of the solids collected from the produced water in the presence of skim oil recycle indicated that the solids are bitumen-coated fine quartz and clays. Demulsification studies show that application of dual reverse emulsion breakers could help improve water quality and alleviate the negative effects due to the solids from skim oil addition. • Water quality deteriorates and a rag layer is formed at the oil/water interface when skim oil is recycled. • Skim oil recycle leads to more solids and small oil droplets left in the produced water throughout the treating system. • The oil removal efficiency of treating vessels decreases with skim oil recycle. • Application of dual reverse emulsion breakers improved water quality and reduced negative effects from skim oil addition. [ABSTRACT FROM AUTHOR]

• Uncertainty quantification of factor of safety (FoS) of caprock in steam-assisted gravity drainage. • Proper orthogonal decomposition combined with polynomial chaos expansion (PCE) technique. • Different scalar measures for FoS of the caprock layer. • PCE models can propagate uncertainty in permeability and well bottom hole pressure to the FoS. The factor of safety (FoS) is a measure of the operational safety of a reservoir and is defined as the ratio of the yield strength to the applied effective stress. In the steam assisted gravity drainage (SAGD) process, maintaining the caprock FoS within the prescribed limits during the operation is crucial in adhering to safe operational standards. Deformations associated with the development of the steam chamber in the reservoir affect the FoS of the caprock significantly. With a limited number of well-logs, precise quantification of heterogeneity in petrophysical and geomechanical parameters is a challenge in coupled reservoir-geomechanics modelling; this, along with nonlinearity in the process dynamics, gives rise to non-Gaussian uncertainties in the pore pressure/temperature, which poses severe challenges in reservoir control and optimization. The large scale nature of the reservoir imposes computational complexity in uncertainty quantification through first-principles modelling; hence, a data-driven methodology using the results from first-principles simulations is valuable. In this work, a data-driven polynomial chaos expansion (PCE)-based proxy model is developed from sequentially coupled reservoir-geomechanics simulation. Proper orthogonal decomposition (POD) combined with the PCE yields a proxy model which can provide a quick and accurate estimation of caprock FoS along with quantifying its uncertainty. [ABSTRACT FROM AUTHOR]

• A comprehensive techno-economic analysis of PCLC technology has been performed. • The main contribution regarding CAPEX corresponded to the rotating equipment. • Natural gas price and CAPEX largely affected the profitability of the CLC process. • Operating at pressurized conditions was beneficial from an economic point of view. • PCLC can be a competitive CO 2 capture option for its use in SAGD facilities. A great effort is still pending in terms of thorough bottom-up economic assessments in the particular case of Chemical Looping Combustion (CLC) and Pressurized Chemical Looping Combustion (PCLC) processes. This work tries to reduce this knowledge gap through a comprehensive techno-economic analysis of PCLC technology focused on the replacement of a Once-through Steam Generator (OTSG) for the production of steam in a Steam Assisted Gravity Drainage (SAGD) facility in Alberta (Canada) by a PCLC system that burns natural gas using ilmenite as oxygen carrier. The evaluation of capital expenditure (CAPEX) for the different CLC cases analyzed revealed that the main contribution to costs stemmed from the rotating equipment. The economic performance of the CLC processes was evaluated through the Levelized Cost of Steam (LCOS) and the cost of CO 2 captured. These parameters ranged between 30.45 and 39.93 CAD/t of steam (23.61–30.95 USD/t) and between 44.39 and 107.05 CAD/t of CO 2 (34.41–82.98 USD/t), respectively. In the particular case of the CLC unit that operated at atmospheric pressure, the results were 34.92 CAD/t of steam (27.07 USD/t) and 75.46 CAD/t of CO 2 (58.50 USD/t), which highlighted the economic benefits resulting from the use of CLC technology under pressurized conditions. Finally, comparing the economic results obtained in this framework with those found in the literature using other Carbon Capture and Storage (CCS) technologies, it can be concluded that PCLC technology has the potential to be a competitive CO 2 capture option in the future for use in industrial SAGD facilities. [ABSTRACT FROM AUTHOR]