Steam Assisted Gravity Drainage Process Research Articles

Technology Focus: Cementing and Zonal Isolation (May 2024)

This past year’s Cementing and Zonal Isolation papers indicated that our industry continues to maintain high levels of innovation and optimization. We saw a healthy mix of both academic and field-specific content. The evident collaboration between operators and service providers continues to propel technical developments at rates otherwise not possible. Geopolymer cementing-systems-development took center stage again, with 11% of the published papers covering this topic, with the ultimate goal of reducing the CO2 footprint of wellbore-sealing materials. Last year’s column described the geopolymer-systems-development timeline and how we had yet to have any case studies published. This year, I invite you to read a paper highlighting the first published field implementation of geopolymer in primary casing cementing, paper OTC 32218. This paper describes techniques that ensure that geopolymer systems are suitable for the downhole application, compatible with existing pumping equipment, and scalable to current operations. Several other papers published this past year describe these specific geopolymer topics in detail. Academic paper SPE 213763 describes the development, testing, and results of a novel resin-cement blend. This innovation stands out because, among other reasons, it presents improved bonding of cement to the casing, which enhances wellbore integrity over the well life cycle. Such materials can provide long-term isolation, especially in environments where conventional cement does not always endure mechanical stresses, vibrations, or shocks. Paper SPE 214768 is a robust case study on the implementation of foamed cements in shallow thermal well applications to mitigate gas migration. This paper showcases best practices for generating solutions to challenging downhole conditions from well design, drilling, and cementing perspectives. While the discussed geology and steam-assisted gravity drainage processes are largely unique to Canadian oil sands operations, I recommend this as an informative read for any operator or service provider facing similar downhole challenges. I hope you gain valuable insight from these selections and am looking forward to what the next year of publications brings to the cementing and zonal isolation space. Some excellent case studies and technological developments are also listed as additional reading. Recommended additional reading at OnePetro: www.onepetro.org. SPE 217797 Cementing: The Good, the Bad, and the Isolated—Techniques To Measure Cement Quality and Its Impact on Well Performance by Kyle Haustveit, Devon Energy, et al. SPE 216911Well Life Extension Through CasingCorrosion Control by A. Yugay, ADNOC, et al. SPE 214538 Using Ultrasonic Flexural Measurements To Validate Casing Standoff Simulations: A Kuwait Case Study by Ahmed Nour, Kuwait Oil Company, et al. SPE 213099 Biomineralization: Surface Injection Eliminates Bradenhead Pressure by Dwight Randy Hiebert, BioSqueeze, et al.

A new pressure control scheme on steam‐assisted gravity drainage for heavy oil production

AbstractAs one the most important recovery mechanisms of steam‐assisted gravity drainage (SAGD), gravity drainage is largely dependent on the inclination angle of the steam chamber edge. The existence of solution‐gas causes an ellipsoid‐shaped chamber that has small inclination angle at the bottom, which leads to inefficient gravity drainage and slows down oil production. To address this problem, this study proposes a new scheme, variable‐pressure SAGD (VP‐SAGD). It is basically a SAGD process, at certain stages of which pressure surge is induced by controlling the operating conditions so that the shape of steam chamber can be altered. This leads to a larger slip angle in the steam chamber at the bottom and more efficient heat transport between hot steam and crude oil. Results show that VP‐SAGD is able to increase oil recovery by up to 20% and decrease cumulative steam–oil ratio (cSOR) by up to 7%. Its special oil extraction mechanisms include swabbing effect, enlarged inclination angle of steam chamber boundary at the bottom, and enhanced heat transfer. Particularly, the inclination angle is increased by up to 40%. In addition, a lower producer bottom‐hole pressure (BHP) during pressure drawdown leads to a better production incremental in later stages. The optimal timing for pressure surge is the middle stage of steam chamber growth. The lower the producer BHP decrease, the better the yield increase. Moreover, The VP‐SAGD strategy works better in heavy oil reservoirs with a permeability of k = 0.5–10 Darcy or solution gas content of greater than 2%.

Resourceful and harmless treatment of the steam-assisted gravity drainage produced fluid

The steam-assisted gravity drainage (SAGD) process is an effective technology for heavy crude oil extraction. SAGD produced fluid (including oil, water, and sludge) that has strong stability and difficult separation characteristics. It is very necessary to thoroughly separate SAGD produced fluid, as it can lead to environmental pollution and resource waste. In this study, a combined process of thermochemical treatment and electrocoagulation was proposed to deal with SAGD produced fluid. The influence of such parameters as type and structure of surfactants, temperature, stirring rate, and current density were examined on the separation efficiency of SAGD produced fluid. The results indicated that the oil recovery rate was 99%, with the oil and suspended solids content (4.4 and 0.58 mg/L, respectively) in the water meeting the reinjection standard (oil content <15 mg/L, suspended solids <3 mg/L) and the oil content in the sludge (1 wt%) attained the solid waste disposal standard (<2 wt%). The combined separation process of SAGD produced fluid allowed the obtaining of qualified oil, sludge, and water, with oily sludge and waste water simultaneously eliminated. Therefore, this process achieved oil and water resource utilization, as well as harmless sludge treatment, which would achieve great economic benefits and application prospects in the oil field.

A Simple Normalized Analytical Model for Oil Production of SAGD Process and Its Applications in Athabasca Oil Sands

Summary Since the late 1980s, when the Alberta Oil Sands Technology and Research Authority Underground Test Facility project first demonstrated the feasibility of the steam-assisted gravity drainage (SAGD) technology, many commercial SAGD projects were brought online in Western Canada. Now, many of these projects have late-life SAGD wells approaching their ultimate SAGD recovery factors. Although these projects have demonstrated highly variable production performance, there is an opportunity to use the industry production data to find what they have in common and develop a normalized SAGD model. For this paper, we collected oil production history from several leading SAGD projects with late-life production in the Athabasca oil sands area and confirmed the three stages in an SAGD project lifespan: chamber rising, chamber spreading, and chamber falling stages. By normalizing the field data, all SAGD projects converged to one type curve, regardless of reservoir quality and operating conditions. Based on this observation, a new simple normalized model is derived to model the bitumen production in a typical SAGD process for Athabasca oil sands. The new model bridges the gap between the existing SAGD analytical model and conventional decline analysis and provides oil production forecasts based on the inputs for the five-component recovery factor method defined in the Canadian Oil and Gas Evaluation Handbook(Society of Petroleum Evaluation Engineers 2018). The model has been applied to one of the thermal projects to history match the field production. By running a Monte Carlo simulation, this model further demonstrates its capability to capture the uncertainty of the production forecast for the project at different stages of SAGD operation. In addition, by properly modifying the type curve of the analytical model, a similar workflow can be used to model cases with special reservoir quality or different operational limitations.

A New Method to Reduce Shale Barrier Effect on SAGD Process: Experimental and Numerical Simulation Studies using Laboratory-Scale Model

Summary Shale barrier has been widely reported in many steam-assisted gravity drainage (SAGD) projects. For an SAGD project, the properties and distribution of shale barrier can significantly impede the vertical expansion and lateral spread of steam chamber. Currently, although some literature has discussed the shale barrier effect from different perspectives, a systematic investigation combining the scaled physical and numerical simulations is still lacking. Simultaneously, how to reduce the shale barrier effect is also challenging. In this study, aiming at the Long Lake oilsands resources, combining the methods of 3D experiment and numerical simulation, a new method based on a top horizontal injection well is proposed to reduce the impact of shale barrier on the SAGD process. First, based on a dimensionless scaling criterion of gravity-drainage process, we conducted two 3D gravity-drainage experiments (base case and improved case) to explore the effect of shale barrier and the performance of top injection well on SAGD production. During experiments, to improve the similarity between the laboratory 3D model and the field prototype, a new wellbore model and a physical simulation method of shale barrier are proposed. The location of the shale barrier is placed above the steam injection well, and the top injection well is set above the shale barrier. For an improved case, once the steam chamber front reaches the horizontal edge of the shale barrier, the top injection well can be activated as a steam injection well to replace the previous steam injection well in the SAGD well pair. From the experimental observation, the effect of the top injection well is evaluated. Subsequently, a set of numerical simulation runs are performed to match the experimental measurements. Therefore, from this laboratory-scale simulation model, the effect of shale barrier size is discussed, and the switch time of the top injection well is also optimized to maximize the recovery process. Experimental results indicate that a top injection well-based oil drainage mode can effectively unlock the heavy crude oil above shale barrier and improve the entire SAGD production. Compared with a basic SAGD case, the top injection well can increase the final oil recovery factor by about 8%. Simultaneously, through a mass conservation law, it is calculated that the unlocking angle of remaining oil reserve above the shale barrier is about 6°. The angle can be used to effectively evaluate the recoverable oil reserve after the SAGD process for the heavy oil reservoir with a shale barrier. The simulation results of our laboratory-scale numerical simulation model are in good agreement with the experimental observation. The optimized switch time of the top injection well is the end of the second lateral expansion stage. This paper proposes a new oil drainage mode that can effectively reduce the shale barrier effect on SAGD production and thus improve the recovery performance of heavy oil reservoirs.

Development of a heat-penetration criterion to characterize steam chamber growth and propagation dynamics during a steam-assisted gravity drainage (SAGD) process

Steam chamber growth and propagation dynamics dictates the success of a steam-assisted gravity drainage (SAGD) process, which is an enhanced oil recovery (EOR) method for effectively and efficiently exploiting the enormous heavy oil and bitumen reserves. To set the baseline, this work is focused on the SAGD process with pure steam. After numerous trials and errors, a heat-penetration criterion has been developed and integrated into a reservoir simulator for the first time to characterize steam chamber growth and propagation dynamics conditioned to the production profiles during a steam-assisted gravity drainage process. More specifically, based on the heat transfer principle, a pore-scale heat-penetration criterion has been developed with respect to both heat conduction and convection for calibrating the temperature distributions ahead of the steam chamber interface (SCI). Subsequently, such a heat-penetration criterion has been upscaled to a grid-scale for its integration with a commercial reservoir simulator (i.e., CMG STARS), allowing us to pragmatically and accurately quantify the dynamic temperature field during a steam-assisted gravity drainage process. Furthermore, three sets of multiphase relative permeabilities are employed to evaluate comprehensive impacts of the thermally sensitive co/counter-current flows. Finally, such a heat-penetration criterion has been verified by reproducing the experimentally measured steam chamber during a steam-assisted gravity drainage process from a large-scale 3D physical model. With such an integrated method, good agreements between the measured and simulated data including production profiles and temperature distributions have been found, whereas the dynamics of production profiles and corresponding steam chamber propagations cannot be well reproduced solely with a commercial reservoir simulator. Sensitivity analysis has been performed to examine the effects of thermal-sensitive properties, steam chamber configuration, boundary, multiphase flow behaviour (e.g., co-current and counter-current flow), and gridblock dimension. In practice, the newly developed heat-penetration criterion can be seamlessly integrated with a commercial reservoir simulator. Such an integrated method can significantly reduce the model complexities and uncertainties, providing a simple and convenient way to dynamically and accurately characterize the steam chamber growth and propagation dynamics within a unified, consistent, and efficient framework.

Sequentially Coupled Thermal-Hydraulic-Mechanical Simulation for Geomechanical Assessments of Caprock Integrity in SAGD

Oil sand reservoirs and caprock undergo deformations triggered by pore pressure increases and thermal induced stresses during the steam-assisted-gravity-drainage (SAGD) processes. Geomechanical assessments are mandated by energy regulators to evaluate the caprock integrity and ensure the safe SAGD operations. Commercial reservoir simulation packages started to incorporate geomechanical effects when predicting flow response; however, these geomechanical modules are not able to correctly model the plastic deformations caused by thermal-hydraulic-mechanical (THM) interactions, which has a first order effect on predicting steam chamber propagation and evaluating caprock integrity.&#x0D; An integrated coupled THM modeling methodology is proposed here to improve the modeling of reservoir deformations and caprock integrity in a heterogeneous oil sand reservoir with interbedded shale barriers. The pressure and temperature front are found to propagate at different speed and that dominate the elastic and plastic deformations caused by changes of shear and mean effective stress. Therefore, four stages are divided in the SAGD process that can be interpretations of changes in stress paths including buildup of pore pressure, generation and dissipation of thermal induced stresses. The response surfaces of minimum factor of safety (FOS) are introduced and computed to provide a conservative estimate for caprock integrity during SAGD of a heterogeneous reservoir with multiple layers of caprocks in Athabasca oil sands. &#x0D;

Physical and Numerical Simulations of Steam Drive and Gravity Drainage Using the Confined Bottom Oil–Water Transition Zone to Develop Super Heavy Oil

The existence of the bottom oil–water transition zone (BTZ) greatly impairs the performance of the conventional steam-assisted gravity drainage (SAGD) process and its mitigation measures are very limited. In order to accelerate oil production and decrease the Steam-to-Oil Ratio (SOR), a promising technology involving a steam drive and gravity drainage (SDGD) process by placing dual-horizontal wells with high permeability in the BTZ was systematically studied. This paper conducted two-dimensional (2D) and three-dimensional (3D) physical simulations as well as 2D numerical simulation of the SDGD process to explore the mechanism, potential, and application conditions. The research findings indicate that the SDGD process in the BTZ with enhanced permeability through dilation stimulation can achieve higher oil production and lower SOR than the SAGD process. This process fully leverages the advantage of the BTZ to quickly establish inter-well thermal and hydraulic connectivity. The steam chamber first forms around the injector and then spreads towards the producer. By exerting the horizontal displacement of drained oil, oil production rapidly ramps up and keeps at a high rate under the synergistic effect of steam drive and gravity drainage. These insights enhance our understanding of the mechanism, potential, and application conditions of the SDGD process in the confined BTZ to develop super heavy oil or oil sands.

Simulation Calculation and Analysis of Connate Water Convection on Steam Chamber Expansion in Steam-Assisted Gravity-Drainage Process

Steam-assisted-gravity-drainage (SAGD) is a widely employed method to enhance heavy oil production and efficiency, and the key to ensuring its steady operation is the maintenance of a steam chamber. Heat conduction and convection of steam to connate water are essential factors in the heat transfer process. In this paper, we developed a novel analytical model to investigate the heat transfer process on the boundary of the steam chamber, driven by the pressure difference between the injected steam and the original reservoir. Both conduction and convection are considered in this new model, and the calculated results are in good agreement with the simulated data by using CMG-STARS. After model validation, the effects of physical properties and operating conditions (relative permeability, initial water saturation, and steam temperature) on the heat transfer process are investigated. The results reveal that connate water saturation plays a large role than the steam temperature in conductive heat flux; low saturation leads to more efficient crude oil exploitation. This work provides new insights into the recovery mechanisms of a SAGD process.

Feature engineering process on well log data for machine learning-based SAGD performance prediction

The conventional numerical simulation requires a reliable three-dimensional reservoir model to evaluate the steam-assisted gravity drainage (SAGD) performance, but it may be time-consuming and need a significant amount of static data. This study aims to develop a machine learning (ML) model that predicts the SAGD performance based on well log data from a near single well. Although the ML model is useful in capturing underlying non-linear relationships between input features and target features, it requires a large number of training data. However, the number of data is usually small in commercial fields, limiting the availability of all log responses as input features to consider reservoir heterogeneity. In case of using small dataset, the overfitting can occur with an excessive number of model parameters. Therefore, this study introduces a feature engineering process to extract and select key features from well log data to alleviate the overfitting problem.In this study, the feature engineering process was optimized by sensitivity analysis on feature extraction and feature selection methods. For data preparation, the 63 SAGD well pairs and their matched logged wells were screened from the six commercial oil sand fields in Alberta, Canada. The SAGD process mechanism and petrophysics were considered to build data screening criteria. Each depth of the log data was categorized into pay-zone or shale barrier. For feature extraction, sampling intervals were placed on log data. This calculates the net pay thickness, averaged gamma ray, deep resistivity, and neutron porosity logs in the pay-zone. In addition, the elevation of two shale barriers and the distance between the SAGD well and logged well are extracted. Sensitivity analysis of the sampling interval length was conducted to determine the optimal conditions considering heterogeneity and feature reduction. For the feature selection, various combinations of the extracted features were used to examine their inherent meaning for predicting the SAGD performance. The multi-layer perceptron model was trained based on various selected features to predict the SAGD performance indicators of a seven-year operation. The optimal sampling interval length was determined as 10m and the combination of gamma ray, deep resistivity, shale barrier elevation, and the distance information was selected as key input features. The model showed reasonable prediction results for SAGD productivity and economic indicator with R2 of 0.67 and 0.72, respectively.

Optimization of process parameters for acid fracturing assisted herringbone well SAGD

Zhong18 wellblock of Fengcheng oilfield developed with low permeability interlayer and had strong heterogeneity, which caused steam chamber of conventional steam assisted gravity drainage (SAGD) process cannot extend lengthwise continuously and serious steam heat loss. To address this problem, a method of acid fracturing assisted SAGD process is proposed to enhance the oil drainage and improve oil recovery. Based on the herringbone well SAGD being used in Zhong18 wellblock, the orthogonal experimental design and oil reservoir numerical simulation are used to determine the significance level and fracture parameter optimization of the acid fracturing process. The priority of optimization sequence is: fracture permeability, fracture width, fracture half-length, fracture spacing. The optimal parameters are as: 3D fracture permeability, 2.8 mm fracture width, 80 m fracture half-length and 80 m fracture spacing. A 10-year simulation using optimized parameters can improve the recovery by 9.2 % compared with the conventional SAGD process. The result proved that acid fracturing assisted herringbone well SAGD process can effectively penetrate the low permeability interlayer, expand the sweep range of steam chamber, and improve the oil recovery degree of the reservoir.

Water Separation Performance in Bitumen Recovery from Athabasca Oil Sands: Implementation of Separation Efficiency Index

The oil (diluted bitumen)–water separation efficiency at steam-assisted gravity drainage (SAGD) process conditions has been evaluated in a laboratory environment by using a custom-built batch gravity setup, using SAGD field fluids and commercial gas condensate as a diluent. The key parameters and conditions investigated are solvent amount, shear conditions, water-to-oil ratio, and the presence and wettability of fine solids. The results demonstrate the complexity of the oil–water separation process, affected by the dependence of the investigated parameters from one another. A new quantification approach is introduced to facilitate the oil–water separation efficiency evaluation, based on the proposed descriptor, referred to as a separation efficiency index (SEI). Defined as the average of the residual water-in-oil and oil-in-water indices, SEI ranges from 0 to 1, where 1 represents a “perfect” (complete) separation and 0 corresponds to a complete emulsification. The SEI allows one to describe the separation efficiency throughout the entire separation vessel volume, using discrete vertical water distribution profiles, and represents the separation efficiency with a single number, regardless of the experimental approach taken. The findings show that in the range of solvent concentrations of 30 vol % or lower, the mixing speed affects the separation performance and becomes predominant at the relatively low solvent concentrations of 10 and 20 vol %. The amount of solvent added becomes predominant in the oil–water separation process and overcomes all other effects in the highest solvent addition (40 and 50 vol %) range. The presence of water-wet solids improves the separation performance, while the presence of oil-wet solids impedes the oil–water separation. The results presented in this study, in particular the proposed SEI, are important for improving the oil–water separation efficiency and can be used to develop operational envelopes and new solvent injection strategies, in terms of location, amount, and stages, further improving the quality of the oil product obtained in SAGD.

Steam allocation for SAGD: Multi-pad multi-criteria short and long-term real-time performance management

Optimizing steam allocation is critical for long-term performance goals in Steam-Assisted Gravity Drainage (SAGD) recovery. The steam supply mainly contributes to the economics, steam chamber conformance, greenhouse gas emissions, and ultimate bitumen recovery. Therefore, SAGD real-time optimization (RTO) must balance steam chamber development and economics to achieve long-term goals. However, in RTO, general-purpose optimization algorithms decide based on short-term responses, unlike long-term optimization processes. Using economic Key Performance Indicators (KPI) such as Net Present Value (NPV) in a single objective, the RTO determines the smallest amount of steam that results in the highest economic returns. Injecting a small amount of steam reduces steam chamber heat loss, growth, and long-term ultimate bitumen recovery. As a result, a suitable selection of critical KPIs is required to balance the development and economics of the steam chamber.This work presents a study of multiple combinations of SAGD KPIs for a multi-pad real-time steam allocation. The KPI combinations used in this study are NPV, cumulative steam-oil-ratio (cSOR), recovery factor (RF), and average pad temperature (aveTemp). A Box-Jenkins-based data-driven model simulates the SAGD recovery process, and a first principle simulator is used as a substitute for an actual reservoir. The Alternating Direction Method of Multipliers (ADMM) is proposed for multi and many-objective optimization for real-time steam allocation across multiple pads. A compromise programming approach guides the decision-makers choice of the optimum control setpoints of the non-dominated solutions on each horizon. At the end of three and half years of RTO, the optimal KPI combination is ranked based on the aggregated performance of NPV, cSOR, and RF of SAGD multi-pad steam allocation. A synthetic Western Canadian reservoir model with four pads and 33 well pairs developed from publicly available data is used for this study.The aggregated performance of this study's results showed that joint optimization of an economic and a steam chamber growth KPIs of two is better than a combination of three or four. The choice of the joint economic and steam chamber growth KPIs depends on the average pad temperature at the start of RTO to achieve optimal fluid balance in the long term. cSOR or NPV with RF joint KPI performs optimally at average pad temperatures above 90 °C, while cSOR or NPV with aveTemp below 90 °C at the start of RTO to achieve injected and produced fluid balance. Optimum economic return, recovery, and greenhouse gas emission of the SAGD process are achieved with cSOR KPI as the primary economic objective.

On geothermal energy recovery from post-SAGD reservoirs

In the steam-assisted gravity drainage (SAGD) process, large amounts of steam are injected into the reservoir to mobilize bitumen for its production to surface. The amount of thermal energy injected into the reservoir creates a man-made geothermal system that could be used to yield heat after the SAGD operation is complete. In the research documented here, for the first time, the amount of energy stored in the reservoir is evaluated and potential processes for recovery of the thermal energy are explored. The results reveal that after 10 years of SAGD, about 35% of the total injected energy in the steam remains in the reservoir rock from which the bitumen was extracted. After a 1 year blowdown stage at the end of the SAGD operation, ∼32% of the total injected energy remains in the reservoir rock. Three cases are used to explore the potential for recovering the thermal energy in the reservoir rock. The results show that the best case is one where a new horizontal well is added at the top of the reservoir above the SAGD well pair. In this case, >100 °C water was recovered at high rate for over 1,400 days realizing about 34% recovery of the thermal energy contained in the reservoir rock after the SAGD blowdown stage. The results demonstrate that there is potential for recovering the thermal energy. This recovered energy offers means to make the SAGD process more thermally efficient over its entire energy production life.

Introduce dimethyl ether (DME) as a solvent for steam-assisted gravity drainage (SAGD) co-injection: An effective and environmental application

Conventional heavy oil and bitumen thermal recovery is currently facing increasing energy demands and climate-related challenges. Dimethyl ether (DME) as a renewable and sustainable solvent was recently proposed as a possible solution for a carbon transition to hydrogen economics. However, only limited studies with unclear mass transfer mechanisms have been conducted on DME and its co-injected on steam-assisted gravity drainage (SAGD) optimization. In this study, a numerical model was developed to investigate the DME-based expanding-solvent SAGD (ES-SAGD) process to capture the complex mechanisms involved. The impact of temperature on relative permeability curves and coupled heat/mass transfer were further discussed in detail. The results of DME-based ES-SAGD and conventional SAGD were compared in terms of process performance and energy efficiency as well as carbon intensity. The optimal range of DME concentration was investigated to achieve the highest recovery factor, and with the assistance of DME carbon intensity can be reduced to one quarter to half of that in conventional SAGD. The study confirmed DME is a novel solvent that leads to the viable performance of ES-SAGD to meet carbon emission reduction objectives.

Molecular Dynamics Investigation of Wettability Alteration of Quartz Surface under Thermal Recovery Processes.

One of the primary methods for bitumen and heavy oil recovery is a steam-assisted gravity drainage (SAGD) process. However, the mechanisms related to wettability alteration under the SAGD process still need to be fully understood. In this study, we used MD simulation to evaluate the wettability alteration under a steam injection process for bitumen and heavy oil recovery. Various oil droplets with different asphaltene contents were considered to determine the effect of an asphaltene content on the adsorption of the oil droplets onto quartz surfaces and wettability alteration. Based on the MD simulation outputs, the higher the asphaltene content, the higher the adsorption energy between the bitumen/heavy oil and quartz surfaces due to coulombic interactions. Additionally, the quartz surfaces became more oil-wet at temperatures well beyond the water boiling temperature; however, they were extremely water-wet at ambient conditions. The results of this work provide in-depth information regarding wettability alteration during in situ thermal processes for bitumen and heavy oil recovery. Furthermore, they provide helpful information for optimizing the in situ thermal processes for successful operations.

Modelling temperature dynamics of the SAGD process in an oil reservoir by the discovery of parametric partial differential equations

AbstractMany chemical and industrial processes are complex, and the dynamics of such processes cannot be explained using a partial differential equation (PDE) or a system of PDEs with constant coefficients. Parametric PDEs, that is, PDEs with their coefficients varying across time or space, are utilized for this purpose. The non‐availability of data at all spatial locations and partially available process knowledge add to the complexity of modelling such processes. This paper proposes a framework to discover parametric PDEs using data‐driven and hybrid modelling approaches with the temperature dynamics of steam‐assisted gravity drainage (SAGD) process in an oil reservoir as the system under study. We utilize an ensemble of 200 realizations of the temperature dynamics generated using the variogram for the PDE discovery. Permeability, which is one of the oil reservoir's petrophysical properties, is used to develop the hybrid models. We infer that utilizing partial process knowledge aids in improving the model's accuracy.

Numerical Investigation of a Novel Bottom-Up Assisted Pressure Drive Process in Oil Sands Reservoirs with Shale Barriers

Steam-assisted gravity drainage (SAGD) is widely applied to recover bitumen and heavy oil resources. Reservoir heterogeneity, especially the presence of shale barriers, continues to challenge the performance of SAGD. A novel enhanced oil recovery process, bottom-up assisted pressure drive, is proposed to improve the oil production in the reservoirs with shale barriers. In this work, numerical simulation is applied to investigate the feasibility of a bottom-up assisted pressure drive process. A reservoir model with typical oil sand reservoir properties is developed considering shale barriers. The performance of bottom-up assisted pressure drive and SAGD is compared under the same reservoir conditions, including steam chamber development, oil production rate, cumulative oil production, and the pressure difference between injector and production. The inherent mechanisms associated with the bottom-up assisted pressure drive are also well understood and confirmed. In the bottom-up assisted pressure drive, a flat steam chamber is developed from the bottom of the reservoir in the early stage of the process and grows upward with the injection of steam. The large volume of the steam chamber and the huge contact area between steam and bitumen contribute to a high oil production rate. The peak oil production rate in the bottom-up assisted pressure drive is approximately three times that in the SAGD process. The cumulative oil production in the bottom-up assisted pressure drive is 20% higher than that in the SAGD process. The effect of shale barriers on bottom-up assisted pressure drive is less, indicating one advantage of this novel process over SAGD in oil sands reservoirs with shale barriers. The pressure difference in the bottom-up assisted pressure drive is greater than that in the SAGD process. The pressure drive is another mechanism for improving oil production. The calculated net present value (NPV) in the bottom-up assisted pressure drive process is 27% higher than that in the SAGD process. This is mainly attributed to the high oil production rate in the early stage of the process and high cumulative oil production. The simulation study in this work provides technical support for the future field applications of this novel recovery process.

A New Analytical Model for Predicting Steam-Assisted Gravity-Drainage Performance in the Plateau and Decline Stages

Summary Analytical models have been widely used to study the steam-assisted gravity-drainage (SAGD) process. Existing analytical models for this process either underperform or are limited in their applicability. In this paper, a new analytical model is developed to address these shortcomings. The new model consists of three major components. First, an equation for predicting oil production rate during the plateau stage was developed. This equation allows for permeability anisotropy in the reservoir, which is neglected in the majority of existing analytical models. Second, a novel and concise equation for calculating oil production rate during the decline stage was derived. This equation for the first time provides a general relationship between oil production rate during the decline stage and the properties of the reservoir together with key operating conditions and simultaneously mitigates the shortcomings of the majority of existing models (e.g., inapplicable in the decline stage of the SAGD process). Third, new correlations representing heat loss from the steam chamber to the overburden and heat transfer to oil-undepleted zone ahead of the chamber interface were derived; new predictive equations for estimating steam/oil ratio (SOR) in the plateau and decline stages of SAGD were obtained. The new model has been validated against a 2D scaled laboratory experiment and a set of field data. The results of this validation show that the new model predicts the oil production rate and SOR over the lifetime of an SAGD operation (excluding the short steam rise period) reasonably well. Predictions from the new model were also compared with several existing analytical models: The new model provided a closer match to actual measurements than other models. This robust model is grounded in more physics and incorporates reservoir geology and well operating conditions. It enables better understanding of the SAGD process and significantly improves the prediction of SAGD performance. Hence, it can be used to design new SAGD projects, predict existing projects, and optimize existing projects.

Integration of data-driven models for dynamic prediction of the SAGD production performance with field data

Steam-assisted gravity drainage (SAGD) is a successful thermal recovery process and has been widely applied to oil sands production. The prediction of oil production of the SAGD process plays a significant role in decision-making, where numerical simulation is one of the tools which support engineers. However, the traditional numerical simulation process for the SAGD production prediction, such as history matching, sensitivity analysis, and predictive runs, is a time-consuming process that is always associated with heavy computational costs. Engineers require reliable alternative modeling tools for the management of SAGD production. In this study, a data-driven model-based workflow is formulated and tested for the prediction of the SAGD production performance. After a series of data processing and integration of real field data, the machine learning algorithms are successfully utilized to predict future production performance based on past production information and operational conditions. A comparison of different machine learning algorithms shows that a Gated Recurrent Unit (GRU) based model has the best predictive ability.