SAGD Research Articles

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.
 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. 

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.

A practical workflow to design inflow control devices in SAGD projects to increase production and lower fresh water usage

This paper discusses the significance of inflow control devices (ICDs) in steam-assisted gravity drainage (SAGD) operations and their impact on well performance in different reservoir heterogeneities and qualities. The study focuses on investigating the specifications of ICD design using a numerical flow simulation model and flow rate versus pressure data obtained from a flow-loop experiment. The key advantage of employing flow-loop experiment data in the simulation would be a physics-based mechanistic model rather than using empirical correlations.The research collects core analysis data from three wells and particle size distribution (PSD) data from four wells in the same location. Permeability estimation is conducted for each PSD using a previously developed correlation. These data and other real data are used to construct the reservoir model, and the performance of liner deployed (LD) ICDs is compared by assigning flow-loop data to the simulation.By employing a relatively conservative production approach with subcooling between 10 °C and 15 °C, the cases with LDICDs demonstrate higher oil production rates, improved steam conformance, and lower cumulative steam oil ratios (cSOR) compared to the case without LDICDs. However, in a relatively challenging production scenario with subcooling between 1 °C and 5 °C, the case without ICDs cannot be simulated at the desired subcooling temperature and the cases with LDICDs improved the well productivity. LDICD#1 is identified in both scenarios as the best case due to its enhanced steam conformance and higher oil production rate.Compared to the case without ICDs, using LDICD#1 at higher subcooling temperatures leads to a 17 % increase in oil production rate, while reducing cSOR and natural gas usage by 8 % and 10 % respectively. Similarly, at lower subcooling temperatures, the case with LDICD#1 shows a 21 % increase in oil production rate and reductions of 12 % and 17 % in cSOR and consumed natural gas respectively, compared to the case without ICDs.The findings highlight the effectiveness of LDICDs at various subcooling levels and their potential application in SAGD projects to reduce freshwater usage and greenhouse gas emissions. Completion and production engineers can benefit from a better understanding of relative production performance to develop more effective operational designs.

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.

Influence of solvent injection temperature in steam-solvent assisted gravity drainage process for heavy oil reservoirs of Brazilian Northeast

The solvent–steam assisted gravity drainage is an oil recovery process that combines the advantages of thermal and miscible effects, and it has been successfully tested, especially in Canada, where many heavy oil reservoirs are located. This method uses two parallel horizontal wells drilled one above the other, the upper injects steam and solvent and the lower produces oil. This process has not been applied yet in Brazil, where there are heavy oil reservoirs, especially in northeast region. Based on this context, this research aimed to study the application of the ES-SAGD process in a semisynthetic reservoir, with characteristics similar to those found in the Brazilian Northeast, specifically to analyze the influence of the solvent injection scheme on ES-SAGD. Numerical simulations were performed using commercial software from CMG. It was analyzed several steam-solvent injection rates, using two injected temperatures for solvent, (at reservoir or at steam temperature´s), in order to minimize explosion risks, that can be due to high temperatures. Results showed that solvent injection temperature has great influence on oil recovery, it is better for oil production when it is inject hot solvent, because cold solvent generates a cooling of the steam. However, it is possible to injected cold solvent (at reservoir temperature), and increase oil production, changing some steam properties, avoiding explosions risks.

Investigation of solid particle erosion‐related failures in once‐through steam generators (OTSGs) in oil sands in‐situ production: The limitations of the API RP 14E guideline in OTSG design or operational decision‐making

AbstractThe required steam for steam‐assisted gravity drainage (SAGD) oil sands operations is generated using a once‐through steam generator (OTSG) that is fed with relatively poor quality process water. Industries have reported possible solid particle erosion‐related failure in the OTSG boiler tubes because of the transport of precipitated dense inorganic particles. However, the presence of other damage mechanisms, e.g. corrosion, flow accelerated corrosion (FAC), often masks the evidence of erosive wear. Also, industries set an upper limit operating velocity for the OTSG using the API RP 14E guideline, which provides no quantitative erosion rates to determine an operating envelope. This study presents a computational fluid dynamics (CFD) analysis of erosion damage in a SAGD OTSG boiler tube. The results revealed that API RP 14E may not be an effective decision‐making tool for operating the OTSG system. For example, a 10% increase in velocity, even at conditions below the API RP 14E threshold, showed a decrease in the failure time of the boiler tubes by 40%–50%.

Fundamentals-Based Alternative Addresses Issue With Three-Phase Permeability Model

_ This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper SPE 205883, “Issue With Stone II Three-Phase Permeability Model and a Novel Robust Fundamentals-Based Alternative to It,” by Subodh Gupta, SPE, Heretech Energy. The paper has not been peer reviewed. _ The objective of this paper is to present a fundamentals-based, three-phase flow model consistent with observation that avoids the pitfalls of conventional models. Though the use of the Stone II model is very popular for three-phase flow across the industry, one issue in the context of gravity drainage is how it appears counterintuitively to limit the flow of oil when water is present near its irreducible saturation. The novelty of the work presented in the complete paper is in the development of a model based on fundamentals of flow in fine channels that better explains observed results in the context of flow in porous media. Problem Definition Residual oil saturation (So) from retrieved cores from oil-drained chambers of steam-assisted gravity drainage (SAGD) reservoirs invariably shows values as low as 1 or 2%, whereas reservoir simulations using Stone II-based relative permeabilities (an industrywide favorite) predict significantly higher numbers (14–18%). In previous work, the author and others, in an attempt to remedy the situation, extended the oil-phase relative permeability in the presence of the water phase (krow) and oil-phase relative permeability in the presence of the gas phase (krog) curves all the way to water and gas saturation values less than unity; however, they discovered that, in the presence of water saturation (Sw) near the irreducible water saturation (Swi), the use of the Stone II formula for oil relative permeability still resulted in high residual So. Correct estimation of residual oil-phase saturation is even more important for solvent/steam mixed thermal recovery processes such as solvent-aided processes, where a small amount of solvent is added with steam in SAGD, and significantly more important for solvent-dominated processes, where a small amount of steam or heat is added with a large amount of solvent. A large amount of residual oleic-phase saturation and associated pessimistic solvent-recovery prediction will lead to erroneous economic assessment of these processes. The discrepancy in residual So, as the author and coauthors discovered in previous work, stems from a peculiarity of the Stone II formulation given by Equation 1 of the complete paper. To model this 1D problem numerically, a program developed by the author for his PhD thesis for modeling of moving front reservoir processes with dynamic gridding was modified and run with constant fluid properties for hexane and water at constant pressure and temperature. It also incorporated the three-phase relative permeabilities given by Equation 1 and Table 1 of the complete paper. The results are shown in Fig. 1.

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.

Integration of machine learning and data analysis for the SAGD production performance with infill wells

AbstractThere 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 (), a total steam–oil ratio (SORtotal), and a stolen ratio () 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.

Study on CO2 Huff-n-Puff Development Rule of Horizontal Wells in Heavy Oil Reservoir by Taking Liuguanzhuang Oilfield in Dagang as an Example

Heavy oil reservoirs are often characterized by high viscosity and poor mobility, which is more complex with the presence of bottom water. The conventional vertical well development method has low oil recovery efficiency and limited controlled reserves of a single well. In addition, water cut can increase dramatically when the edge-bottom water breaks through. Horizontal well and CO2 huff-n-puff is an effective alternative development model for heavy oil reservoirs. This development method makes efficient use of CO2 and accords with the “Carbon Capture, Utilization, and Storage (CCUS)”. The horizontal well can increase the drainage area. The dissolution of CO2 improves the mobility of crude oil and increases formation energy. In this paper, we established numerical simulation models based on the Liuguanzhuang oilfield in Dagang. The characteristics and producing rules of the horizontal well and CO2 huff-n-puff development in the heavy oil reservoir were studied. The results show that the production characteristics of horizontal well and CO2 huff-n-puff were similar to Steam-Assisted Gravity Drainage (SAGD). CO2 forms a viscosity reduction area above the horizontal well and the heavy oil flows into the wellbore due to gravity after viscosity reduction. The CO2 huff-n-puff can effectively enhance the production area of horizontal wells compared with the depletion development. However, the improvement in the production area gradually decreased as CO2 huff-n-puff cycles continued. There was a boundary of production area against the horizontal well, with the main production of heavy oil occurring at the upper and either end of the horizontal well. The CO2 huff-n-puff has a restraining effect on the edge-bottom water, which is confirmed via the proposed theoretical model.

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.

Heavy oil recovery using gas injection methods and its challenges and opportunities

The relevance of enhanced oil recovery (EOR) and its development are always important considerations when it comes to the approaches used to improve heavy crude oil recovery. As a direct consequence of this, there is a growing demand for the discovery of unconventional resources such as bitumen, shale, and heavy oil. With the diminishing availability of conventional crude oil stocks, it is necessary to make efficient and fruitful use of heavy oil resources. Heavy oil recovery poses challenges due to the high viscosity and low mobility of the oil, making traditional recovery methods less effective. Gas injection has emerged as a promising technique to enhance heavy oil recovery, where different gas injection methods are evaluated to improve the oil displacement efficiency. Several gas injection methods have been employed in heavy oil recovery, including natural gas injection, carbon dioxide (CO2) injection, and steam-assisted gravity drainage (SAGD). Each method has its benefits and difficulties. Natural gas injection is relatively simple and cost-effective, but it may face limitations in terms of the amount of gas available and the gas-oil miscibility. CO2 injection has shown promising results due to its miscibility with heavy oil, which leads to improved oil recovery through swelling and viscosity reduction. The benefits of gas injection methods include increased oil recovery, reduced environmental impact, and potentially lower operational costs. These methods can also enhance the recovery of stranded heavy oil reserves, thereby contributing to global energy security. However, challenges associated with gas injection methods include high viscosity and low mobility, reservoir heterogeneity, the potential for gas channeling, and high capital and operational costs. Despite the challenges, gas injection methods offer significant opportunities for heavy oil recovery. Overcoming these challenges requires advanced reservoir characterization, optimized well design, efficient gas injection strategies. Technological advancements, such as advanced reservoir characterization techniques, improved well design, and optimized gas injection strategies, can help overcome these challenges and enhance heavy oil recovery using gas injection methods. The gas injection methods that are used to recover heavy crude oil have been evaluated in the research along with their benefits and the difficulties that can arise while employing the gas injection methods. This paper focuses on the challenges and opportunities of gas injection methods for heavy oil recovery.

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.

On the ability to store and recover hydrogen in post-SAGD reservoirs

In typical steam-assisted gravity drainage (SAGD) operations, after commercial operations are complete, over 60% of the oil within the reservoir is produced. This means that after commercial operations, there is a steam-filled gas porous rock zone with small amounts residual water and oil referred to as the depletion zone. Given the dimensions of a SAGD depletion zone is of order of 1,000 long, 100 m wide, and between 20 and 30 m tall, this represents a large pore volume that could be used for storage. For underground options, there have been suggestions of using salt caverns and produced gas or oil reservoirs. One novel option that has not yet been examined is hydrogen storage in post-SAGD depletion chambers. The research described here an evaluation of post-SAGD chambers for injection and production of hydrogen. The results show that hundreds of tonnes of hydrogen can be stored within post-SAGD chambers and the purity of the hydrogen that is produced varies from 98% at start to 96% after 5 years of production during co-production of methane originated from the original solution gas that is the oil. The purity of produced hydrogen improved with increased hydrogen storage capacity after multiple cycle storage reaching its highest recovery factor of 99.2 % after 4 cycles.

The development of life cycle greenhouse gas emission footprints of novel pathways for the solvent-assisted and solvent-electromagnetic heating oil sands extraction processes

Steam-based oil sands extraction methods are emissions-intensive. Solvent-assisted and solvent-electromagnetic heating are alternative methods with the potential to lower greenhouse gas emissions (GHG). However, identifying an energy-efficient process pathway for these technologies remains a major concern. This is a gap in the research. In this study, we developed simulation models to assess the performance of solvent-assisted, solvent-electromagnetic heating, and steam-assisted oil sands extraction central processing facilities. Three central processing facilities (pathways) were developed for solvent-assisted and solvent-electromagnetic heating processes to recover bitumen and solvent from emulsions. Pathways I and III use a low-temperature and a high-temperature distillation system, respectively, to purify the solvent. Pathway II uses a high-pressure separator to lower the amount of non-condensable gases in the solvent. Each pathway was applied to a deep and a shallow reservoir. Sensitivity and uncertainty analyses were conducted to present the GHG emission results. The results show that pathways I and III produce satisfactory solvent purity and minimize solvent losses in the central processing facility, and pathway II does not. Pathway II can be applied when a high degree of purity is not required. The life cycle GHG emissions from pathways I and II may not be favorable to the solvent-assisted process if the electricity emission factor and solvent-to-oil ratio are high. The lowest GHG emissions are from pathway III. The life cycle GHG emissions of the solvent-electromagnetic heating extraction in pathway III range from 34.4 to 61.7 and 23.3 to 43.9 kgCO2e/b-e for the deep and shallow reservoirs, respectively, while solvent-assisted emissions range from 26.6 to 48.2 and 20.2 to 40.0 kgCO2e/b-e for the deep and shallow reservoirs, respectively. Steam-assisted gravity drainage emissions range from 72.7 to 111.6 kgCO2e/b. The results show that solvent-assisted and solvent-electromagnetic heating processes can provide better performance than steam-assisted gravity drainage when a high-temperature distillation is installed in the central processing facility to recycle the solvent.

Parallel particle swarm optimization for optimal SAGD operating scenario and well placement in a high dimensional search space

Steam-assisted gravity drainage (SAGD) has been commercially tested successfully in many oilfields with different characteristics. The operational parameters and wells’ location substantially affect the performance of SAGD, and designing a scenario optimization to find the optimum values of these parameters would enhance the efficiency of the process. Although most previous studies worked on optimizing some of the mentioned parameters separately, barely any optimized them simultaneously using a full 3D model since optimizing such a high-dimensional problem is time-consuming. In this study, whole-time scenario optimization is designed to simultaneously optimize the operational (steam injection rate, temperature, and production bottom hole pressure of all intervals) and well placement parameters of an 8-year SAGD. Parallel particle swarm optimization (PSO) is developed to determine the desired number of simulations concurrently to reduce computational costs. Also, the SAGD time is divided into four time intervals, and the effect of uniform and non-uniform time intervals on the net present value (NPV) and oil production is investigated. The outcomes showed that conducting parallel PSO would reduce the optimization time by 79.8%. Also, by applying the non-uniform intervals, the highest NPV is achieved, and the SAGD time declines to 6 years.

Aperture Design Optimization of Wire-Wrapped Screens for SAGD Production Wells

Wire-wrapped screens have been established as one of the primary sand control devices in Steam-Assisted Gravity Drainage (SAGD) wells due to the high open-to-flow area and superior plugging attributes. However, their design is still a point of interest for thermal operations. Generally, existing approaches rely on one or more particular points of reservoir sands’ particle size distribution (PSD) and rules of thumb inferred from other devices like the slotted liners. This study used Sand Retention Testing (SRT) to analyze the performance of WWS under various testing conditions, which were neglected in the current design criteria. The experimental investigation leads to a set of graphical design criteria that provide an optimum aperture size window. The results show that the sand retention performance of WWS is highly dependent on the flow velocities of the wetting phase. Moreover, the testing showed satisfactory plugging performance of WWS even with narrow aperture sizes, proving a superior performance for low-quality oil sands.

Application of Inter-Well Connectivity Analysis with a Data-Driven Method in the SAGD Development of Heavy Oil Reservoirs

The development of heavy oil reservoirs in China is of great significance to safeguard national energy security, but great challenges are faced due to the complex and heterogeneous reservoir properties. Inter-well connectivity analysis is critical to enhancing the development performance, as it is a good way to interpret fluid flow and provides a theoretical basis for injection-production optimization. Data-driven deep learning methods have been widely used in reservoir development and can be employed to develop surrogate models of injection and production and to infer inter-well connectivity. In this study, the model performance of a recurrent neural network (RNN) and its four variants were evaluated and compared in a temporal production prediction. The comparison results showed that bidirectional gated recurrent unit (Bi-GRU) is the optimal algorithm with the highest accuracy of 0.94. A surrogate model was established to simulate the inter-well connectivity of steam-assisted gravity drainage (SAGD) in the research area by utilizing the Bi-GRU algorithm. A global sensitivity analysis method, Fourier amplitude sensitivity testing (FAST), was introduced and combined with the surrogate model to explain the influence of the input variables on the output variables by quantitatively calculating the sensitivity of each variable. Quantitative results for the inter-well connectivity of SAGD were derived from the sensitivity analysis of the proposed method, which was effectively applied to typical linear patterns and five-spot patterns. Inter-well connectivity varied from 0.1 to 0.58 in test applications, and mutual corroboration with previous geological knowledge can further determine the distribution of the interlayer in the reservoir. The workflow proposed in this study provides a new direction for analyzing and inferring the inter-well connectivity of SAGD in Northeast China heavy oil reservoirs.