Steam Assisted Gravity Drainage Project Research Articles

SAGD Trial in Omani Heavy Oil Field Overcomes Suboptimal Conditions

_ This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper SPE 215943, “Short Spacing, Lower Viscosity, and Suboptimal Operating Conditions SAGD Trial in Mukhaizna Heavy Oil Field,” by Buthaina S. Al Yahmadi, Rawaa M. Al Aamri, and Walaa S. Al Suqri, Oxy, et al. The paper has not been peer reviewed. _ Mukhaizna is a heavy oil field in southern Oman. It is a multistacked reservoir that has been producing under steamflood since 2007. The main sandstone reservoirs were developed using horizontal producers in each target zone supported by vertical injectors. Although most of the patterns are thermally mature, a few areas still are awaiting steamflood response. To mature these areas, a steam-assisted gravity drainage (SAGD) pilot was evaluated, customized, and implemented using existing patterns and well configurations. Mukhaizna Field The Mukhaizna heavy oil field contains viscous, low-gravity (14–18 °API) crude oil in the shallow Permian-age sands of the Gharif formation. Porosity is very good (25–35%), as is permeability (1,000–10,000 md). The Gharif formation consists of upper, middle, and lower reservoirs. Different injector and producer configurations were evaluated to ensure good production. Because a shale barrier clearly was present in the Gharif formation in most of the area but absent elsewhere, the development of this formation was affected. After evaluation of various pattern-configuration options, a development plan was based on three vertical injectors and three horizontal producers per pattern. Thermal development of the field with steam injection began in July 2007. Steamflood maturity has been inconsistent across the field. Various methods of optimizing steam-injection volumes or steam reshuffling in the offset injectors in some patterns were attempted in order to accelerate thermal maturity, but some horizontal producers were still cold with low inflow. To solve this, a pilot-project area with two stacked horizontal producers was evaluated for SAGD potential. These two producers targeted the same zone, Upper Gharif 2A, in one of the best reservoirs in the field. This area was supported by a horizontal injector that had strong communication with the lower producer, but because of misalignment between the horizontal injector and the upper producer, the upper producer was cold, with its progressive cavity pump at pumpoff condition. To evaluate this SAGD trial and predict performance, two analogs were reviewed to compare reservoir properties and parameters. The first analog, Jackfish1, is considered a successful SAGD project, exceeding 90% of its nameplate capacity since first steam. The second analog is Xinjiang oil field, which was not a successful SAGD project, with a steam/oil ratio (SOR) reaching 4.3. This SAGD trial aimed to enhance the oil production of cold patterns with two stacked wells while gaining an understanding of the potential challenges and opportunities of applying SAGD in the existing well configurations at Mukhaizna. The upper horizontal well was converted to a steam injector with an insulated tubing completion. The nearby horizontal injector was kept at the same injection rate to avoid any changes in operating conditions around the SAGD trial.

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.

What did we learn from steam assisted gravity drainage (SAGD) applications in three decades, and what is next?

This paper evaluates and analyzes three decades of ongoing SAGD projects in Canada, examining their successes, failures, lessons learned, and limitations from multiple perspectives, including geological, technical, environmental, and operational aspects. The reasons for successful SAGD practices are also identified, and recommendations for designing new SAGD projects and future post-SAGD practices in matured fields are provided. The potential of mature SAGD projects was also explored, and new insights for the future of SAGD (new and matured fields), including “zero emission” applications using solvents and reduced emission using steam additives, are also presented. The conclusive analyses done and the recommendations made will lead to more efficient SAGD applications (new and matured) in Canada, also providing a useful road map for the other parts of the world.

Mechanisms and Operational Strategies of Multi-Lateral Steam-Assisted Gravity Drainage (SAGD) for Heterogeneous Reservoirs

As the SAGD steam chamber and production performance in heavy oil reservoirs under fluvial sedimentation environment are heavily impacted by reservoir heterogeneity, an innovative strategy was proposed in this study coupling rock dilation and multi-lateral wells in SAGD projects to break the mud barriers and achieve uniform steam chamber growth. True tri-axial experiments and numerical simulation were designed to validate the feasibility of this strategy, based on which the branches of the SAGD well pairs were designed and the operational parameters were optimized for different geologic heterogeneity conditions. The tri-axial experiment results indicate that the rock formations in the heavy oil reservoirs of the F oilfield exhibit significant shear dilation effects under low confinement pressure conditions, with a volumetric dilation capacity of up to 7%. The branches should be deployed in an interleaved manner, with a horizontal displacement of 20 m and a vertical displacement of 6 m. The optimal results are achieved when the branches intersect the interbeds, allowing for enhanced steam chamber conformance and enlarged volume. Dilation zones of 3–8 m can be created above the steam-injection horizontal wells and around the branches in the reservoir during the dilation of SAGD steam chambers. The maximum volume of dilation fluid used for hydraulic dilation is suggested to be less than 2000 m3. This strategy has been validated as being successful in the pilot SAGD well pair in the F oilfield, China, with the SAGD preheating time reduced by 50% and an incremental oil rate of 4.5 tones/day, indicating encouraging potentials in similar heavy oil reservoirs.

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.

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.

Study of novel steam assisted gravity drainage multilateral wells with dynamic gridding

SAGD (steam assisted gravity drainage) performance and its stream chamber growth are primarily determined by the vertical permeability of a reservoir. To deal with inter-bedded shale (IBS)-isolated intervals in bitumen reservoirs and improve steam chamber conformance, novel multilateral (MLT) wells with laterals and/or vertical legs in their trajectories are drilled to penetrate IBS. PetroChina Canada LTD. (PCC) has implemented MLT wells as a technology trial to evaluate potential mitigation to the presence of IBS in its MacKay River SAGD Project. Taking into account both accuracy and efficiency, dynamic local grid refinement (DLGR) is incorporated into the description of the mass and heat transfer phenomena in the vicinities of MLT wells. Also, to represent MLT injection and production wells as open hole branches, their lateral properties are adjusted by considering pore-scale mechanisms of fluid flow and heat transfer. With all these novel features established, the impacts of MLT wells on steam chamber growth and oil recovery are evaluated. It is discovered that MLT wells are conducive to increasing both injectivity and productivity due to the improvement of contact and drainage areas. Besides, how MLT wells perform with various steam operation strategies, geological parameters, injection pressure and NCG (non-condensable gas) wind-down scenarios is assessed.

Sensitivity analysis of injection parameters in steam assisted gravity drainage under geological uncertainty

Steam-assisted gravity drainage (SAGD) is a challenging enhanced oil recovery technique that requires proper parameterization in terms of well geometry and steam injection parameters as these parameters are highly dependent on the reservoir geology and fluid characteristics (e.g., net pay variation, water saturation). Injection rate and pressure, temperature, steam quality, lean zone, gas zone, water saturation, and wellbore hydraulics are among the most important engineering parameters of SAGD. This work focuses in the sensitivity analysis under geological uncertainty of some operational parameters, such as: injection rate, temperature, steam quality and pressure. To reach this objective we build a realistic reservoir model with multiple geological settings and descriptions. Moreover, two complementary approaches were studied: i) a deterministic sensitivity analysis relying on a factorial design matrix and ii) a stochastic analysis using particle swarm optimization. There are several key geological uncertainties in SAGD, such as net pay variation, inclined heterolithic stratification (IHS) presence, high water saturation in reservoirs, bottom water issues, and gas cap problems. This work focuses on the role of porosity and permeability in oil production, as these impact these geological properties. To reach this objective, two specific groups of ten different porosity and permeability pairs of geostatistical realizations were generated using Direct Sequence Simulation and Co-simulation. Group 1 used the same variogram model for 10 random seeds; and Group 2 used a combination of values that adopted a simultaneous and a random variation, which were assigned to the seed and to the variogram. We opted by a reservoir model that mimics an anticlinal reservoir, as it proved to be a determining factor for the low levels of Net Present Value (NPV) when compared to other geological scenarios. Within the four most commonly studied parameters in SAGD projects, the association of deterministic versus stochastic multi-objective analysis allowed to accurately validate injection rate as the most relevant parameter. Regarding the geological uncertainties, Group 1 showed that for a certain porosity distribution and permeability orientation, the random origin of these distribution maps eventually attributed a higher NPV uncertain. On the other hand, in Group 2, the simultaneous spatial and seed variation provided less uncertainty associated to NPV. • Sensitivity analysis under geological uncertainty of SAGD operational parameters. • Impact of small-scale variability of petrophysical properties in SAGD performance. • Deeper understanding of relevant injection parameters that influence the NPV and CSOR. • Comparison between deterministic statistical analysis and stochastic optimization.

Physical modeling of nitrogen slug operation in Xinjiang SAGD projects - Fundamental roles of NCG in SAGD process

Non-condensable gas (NCG) co-injection in mature Steam Assisted Gravity Drainage (SAGD) chamber had been widely implemented and significant amount of steam was saved. Encouraged by their performance, NCG SAGD was also tested in Xinjiang oilfield since 2012. Its strategy differed from others in that nitrogen slug was injected once per year since the early SAGD stage. However, its performance was quite mixed. A unique 2D model was used to mimic the field operation of SAGD and NCG SAGD. The general performance, temperature drop, pressure oscillation, gas fingering and gas coning were analyzed. It showed non-condensable feature of NCG lead to gas accumulation and pressure oscillation in NCG slug operation. Its partial pressure effect lowered down temperature, saving steam but reducing oil rate, potentially leading to gas coning issue. The main purge mechanism was gas solubility in water and oil which controlled the NCG concentration inside the steam chamber. NCG fingering was found to speed up vertical growth of steam chamber in the early SAGD stage. However, injecting NCG before chamber getting mature should be treated with caution. Lastly, NCG was recommended to inject through vertical well to the top of the formation.

A steam injection distribution optimization method for SAGD oil field using LSTM and dynamic programming

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

Analysis of Athabasca Oil Sands Investigates SAGD Performance Variability

This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper SPE 195348, “Steam-Assisted Gravity Drainage Performance Variability—Analysis of Actual Production Data for 28 Athabasca Oil Sands Well Pairs,” by Quang T. Doan, Vincano; S.M. Farouq Ali, SPE, University of Houston; and Thomas B. Tan, SPE, Petrostudies Consultants, prepared for the 2019 SPE Western Regional Meeting, San Jose, California, 23–26 April. The paper has not been peer reviewed. Steam-assisted gravity drainage (SAGD) performance in bitumen-recovery projects in Alberta is affected by geological deposits, reservoir quality, and operational experience. The authors reviewed and analyzed actual field production and injection data for 28 Athabasca oil-sands-deposit SAGD well pairs (WPs). Based on analysis of field-production data, a numerical model was built and calibrated against production data from two of the poorer-performing WPs among the 28 studied. Agreement between simulated and actual cumulative oil and steam/oil ratio (SOR) was within 10% after 6 years of operations on a first-iteration basis. Problem and Investigation Methodology A survey of the literature reveals that some aspects of the SAGD process, particularly with regard to the behavior of gas, still largely are not understood. While successful history-matching simulations of SAGD WPs exist for several different projects, these rely on dead-oil pressure/volume/temperature treatment and exclude any findings and discussion on gas production. Such history-matched models likely would need to be modified significantly to be useful for modeling the wind-down stage of SAGD operations. Recent numerical studies modeling the generation of aquathermolysis gases focused on the injection of noncondensable gas into a mature SAGD steam chamber. In preparation for a series of numerical studies on aspects of SAGD performance, a reservoir model simple enough to be relatively adaptable for different geological settings was built. Such a model had to be calibrated rigorously with actual production data to provide a high degree of confidence in its results and predictive capability in appropriate contexts. The investigation in the complete paper is aimed at addressing several fundamental aspects of SAGD operations, including the effects of reservoir heterogeneities and the behavior of gas. The first part of the complete paper is focused on reviewing and analyzing actual field production data spanning more than 1,700 days from 28 SAGD WPs from four different pads (A, B, C, and D) of the Jackfish 1 project; this synopsis will not include that extensive data. Jackfish 1 Project. Jackfish 1 consists of 42 WPs divided into six pads (including the 28 WPs in Pads A, B, C, and D analyzed for the authors’ study) and is part of the geological oil-sands trend of the Athabasca oil-sands deposit. Jackfish 1 has a nameplate capacity of 35,000 BOPD, with a designed SOR of 2.7. Consistently exceeding 90% of its nameplate capacity since first steam, it is commonly considered to be a successful SAGD project. The results of data analysis for the WPs studied indicated the following: Considerable variance exists in the recovery performance of SAGD WPs on the same pad. Considering the small drainage area of the 7-WP pad (800×800 m), such variances bear important implications for the planning and execution of SAGD projects (particularly greenfield development but also with regard to brownfield expansion). The authors stress that forecasting project productivity should not be based on a single-WP, deterministic simulation model without any consideration for distributions in reservoir geology and parameters affecting SAGD performance. This assessment is equally applicable in the estimation of reserves.

Machine learning-based prediction of the shale barrier size and spatial location using key features of SAGD production curves

The shale barrier (SB) tends to impede the steam chamber development because of the low permeability of shale during the steam-assisted gravity drainage (SAGD) process. The interpretation of 4-D seismic data in geostatistical reservoir modelling is traditionally used to understand better the uncertainty of distribution of SB. On the other hand, long-term 4-D seismic survey to monitor the steam chamber development incurs additional cost.In this study, machine learning (ML) approaches, such as multiple linear regression (MLR), Random Forest, and artificial neural network (ANN), were performed to predict the horizontal location, width, and length of the SB using the inflection points of the SAGD production data; oil rate, cumulative oil, steam-oil ratio, and cumulative steam-oil ratio and the reservoir and operating parameters; reservoir thickness, horizontal permeability, vertical-horizontal permeability ratio, oil saturation, and steam injection pressure without the application of 4-D seismic data.Data pre-processing was carried out to examine and select 38 parameters (5 reservoir and operating parameters, the vertical location and thickness of the SB, and 31 inflection points), and the dataset (2131 cases) was divided into 75% of the train set and 25% of the test set. The k-fold cross validation and grid search process for hyperparameter tuning were performed to optimize the ML models. A comparison of the ML models revealed the ANN models to have larger coefficient of determination (R2) values than those of the MLR and Random Forest models. In the optimal ANN model, the R2 values of the test set for predicting the width (0.869) and length (0.918), but the R2 value for predicting the horizontal location was as low as 0.569.For verification, the optimal ANN model was tested using the production data from Husky's Sunrise and Suncor's Firebag SAGD projects in Canada. The field production data and simulation results using the reconstructed SB showed a similar trend, and the similarity between the field data and simulation results was improved compared to the results reported by Kim and Shin (2018).

An Empirical Oil, Steam, and Produced-Water Forecasting Model for Steam-Assisted Gravity Drainage With Linear Steam-Chamber Geometry

Summary Presented here is a steam–assisted–gravity–drainage (SAGD) forecasting technique for oil and water production and steam injection based on linear steam–chamber geometry and an empirical form for the progression of the steam/oil interface with time. The oil forecast model generates full–cycle SAGD production profiles using three empirical inputs (the initial plateau oil rate qo,si, an exponent n, and the rising–phase–chamber angle θ) and volumetric parameters (well length, pay thickness, porosity, half–well spacing, and initial and residual oil saturation). Steam and produced–water forecasts are derived analytically using the resulting steam–chamber geometry and the heat required for the fluids, rock, and overburden. Peak rate is a direct input in this methodology, and as a result only volumetric and some thermodynamic parameters are required, but not fluid or transmissibility inputs, such as viscosity and permeability. This allows for direct use of commercial SAGD production data in the forecasting process. The model predictions are validated at a high level with field data from Devon Canada Corporation's Jackfish SAGD project and numerical simulation.

Integration of data-driven modeling techniques for lean zone and shale barrier characterization in SAGD reservoirs

High water saturation zone, which is also known as lean zone, and shale barrier, are two common types of heterogeneous features in steam-assisted gravity drainage (SAGD) reservoirs. Lean zone poses a detrimental influence on conventional SAGD operations, as it causes steam utilization efficiency to decrease and increases the steam-oil ratio. Shale barrier would also impede the vertical growth and lateral spread of a steam chamber and potentially reduce oil production. An efficient characterization workflow is proposed to estimate the quantity, location, and volume of these heterogeneous features by integration of data-driven modeling techniques.Field data including geophysical, operational and production data corresponding to several existing SAGD projects are extracted from the public domain and used to build a series synthetic homogeneous models. Lean zones and shale barriers with varying distribution and volume are randomly added. From the corresponding production time-series data, a set of input features are identified through a hybrid method comprised of discrete wavelet transformation (DWT) and principal component analysis (PCA), while the output parameters are formulated to describe the actual number and geological parameters of two types of reservoir heterogeneities. A two-level data-driven model based on artificial neural networks (ANN) is employed to correlate the complex relationship between input and output attributes. Finally, this calibrated model is integrated into a novel characterization workflow to infer an ensemble of probable realizations of lean zone and shale barrier distribution that are conditioned to a given production historical profile.This work demonstrates the potential of practical application of data-driven models in correlating complex reservoir heterogeneity properties and production time-series data. Results from the case study illustrate the utility of the proposed workflow in facilitating the efficient identification of heterogeneous features from SAGD profiles. The potential savings of computational efforts associated with the proposed methodology are also explained.

A New Approach to the Analytical Treatment of Steam-Assisted Gravity Drainage: A Prescribed Interface Model

Summary The majority of the models in the literature for the steam-assisted-gravity-drainage (SAGD) process solve the problem of conductive heat transfer ahead of a moving hot interface using a quasisteady-state assumption and extend the solution to the base of the steam chamber where the interface is not moving. This approach, as discussed by Butler (1985) and Reis (1992), results in inaccurate or sometimes infeasible estimations of the oil-production rate, steam/oil ratio (SOR), and steam-chamber shape. In this work, a new approach for the analytical treatment of SAGD is proposed in which the problem of heat transfer is directly solved for a stationary source of heat at the base of the steam chamber, where the oil production occurs. The distribution of heat along the interface is then estimated depending on the geometry of the steam chamber. This methodology is more representative of the heat-transfer characteristics of SAGD and resolves the challenges of those earlier models. In addition, it allows for the extension of the formulations to the early stages of the process when the side interfaces of the chamber are almost stationary, without loss of the solution continuity. The model requires the overall shape of the steam chamber as an input. It then estimates the movement of chamber interfaces using the movement of the uppermost interface point and by satisfying the global material-balance requirements. Oil-production rate and steam demand are estimated by Darcy's law and energy-balance calculations, respectively. The result is a model that is applicable to the entire lifetime of a typical SAGD project and provides more-representative estimations of in-situ heat distribution, bitumen-production rate, and SOR. With the improved knowledge obtained on the fundamentals of heat transfer in SAGD, the reason for the discrepancies between the various earlier models will be clarified. Results of the analytical models developed in this work show reasonable agreement with fine-scale numerical simulation, which indicates that the primary physics are properly captured. In the final section of the paper, the application of the developed models to two field case studies will be demonstrated.

Development and application of proxy models for predicting the shale barrier size using reservoir parameters and SAGD production data

The modelling of an interbedded shale barrier in heterogeneous oil sands reservoirs has high uncertainty, which has a critical impact on the steam-assisted gravity drainage (SAGD) performance. Generally, an interpretation of 4D seismic data is the most widely used method for understanding the uncertainty of the shale barrier size.In a shale interbedded oil sands reservoir, the SAGD production data, such as the oil rate and steam-oil ratio (SOR), increase to a peak point and decrease to a trough point; the point intermediate between these two points is called the inflection point (IP).In this study, proxy models were developed to predict the shale barrier size using reservoir parameters and the IP of the SAGD production data without utilizing a 4D seismic data interpretation. In addition, a field application was carried out to test the developed proxy models using the data from Suncor's Firebag SAGD project, Alberta, Canada.The proxy models for predicting the shale width (WD), shale length (LN), and vertical location of the shale (VL) were developed using the statistical analysis of the reservoir parameters, shale size and location, and IP from production data. As a verification procedure, homogeneous 3-D simulations were performed to reconstruct the predicted WD, LN, and VL, and the oil production profiles of the SAGD field were compared with the simulation results. The oil production profiles showed a similar trend between the simulation results of the reconstructed model and the field SAGD production data. Therefore, the developed proxy models may use to predict the shale barrier size properly, and might be useful for field applications.

Pad-scale control improves SAGD performance

Steam Assisted Gravity Drainage (SAGD) is widely used in the Athabasca oil sands deposit to recover bitumen. Since the viscosity of bitumen is high at original reservoir conditions, heat is required to lower its viscosity to the point it becomes mobile enough to be recovered under gravity drainage. To heat the reservoir, steam is injected into the formation and thus SAGD is energy intense. Given that the fuel used to generate steam is the largest operating cost, the steam-to-oil ratio is one of the key parameter for evaluating the economics of any SAGD project. Here, the use of dynamic distributed steam injection within a pad of SAGD wellpairs is explored. The results demonstrate that feedback control leads to improvements of the SOR over that of constant pressure. The results show that the controller is able to detect the “sweet spots” (oil zones with better geological properties) in the reservoir and dynamically deliver more steam to that region. Meanwhile, it reduces the steam injection towards relatively worse quality zones to lower the local SOR.

Experimental study on viscosity reducers for SAGD in developing extra-heavy oil reservoirs

Steam assisted gravity drainage (SAGD) is an effective in situ oil recovery technology in developing extra-heavy oil reservoirs. Large volumes of steam are needed, however, to heat the extra-heavy oil because of its high viscosity. Steam generation consumes large amounts of natural gas, which adversely affects the economics of SAGD, especially when oil prices are low. Moreover, environmental concerns arise because of excessive freshwater use and greenhouse gas emissions from the burning of the fossil fuels to generate steam. Considering these limitations and concerns, this paper evaluates the effectiveness of different viscosity reducers to decrease the steam consumption and improve SAGD performance. We conducted a series of screening experiments, including viscosity-reduction ratio, thermal stability, and core flooding, for nine types of viscosity reducers, based on an extra-heavy oil sample from a commercial SAGD project in China. The results indicate that water-soluble viscosity reducer #8, a nanoemulsion, is suitable for SAGD. It has a viscosity-reduction ratio of 98.0% at 50 °C and is still effective after high-temperature and high-pressure (200 °C, 4.0 MPa) treatment, with a viscosity-reduction ratio of 92.6%. The displacement efficiency is improved by 29.1%, and the cumulative steam-to-oil-ratio is reduced by 45.3% compared with pure steam flooding. Despite viscosity-reduction, the effect of interfacial tension reduction plays an important role in improving displacement efficiency during the coinjection of steam and viscosity reducer #8 has good potential to improve SAGD performance in developing extra-heavy oil reservoirs.

Statistically Enhanced Model of In Situ Oil Sands Extraction Operations: An Evaluation of Variability in Greenhouse Gas Emissions.

Greenhouse gas (GHG) emissions associated with extraction of bitumen from oil sands can vary from project to project and over time. However, the nature and magnitude of this variability have yet to be incorporated into life cycle studies. We present a statistically enhanced life cycle based model (GHOST-SE) for assessing variability of GHG emissions associated with the extraction of bitumen using in situ techniques in Alberta, Canada. It employs publicly available, company-reported operating data, facilitating assessment of inter- and intraproject variability as well as the time evolution of GHG emissions from commercial in situ oil sands projects. We estimate the median GHG emissions associated with bitumen production via cyclic steam stimulation (CSS) to be 77 kg CO2eq/bbl bitumen (80% CI: 61-109 kg CO2eq/bbl), and via steam assisted gravity drainage (SAGD) to be 68 kg CO2eq/bbl bitumen (80% CI: 49-102 kg CO2eq/bbl). We also show that the median emissions intensity of Alberta's CSS and SAGD projects have been relatively stable from 2000 to 2013, despite greater than 6-fold growth in production. Variability between projects is the single largest source of variability (driven in part by reservoir characteristics) but intraproject variability (e.g., startups, interruptions), is also important and must be considered in order to inform research or policy priorities.