Steam-assisted gravity drainage (SAGD) is a thermal-recovery process to produce bitumen from oil sands. In this technology, steam injected in the reservoir creates a constantly evolving steam chamber while heated bitumen drains to a production well. Understanding the geometry and the rate of growth of the steam chamber is necessary to manage an economically successful SAGD project. This work introduces an approximate physics-discrete simulator (APDS) to model the steam-chamber evolution. The algorithm is formulated and implemented using graph theory, simplified porous-media flow equations, heat-transfer concepts, and ideas from discrete simulation. The APDS predicts the steam-chamber evolution in heterogeneous reservoirs and is computationally efficient enough to be applied over multiple geostatistical realizations to support decisions in the presence of geological uncertainty. The APDS is expected to be useful for selecting well-pair locations and operational strategies, 4D-seismic integration in SAGD-reservoir characterization, and caprock-integrity assessment.
Low steam viscosity during steam injection can cause steam override and channeling issues for heavy oil recovery, resulting in high operating cost and low oil recovery. One of the common methods to increase the viscosity of steam is by co-injecting surfactants that generate stable foams with steam. The objective of this research is to develop structure-property relationships for surfactants in order to identify surfactant candidates as the steam foam additives for heavy oil recovery.
In this study, alkyl propoxy ethoxy ether carboxylate (alkyl PO EO ECA) surfactants were evaluated. Surfactant solutions at 1 wt% prepared in 1 wt% NaCl were aged at up to 250 °C in Parr reactors for up to 2 weeks. The degradation of the surfactants was quantified based on High Performance Liquid Chromatography profiles of the surfactants before and after the aging process. The foaming performance of the surfactants was evaluated at 1 wt% concentration at varied temperatures from 100 to 250 °C in a high temperature high pressure visual cell. Sand-packed columns were performed to evaluate the ability of the surfactant to increase the apparent viscosity of steam.
The results showed that alkyl PO EO ECA surfactants exhibit excellent chemical stability at up to 250 °C. However, the chemical stability of these surfactants are dependent on the hydrophobe structure as well as the numbers of PO and EO units of the surfactants. Among the studied surfactants, only ECA surfactants with specific structures were able to generate stable foam at 250 °C. It was found that the ECA surfactants with both PO and EO units and a long branched hydrophobe demonstrated to be excellent foaming agents that were able to increase the apparent viscosity of steam by three orders of magnitude at 250 °C in sand-pack columns. In the presence of bitumen, these surfactants were able to increase the steam apparent viscosity by two orders of magnitude. This increase in the steam apparent viscosity is sufficient to overcome the steam override and channeling during steam injection.
Past research has randomly identified some sulfonate and ether carboxylate surfactants as foaming agents for steam EOR processes. This work, however, evaluated these surfactants systematically in order to develop the structure-property relationships that can be used to optimize surfactants as steam foaming agents for thermal EOR processes at up to 250 °C.
For numerical reservoir simulation, the well model has always been a critical component that can have significant impact on the results and performance of the simulation. A new well model has been developed in a commercially available simulator to provide additional capabilities and improved robustness for advanced thermal simulation. A Natural Variable (NV) formulation, similar to that used in the reservoir solution, has been adopted for the new well model. The NV formulation enables the well model to reuse many of the reservoir solution computations hence allows for rapidly adding support of new features as they get implemented in the reservoir solution. In addition, to model the steam injection process more accurately, we adopted fullupstream weighted mobility for injection connections, for which the amount of steam injected depends on the wellbore instead of reservoir cell condition.
Shale heterogeneities often impede the development of steam chamber in many steam-assisted gravity drainage (SAGD) projects. Unfortunately, static data alone is generally insufficient for inferring the corresponding distribution of shale barriers. This study presents a novel data-driven modeling workflow, which integrates deep learning (DL) and data analytics techniques to analyze production profiles from horizontal well pairs and temperature profiles from vertical observation wells, for the inference of shale barrier characteristics.
Field data gathered from several Athabasca oil sands projects are extracted to build a set of synthetic SAGD models, where the geometries, proportions and spatial distribution of shale barriers are modeled stochastically. Numerical flow simulation is performed on each realization; the corresponding production/injection time-series data, as well as temperature profiles from one vertical observation well, are recorded. A large dataset is assembled for the development of data-driven models: wavelet analysis and other data analysis techniques are performed to extract relevant input features from the temperature and production profiles; a novel parameterization scheme is also proposed to formulate the output variables that would effectively describe the detailed distribution of shale barriers. DL, such as convolutional neural network, together with other data analytics techniques are applied to capture the complex and nonlinear relationships between these input and output variables.
The feasibility of the developed workflow is validated using synthetic test cases. Salient features capturing the impacts of shale barriers are extracted. It is observed from the production time-series data that, as the steam chamber approaches a shale barrier, a decline pattern is noticeable until the steam chamber advances around the shale barrier. An obstruction in the steam chamber development can also be noted in the temperature profiles, as steam is trapped by shale barriers that are located reasonably close to the horizontal well pair. This observation is confirmed by comparing the petrophysical logs and the temperature profiles at the observation wells. Analyzing both temperature and production data could help to infer the size of shale barriers in the inter-well regions. Finally, the model outputs are used to generate an ensemble of heterogeneous SAGD realizations that correspond to the input production and temperature time-series data.
This study offers a complementary and computationally-efficient tool for inference of stochastically-distributed shale barriers in SAGD models, which can be subjected to detailed history-matching workflows. It is the first time that data-driven models are used to analyze both production data from horizontal production well pairs and temperature profiles from a vertical observation well for inferring SAGD reservoir heterogeneities. The results illustrate the potential for application of data analytics in reservoir modeling and flow simulation analysis. The developed workflow also can be extended to characterize reservoir heterogeneities in other recovery processes.
For thermal heavy oil recovery, conventional steam injection processes are generally limited to reservoirs of relatively shallow depth, high permeability, thick pay zone and homogeneity. An alternative approach of applying Electromagnetic (EM) energy may be used to generate heat in reservoirs that are not suitable for steam injection or to improve the economics of the heavy oil recovery compared with steam injection. EM in-situ heating of oil reservoirs, in the form of EM energy absorption by dielectric materials, leads to an increase in temperature, a reduction in oil viscosity and an improvement in oil mobility. Recent studies have shown that EM heating is capable of reducing carbon emissions and water usage. However, the existing EM field simulators are limited to modeling of homogeneous media with respect to dielectric properties, which affects EM wave propagation and in-situ heat generation. For oil sands recovery where reservoir heating by EM energy is promising, it is desirable to simulate reservoirs in inhomogeneous formations, in which dielectric properties vary according to specific location. In this work, important background information regarding the EM wave propagation in inhomogeneous media is provided. A Helmholtz equation for the magnetic field by deformation of Maxwell's equations is presented that makes it feasible to find EM field solutions for such inhomogeneous media. Solution of only the magnetic field makes this work execution faster than the classical methods in which both magnetic and electric fields need to be calculated. By solving the equations of EM wave propagation and fluid flow in oil sands reservoirs simultaneously, this work provides a fully-implicit modelling method for the EM heating process. The feasibility of EM heating in oil sands is examined in two case studies: a) a horizontal well containing an antenna within and b) a horizontal well-pair with an antenna located in the upper well.
Petroleum recovery from oilfield assets increasingly involves wells that are very long in extent and have multiple laterals, multiple tubing strings and multiple control points to prevent breakthrough of unwanted fluids and/or to optimize recovery. Instead of simply controlling rates at the wellhead, downhole devices are now available where apertures and other controlling parameters can be set statically, autonomously, or through surface intervention,. Having various control points in a wellbore that may include numerous flow paths requires a flexible setup and robust algorithms to effectively set all local constraints at various measured depths. This paper describes special constructs called "boundary segments" with a similar set of flow rate and pressure control modes to those available for tubinghead or bottomhole well control. In a multisegment well model whose topology consists of a set of nodes with intrinsic properties such as pressure, global mole fractions, total enthalpy, saturations, etc. and a set of pipes with attributes of length, volume, and a flow rate, these special segments share an existing node but have their own unique pipe together with boundary conditions and an accompanying set of control modes. Boundary segments are highly flexible, elegant, easy to implement, and useful in a variety of cases. This paper will provide reservoir simulation engineers and developers with an understanding of a simple method to calculate primary well control at the surface choke together with multiple downhole constraints from devices and tubing strings.
In comparison to Steam-Assisted Gravity-Drainage (SAGD), the technique of injecting of warm solvent vapor into the formation for heavy oil production offers many advantages, including lower capital and operational costs, reduced water usage, and less greenhouse gas emission. However, to select the optimal operational parameters for this process in heterogeneous reservoirs is non-trivial, as it involves the optimization of multiple distinct objectives including oil production, solvent recovery (efficiency), and solvent-oil ratio. Traditional optimization approaches that aggregate numerous competing objectives into a single weighted objective would often fail to identify the optimal solutions when several objectives are conflicting. This work aims to develop a hybrid optimization framework involving Pareto-based multiple objective optimization (MOO) techniques for the design of warm solvent injection (WSI) operations in heterogeneous reservoirs.
First, a set of synthetic WSI models are constructed based on field data gathered from several typical Athabasca oil sands reservoirs. Dynamic gridding technique is employed to balance the modeling accuracy and simulation time. Effects of reservoir heterogeneities introduced by shale barriers on solvent efficiency are systematically investigated. Next, a state-of-the-art MOO technique, non-dominated sorting genetic algorithm II, is employed to optimize several operational parameters, such as bottomhole pressures, based on multiple design objectives. In order to reduce the computational cost associated with a large number of numerical flow simulations and to improve the overall convergence speed, several proxy models (e.g., response surface methodology and artificial neural network) are integrated into the optimization workflow to evaluate the objective functions.
The study demonstrates the potential impacts of reservoir heterogeneities on the WSI process. Models with different heterogeneity settings are examined. The results reveal that the impacts of shale barriers may be more/less evident under different circumstances. The proxy models can be successfully constructed using a small number of simulations. The implementation of proxy models significantly reduces the modeling time and storages required during the optimization process. The developed workflow is capable of identifying a set of Pareto-optimal operational parameters over a wide range of reservoir and production conditions.
This study offers a computationally-efficient workflow for determining a set of optimum operational parameters relevant to warm solvent injection process. It takes into account the tradeoffs and interactions between multiple competing objectives. Compared with other conventional optimization strategies, the proposed workflow requires fewer costly simulations and facilitates the optimization of multiple objectives simultaneously. The proposed hybrid framework can be extended to optimize operating conditions for other recovery processes.
Steam-Assisted Gravity Drainage (SAGD) is one of the popular methods for heavy oil production. The process is efficient and economical. However, it requires the use of large quantity of water and disposal of waste water can be costly. In addition, burning of natural gas for steam generation contributes to additional carbon dioxide generation, a known greenhouse gas, which is also undesirable. A method to heat up the in-situ oil without the use of injected water is highly desirable. Radio frequency (RF) heating of heavy oil reservoir is a potential method for oil recovery without steam injection. The evaluation of the potential of such method requires the coupling of a reservoir simulator with an electromagnetic (EM) simulator.
This paper describes the development and implementation of a flexible interface in a reservoir simulator that allows the runtime loading of third party software libraries with additional physics. Data is exchanged between the reservoir simulator and externally loaded software libraries through memory, therefore there is minimal communication overhead. The implementation allows for iterative coupling, explicit coupling and periodic coupling. This paper describes the mathematical coupling of the mass and energy conservation equations in the reservoir simulator with the Maxwell equations in an external library. The electromagnetic properties in the reservoir are highly dependent on temperature and water saturation, this dependence is accounted for in the coupled code using table look-up properties.
Canadian heavy oil and reservoir properties were used in our simulation investigation. We found that RF heating alone can be effective in heating up the in-situ water and reducing heavy oil viscosity by several orders of magnitude. As the in-situ water near wellbore was vaporized by RF heating, electrical conductivities were reduced to zero and thus allowed the EM wave to propagate further into the formation and heat up the water further away from the wellbore. With properly designed RF heating field pilots and tuning of EM and reservoir parameters, the coupled reservoir/EM simulator can be a powerful tool for the evaluation and optimization of RF heating operations.
The interface is sufficiently flexible to allow different types of multi-physics coupling. In addition to RF heating, it has also been used for reaction kinetics and geomechanics coupling with a reservoir simulator. It has been used for large scale coupled full field simulation with over 30 million cells.
Liu, Yigang (CNOOC China Ltd, Tianjin Branch) | Zou, Jian (CNOOC China Ltd, Tianjin Branch) | Han, Xiaodong (CNOOC China Ltd, Tianjin Branch) | Wang, Qiuxia (CNOOC China Ltd, Tianjin Branch) | Zhang, Hua (CNOOC China Ltd, Tianjin Branch) | Liu, Hao (CNOOC China Ltd, Tianjin Branch) | Wang, Hongyu (CNOOC China Ltd, Tianjin Branch) | Wu, Wenwei (China University of Petroleum, Beijing) | Wang, Cheng (China University of Petroleum, Beijing)
Steam and flue gas stimulation technology has been applied for heavy oil exploitation in Bohai Oilfield for almost ten years. For the special fuel and water requirement of the current thermal generator, large amount of diesel and desalinated seawater are needed during the thermal injection process. Besides, treatment of the produced oily wastewater on the platform becomes more difficult as the oil output increases.
Aimed at solving the existing problems and taking the advantage of characteristics of the supercritical water, a new type of supercritical steam and flue gas generator for offshore oilfield is proposed and studied. The newly proposed generator is mainly consisted of two sections, which are the supercritical water gasification reactor and combustion reactor, respectively. The produced oily wastewater could be directly used for steam generation. A series of experiments are carried out for its feasibility research and structure optimization.
A prototype of the generator is made for indoor experiment. During the gasification process, wastewater and the organic material mixed inside is placed in the supercritical conditions in the gasification reactor whose temperature and pressure are about 600-700°C and 23MPa, respectively. And the reaction product would be mainly H2, CO2 and water. Gasification Experiments of both the diesel and oily wastewater are conducted. And the combustion experiment is also conducted and the gasified gas is reacted with O2 under conditions of 25MPa and 500-550°C. Composition of the produced fluid in each experiments are analyzed. Besides, the structure of the generator is also designed and optimized for improving its working efficiency.
The proposed new-type supercritical steam and flue gas generator has the characteristics of high efficiency, waste water treatment and higher temperature and pressure delivery capacity. And there would be a promising perspective for its application on offshore platform.
Ni, Yidan (Department of Chemical and Petroleum Engineering, University of Calgary, Calgary, AB CanadaT2N 1N4) | Ding, Boxin (Department of Chemical and Petroleum Engineering, University of Calgary, Calgary, AB CanadaT2N 1N4) | Yu, Long (Department of Chemical and Petroleum Engineering, University of Calgary, Calgary, AB CanadaT2N 1N4) | Dong, Mingzhe (Department of Chemical and Petroleum Engineering, University of Calgary, Calgary, AB CanadaT2N 1N4) | Gates, Ian D. (Department of Chemical and Petroleum Engineering, University of Calgary, Calgary, AB CanadaT2N 1N4) | Yuan, Yanguang (Bitcan Geosciences and Engineering Inc., Calgary, AB Canada T2A 2L5)
Steam-Assisted Gravity Drainage (SAGD) is a widely used technology for heavy oil and bitumen recovery in Alberta, Canada. However, a SAGD conformance problem arises due to the heterogeneity of oil sands reservoirs, such as the presence of high permeability zones and high water saturation zones. In particular, during a geomechanical dilation startup process that has been developed and applied in SAGD startup operations, the dilation fluid tends to flow into the high permeability zones, leaving the low permeability zones unswept. Therefore, the high permeability zones must be temporarily and selectively blocked off so as to more effectively dilate the low permeability zones along a SAGD well-pair. Laboratory permeability reduction tests in sandpacks by oil-in-water (O/W) emulsion injection showed that a permeability reduction of up to 99.95% can be achieved. Results of emulsion injection in parallelsandpack tests demonstrated that a good conformance control can be obtained by a suitable combinations of IFT, emulsion quality, emulsion slug size, and oil phase viscosity of an emulsion system. The reservoir simulation study was conducted to first match the laboratory test results and then to optimize SAGD conformance control operations by emulsion injection in heterogeneous oil sands reservoirs. A field-scale SAGD simulation model was established to show that emulsion injection during the dilation startup process can build up communication between the injector and producer, resulting in better steam chamber growth and lower cumulative steam-oil-ratio (CSOR).