PRISM :: Browsing by Author "Chen, Zhangxing"

Browsing by Author "Chen, Zhangxing"

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Open Access
3D Geomechanical Modeling of Shale Formations and its Application in Borehole Stabilization
(2021-06-09) Deng, Liyu; Chen, Zhangxing; Hu, Jinguang; Almao, Pedro R Pereira
The issue of borehole instability as seen in shale formation drilling is a major problem currently facing the industry. In recent years, deep exploration and more intensive development of hard and brittle shale gas reservoirs has shown that borehole instability is a widely occurring issue present in this type of strata. Because of the high frequency of catastrophic failures that accompany drilling in shale, this is an important technical problem to be solved. Furthermore, as a result of the recent shale gas revolution in North America, there has been a focus on integrated innovations and the development of multi-disciplinary fields and multiple technologies related to exploitation of this resource. As part of this ongoing multi-disciplinary approach, the advanced development concept known as geological engineering integration has been put forward. Rooted in the study of geodynamics and aimed at the problem of borehole instability in shale formations, this study explores and develops concepts related to geomechanics, including well location optimization, well trajectory optimization, pre-drilling formation pressure prediction and well wall stability prediction techniques. The meticulous modeling of 3D geomechanics is of great significance to the study of regional borehole stability in a shale formation. Therefore, a geomechanical modeling method for shale formations and its field application in Indonesia's Oilfield A is demonstrated in this thesis. As part of this modeling, a detailed study on the physical, chemical, and mechanical properties of shale in Oilfield A is carried out by laboratory mineral analysis, electron microscopy, cation exchange capacity and rock mechanics parameters. These experimental results form the cornerstone of the 3D geomechanical modeling of Indonesia's Oilfield A. Leveraging the Petrel software platform, the 3D geomechanical modeling method and principles of a shale formation are introduced in detail. Through a series of core tests, well logging data and seismic inversion data, the mechanical parameters of Oilfield A are described in depth, and the spatial distributions of important parameters such as 3D elastic modulus, 3D Poisson’s ratio and 3D pore pressure in this oilfield are established. 3D geomechanical models of heterogeneity, porosity and elastoplastic features are also established. Using the finite element method, the 3D stress distributions and 3D safe density windows of Oilfield A are also calculated. By establishing a 3D fine geomechanical model, various attributes are extracted along the borehole trajectory of well A-10, and a prediction of borehole stability is carried out. The drilling fluid density windows and well depth structure are also recommended, indicating the type and approximate depth of possible downhole complications. The numerical results of the minimum in-situ stress present in Indonesia's Oilfield A are calibrated by LOT (leaking of test) data. Importantly, the relative errors that exist between LOT data and the minimum in-situ stress are small, and the maximum relative error is only 0.02. The drilling period of well A-10 is 28 days. Compared with the average drilling period of 55 days in Oilfield A, the drilling period is shortened by 49 days as a result of the modeling studied. Importantly, no complex accidents occur in the drilling process. Through direct or indirect validations of all established 3D pore pressure, collapse pressure, rupture pressure, in situ-stress and other models, both a confident geomechanical model and a density window model are finally determined. The results show that the geomechanical model can accurately reflect the magnitude and heterogeneity of in-situ stress in a shale formation and can effectively solve the problem of regional borehole stability found in this formation.
Open Access
Analysis of Production Data from Communicating Multi-Fractured Horizontal Wells
(2022-08-08) Ahmadi, Hossein; Clarkson, Christopher R.; Hassanzadeh, Hassan; Mattar, Louis; Chen, Zhangxing; Eaton, David W.; Miskimins, Jennifer
The most common technology used for the development of low-permeability (unconventional) oil and gas reservoirs is multi-fractured horizontal wells (MFHWs), which are designed to maximize fracture surface area in contact with the reservoir. In current development practice, multiple MFHWs are typically drilled from the same pad; over time, fracture and well (lateral) spacing have decreased, resulting in greater interference between wells (vertically and laterally). This interference, which commonly occurs through hydraulic fractures, can affect well performance, and complicate reservoir and fracture characterization efforts. Rate-transient analysis (RTA) is a reservoir engineering approach that is commonly used to derive reservoir/fracture properties for MFHWs producing from unconventional reservoirs. However, RTA methods/models are generally applicable to single wells and do not specifically account for inter-well communication through hydraulic fractures. It is the purpose of this dissertation to develop RTA methods/models that account for inter-well communication. In order to account for inter-well communication through fractures, both semi-analytical and machine learning approaches are developed for RTA of MFHWs. The semi-analytical approach developed herein utilizes the dynamic drainage area (DDA) concept. Two and three reservoir/fracture region semi-analytical DDA models are first developed to history match and forecast two MFHWs communicating through hydraulic fractures. These models, which account for two-phase flow (dry gas, water), and pressure-dependent porosity and permeability, are successfully verified with fully-numerical simulation results. Their practical applicability is also demonstrated using a field dataset consisting of six wells (drilled from two neighboring pads) exhibiting different degrees of communication. The final semi-analytical model developed is in the form of a new straight-line analysis (RTA) method, referred to as the “DDA-corrected” RTA model. When this method is applied to two wells that are communicating through hydraulic fractures, and are put on production at different times, two straight lines can be obtained for the first well that comes on production. Because the method assumes that the wells are fully connected, the slope of the first straight line (i.e., before the second well is put on production) corresponds to an equivalent fracture whose half-length is a portion of the total summation of individual fracture half-lengths depending on the permeabilities of individual fractures. This method, which also accounts for two-phase flow (gas, water), and pressure-dependent porosity and permeability, is successfully verified against fully-numerical simulation results, and its practical applicability is demonstrated with the same field case as the history match/forecasting models. Finally, machine learning (ML) algorithms, along with an optimization method, are employed to develop a history matching tool for three-phase flow of oil, gas and water associated with two communicating wells (staggered production). The basic concept used in ML algorithm training is that a change in the slope of the square-root of time plot for the first (parent) well occurs due to the second well coming on production. A dataset consisting of synthetic simulation cases is generated by varying some of the reservoir and fracture parameters to produce all the possible production scenarios for a two-well base model. After preprocessing the outliers, ML models are trained and tested. These models can generalize the relationship between the reservoir and fracture parameters and the square-root of time plot slope values for the parent well. The goal of developing a history matching tool is then attained by using the best performing ML model and an optimization algorithm which can estimate the reservoir and fracture parameters for a set of slopes obtained from the square-root of time plot of the parent well. Fundamentally, this dissertation advances RTA methods that can be applied to two wells that are in communication through hydraulic fractures.
Open Access
The Application of Fishbone Wells in Steam-Assisted Gravity Drainage
(2022-09) Edafiaga, Benjamin; Gates, Ian; Gates, Ian; Wong, Ron; Chen, Shengnan; Haddad, Amin; Hejazi, Hossein; Chen, Zhangxing
Apart from cost, major challenges facing the recovery of bitumen from Canadian oil sands are the amount of energy utilized per volume of bitumen recovered as well as the amount of greenhouse gas (GHG) emitted to the environment. The situation is even worse in reservoirs that are considered to be challenging or difficult-to-produce due to the reservoir geology. Steam-assisted gravity drainage (SAGD) is the primary in-situ recovery technique for bitumen recovery in Northern Alberta, Western Canada. Within the reservoir, steam chamber conformance is a major control on the efficiency, economic performance, and GHG emissions intensity of the process. There is a search for ways to significantly reduce the costs and emissions of SAGD. Multilateral wells possess the potential to contribute towards this goal. To date, different theoretical designs of multilateral wells have been proposed in literature. One of the most common designs studied is the fishbone well configuration. This configuration has large reservoir contact and thus enhances the productivity of the well. While the merits of the application of multilateral wells are well documented in lighter oil systems, an understanding of the best operating conditions for the use in oil sands reservoirs is poorly understood. The research documented in this thesis examines in detail how fishbone multilateral wells can be used to improve the performance of SAGD. In summary, the results demonstrate that fishbone well are able to improve steam chamber conformance and ultimately minimize cumulative steam-oil ratio (cSOR), maximize ultimate bitumen recovery, improve net present value (NPV), and reduce GHG emissions. Therefore, fishbone multilateral wells should be considered for future SAGD operations.
Open Access
Application of Machine Learning in Different Stages of Oil Reservoir Development
(2023-07) Wei, Liu; Chen, Zhangxing; Roman, Shor; Qingye, Lu; Haiping, Huang; Yuntian, Chen
Geological and oilfield big data is exponentially expanding. The traditional methods used to identify reservoirs and predict production cannot use historical information and new data effectively. The processes of well logging interpretation and pipeline non-destructive examination (NDE) are time consuming and subjective. Numerical flow simulation models do provide a relatively reliable and appropriate approach to conduct a reservoir analysis, but they are laborious and time consuming. In today’s big data environments, it is increasingly necessary to develop an effective and dependable technique to maximize the benefits of a growing data explosion and extract useful information within all the oilfield data. A machine learning method incorporates various algorithms that provide powerful functions in an oilfield. Massive static and dynamic data is put into training models to identify valuable features and learn nonlinear relationships between different variables and output targets. Advanced models using the benefits of machine learning (ML) will help operators to implement classification and/or prediction tasks. This study compares various ML methods applied to different stages from oil and gas exploration to transportation in oilfields: reservoir identification, prediction of production in new and old wells and non-destructive examination (NDE) of pipelines. These ML methods are proven useful and fast to resolve reservoir classification and production prediction challenges. This work provides a set of systematic ML methods and their respective pertinent predicting parameters providing useful experiences and references for industry and future relative research.
Open Access
Applications of Interactive Topographic Maps: Tangibility with Improved Spatial Awareness and Readability
(2019-07-02) Li, Hao; Sharlin, Ehud; Costa Sousa, Mario; Takashima, Kazuki; Chen, Zhangxing; Figueroa, Pablo; Willett, Wesley J.
Traditional flat topographic maps are difficult to understand due to the distortion and compromise of the 3-dimensional (3D) spatial representation when it is folded into lower-dimension media (e.g. 2D). During the process, the x-y coordinate of a location can be captured but its physical elevation must be transformed using some visualization techniques, resulting in noticeable cognitive effort in comprehending the original geometric and geographic properties of the original terrain. In this manuscript-based dissertation, I present a collection of my past publications that aim to increase the readability of topographic maps by restoring the original spatiality of the terrain - including the elevations - with a physical map representation and then superimpose additional data visualization on top of it. In this way, the entire terrain topology is kept in a scaled physical representation, allowing users to view it with natural human perceptions. Additionally, user gestures can be tracked in real-time as a sketch-based input to allow novel dynamic interaction of the map interface and data manipulation of the spatial information. Through the chapters, I present the aforementioned concept, named interactive topographic interface, along with a few applications of it in different academic and industrial environments. I also report the design and results of a user study that compares the interface with traditional flat topographic maps. In the long-term, I hope that research mentioned in this dissertation inspires future interactive physical cartography to not only improve map comprehension but also facilitate better spatial and situational awareness over the map interface, resulting in an evolved map usefulness.
Open Access
Catalytic Aromatization of Paraffin-Rich Oil under Methane Environment
(2018-09) Jarvis, Jack; Song, Hua; Chen, Zhangxing; Park, Simon S.
Naphtha fractions obtained from petroleum refinement contain an abundant mixture of hydrocarbons including paraffins, naphthenes, aromatics, and even olefins. n-paraffins are the largest constituents of such oils and are the most undesirable because of their poor octane values and low economic value as chemical feeds. Thus, scientific research aims to convert these components into more valuable components with higher octane numbers for fuels and/or high value chemical precursors used for chemical synthesis. Current naphtha reforming processes require an element of hydrocracking to reduce the number of larger carbon number components but hydrogen is expensive to obtain through the current process of steam reforming natural gas and so an alternative source of hydrogen is also desirable. One such source of hydrogen is methane, a naturally, occurring, and cheap alternative. However, the activation of methane, the most stable of the hydrocarbons, is difficult to achieve. This research aims at the conversion of naphtha feeds (rich in n-paraffins) to more valuable benzene, toluene, and xylenes (BTX) whilst using methane as a hydrogen source through heterogenous catalysis. Catalysts are screened to gauge those with the highest performance and then the effect of methane is also probed. This approach was conducted for two different fractions of naphtha as provided by the petrochemical industry with very different components. A model compound study was also conducted to enable a more comprehensive understanding of the processes involved during upgrading.
Open Access
Catalytic Bitumen Partial Upgrading using Methane
(2016) Luan, Yingqi; Song, Hua; Chen, Zhangxing; Yarranton, Harvey
It is highly desired to partially upgrade viscous heavy oil, to be transportable by pipeline. Conventionally, this is achieved by expensive catalytic hydrogenation under a hydrogen pressure of 15–20 MPa. In this thesis, it is reported that by using zinc and silver cation-modified HZSM-5 as the catalyst, methane can be activated at a relatively low temperature of 380 °C and a pressure of 5 MPa to efficiently upgrade heavy oil. The product is a partially upgraded crude oil which is more desirable for pipeline transportation and downstream refining. Before the evaluation of different catalysts, the reaction conditions optimization and better support identification is carried out. The catalyst with the best upgrading performance among all developed candidates comparison was 1 wt% Ag–10 wt% Zn/HZSM-5. This study opens a door for upgrading heavy oil with natural gas.
Open Access
Catalytic Conversion of Hydrocarbons to Valuable Chemicals and Methanotreating of Oxygenates to Fuel
(2023-05-02) Jarvis, Jack; Song, Hua; Chen, Zhangxing; Hu, Jinguang
The world is accelerating towards a gasoline fuel-free future and research focus is shifting towards alternative energy. The efficient use of remaining downstream fossil-fuel derived oil sources and effective treatment of renewable fuel sources has become imperative. Remaining fossil fuel sources like crude oil distillation and Fischer Tropsch products, which contain large amounts of n-paraffins, are no longer desirable as fuels because of their negative environmental impact. As such, they need to be valorized to valuable chemicals instead. This issue is addressed in this thesis by a thorough investigation of numerous hydrocarbons which can be found in such sources, including olefins, paraffins, and naphthenes. Their valorization to aromatics by heterogenous catalysis are investigated to provide a solution and use for remaining hydrocarbons derived from fossil fuels. Additionally, this thesis focuses on the treatment of bio-oils, a suitable fuel source replacement for fossil fuel-based fuels. Bio-oils can come from various sources, but they all have the same issue; they are high in oxygen content. This means energy density is low, acidity is high, and that the oil is thermochemically unstable. Hydrotreating is currently used to deoxygenate these feedstocks as it contributes to decarbonylation, decarboxylation, and saturation reactions. However, hydrogen is expensive, unavailable naturally, and environmentally unfriendly to synthesize as it is obtained predominantly from steam methane reforming. Direct use of methane for the deoxygenation of bio-oils (methanotreating) is investigated in this research. With carefully tailored catalysts, methane can be activated at low temperatures and pressures to provide hydrogen directly and contribute its carbon moiety to oxygen containing components in the product, highlighting the potential for methanotreating in the future of renewable fuels.
Embargo
Co-Injection of Non-Condensable Gas and Foam in SAGD using a Modified Well Configuration
(2023-12-19) Zhang, Yushuo; Maini, Brij B.; Chen, Zhangxing; Sarma, Hemanta Kumar; Achari, Gopal; Rao, Dandina Nagaraja
The purpose of this project is to evaluate the performance of a non-condensable gas (NCG) foam as an additive to the steam assisted gravity drainage (SAGD) process using the conventional as well as modified well configurations. Both laboratory experiments and numerical simulations were used in the study. For safety reasons, nitrogen gas was used in the laboratory experiments to form the foam. However, in numerical simulations, methane is used as the gas component of the foam. The purpose of foam in this process is to reduce the heat loss and to decrease the residual oil saturation. Modified well configurations are designed to enhance steam efficiencies in the target zones. SAGD experiments were conducted in linear sand-packs to evaluate the effects of NCG and Foamed NCG as steam additives on the oil recovery performance. The value of residual oil saturations under NCG or foamed NCG conditions were determined through history matching of these experiments with numerical simulation. Several different foaming agents were evaluated for their effectiveness in reducing the residual oil saturation and achieving high recovery factor. The best performing foaming agent NC160 was then evaluated in a linear physical model for its foam flow characteristics. The results of these tests were also history-matched with a thermal reservoir simulator to determine the foam flow characteristics that can be applied to field scale simulations. A numerical simulation study of Long Lake Pad 16 found that steam only SAGD operation in 10 years had a cumulative Steam Oil Ratio (cSOR) of 6.23 and the total oil production of 79,193 m3. However, the best performing case of foam assisted SAGD, using three horizontal wells configuration, reduced the cSOR to 3.94 and increased the total oil production to 85,068 m3. As expected, a foam insulation layer formed above steam chamber, which resulted in superior performance regarding steam efficiency. This field scale simulation study was based on the foam flow parameters determined through history matching of the lab-scale physical model tests.
Open Access
Comparative Evaluation of Electrical Heating Methods for Oil Sand Reservoirs
(2019-09-10) Ji, Dongqi; Chen, Zhangxing; Dong, Mingzhe; Huang, Haiping; Nasrabadi, Hadi; Harding, Thomas Grant; Hejazi, Seyed Hossein
For thermal heavy oil recovery, conventional steam injection processes are generally limited to reservoirs of relatively shallow depth, high permeability, thick pay zones and homogeneity. An alternative approach of applying electrical energy, including methods of electric heater, electrical resistance heating and electromagnetic heating, can 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 processes. However, in the current, the most widely used simulation method of electrical heating is the data coupling of two simulators, one is used for calculation of electrical heating and the other is used for calculation of a oil reservoir. The work in this thesis provides a single simulator that is capable of modelling all electrical heating processes for heavy oil and oil sands thermal recovery and the computational overhead and complexity of swapping data back and forth between two simulators has been omitted. In this work, a new numerical simulator is developed that handles the three electrical heating processes, such as electric heater, electrical resistance heating and electromagnetic heating. New models regarding the physical processes of the electrical heating methods have been derived and used for numerical simulation. The electric current balance was used for the modelling of electrical current flow in oil sands reservoirs with an appropriate treatment of electrical conductivity between neighbouring grids. A Helmholtz equation for the magnetic field by deformation of Maxwell’s equations is presented that makes it feasible to find electromagnetic field solutions for an inhomogeneous medium, such as a oil reservoir. Also, it has not been possible until now to model all three electrical heating processes in a single model and the work in this thesis enables a direct comparison of the different methods to be made. The feasibility of electrical heating in oil sands reservoirs is examined in two case categories: a) a horizontal well containing a heating source and b) a horizontal well-pair with heating sources located in both wells. Simulation results are compared in temperature, water saturation and electrical energy dissipation in the three electrical heating processes.
Embargo
Data-Driven Carbon Dioxide Enhanced Oil Recovery Models and their Applications
(2023-10-25) Ma, Haoming; Chen, Zhangxing; McCoy, Sean T.; Bergerson, Joule A.; Bryant, Steven L.; Clarkson, Christopher; Yin, Xiaolong
In the context of the 2050 net zero carbon emission goal to mitigate climate change, the demand for CO2 geological sequestration is substantially increasing. In the oil and gas industry, injecting CO2 has been proven as a mature technology to improve the oil recovery associated with permanent geologic carbon storage to meet the dual demands of energy consumption and emission reduction. Additionally, the revolutionary development of artificial intelligence provides a time-effective and accurate approach to forecast reservoir performance. The paradox of maximizing profitability while minimizing greenhouse gas (GHG) emissions has been heavily debated in recent years. This thesis attempts to address three challenges in the field of CO2-enhanced oil recovery (CO2-EOR) associated with carbon storage. In the first part, a generalized reduced-form model is developed based on numerical simulation and statistical nonlinear regressions. Applied to the Weyburn oil field production data, the proposed model demonstrates its capability to forecast the reservoir performance within 5% tolerance in terms of an incremental oil recovery factor, net CO2 retention, and net CO2 utilization. Three major contributions are made to the existing literature: (1) the predictive capabilities have been proven by combining the early-stage field production data and the proposed generalized reduced-form model; (2) the statistical correlations are illustrated with respect to CO2 injection rather than the total injected fluid compared to the previous investigation; (3) the model is developed based on numerical results with the field data validation, which fills the research gap that statistical models cannot be validated owing to the lack of empirical data. In the second part, three machine learning algorithms are studied to further improve the data-driven models by (1) establishing a large dataset based on reservoir simulations; (2) capturing the field variabilities and reducing the real-time production data as inputs, which are two major limitations of applying reduced-form models to predict the reservoir performance. Results from this part demonstrate that the computational time can be reduced by 700 to 5000 times with an optimal artificial neural network (ANN) model compared to the reservoir simulation approach. Although machine learning has been deployed to the oil and gas industry in recent years, two major challenges remain: (1) most studies are developing site-specific data-driven models based on simulation, which makes it difficult to apply them to other fields; (2) owing to confidentiality reasons, little production data is accessible. This part differs from other studies as it resolved the limitations of statistical models and introduced a framework to develop a generalized data-driven model with the field production data validation. As such, it can be applied to a variety of oil fields to quantify the CO2-EOR potential. Furthermore, the proposed data-driven model has been applied to understand the economic and environmental concerns of CO2-EOR from the entire field scale. In the third part, the potential economic and environmental outcomes are analyzed by combining the predicted reservoir performance with the data-driven models. It is found that when utilizing CO2 from industrial sources, varying the WAG ratio can result in a minimum levelized cost and net emission because increasing and decreasing the WAG ratio can both result in an increasing of a levelized cost of oil production (LCOP) and net emission E_net, but through different mechanisms. When the WAG ratio increases, LCOP increases because of water usage and CO2 recycling and E_net increases owing to the GtG (gate-to-gate) emission. When the WAG ratio decreases, LCOP increases because of CO2 purchase and E_net increases owing to the upstream emission. The trade-off can be estimated for the scenario of CO2 from DAC (direct air capture), which is -1.40 kgCO2eq/$ for the Weyburn oil field because the WAG ratio drives LCOP and E_net in opposite directions. In addition, the weighted factors are used to determine the driven mechanisms as well as the prospective economic and environmental outcomes resulting from the varying market conditions. As a result, CO2-EOR initiatives can be divided into four categories based on the operators' choice of a CO2 source, as current climate policies are insufficient to deploy DAC. Negative emission potential in CO2-EOR has been demonstrated to require a high net utilization factor, CO2 from DAC, and sufficient carbon revenues for operators. Using captured CO2 from the air may result in negative emissions, but insufficient financial incentives exist to encourage this practice.
Open Access
Design of Anthropomorphic Interfaces for Autonomous Vehicle-Pedestrian Interaction
(2023-01) Wei, Wei; Sharlin, Ehud; Chen, Zhangxing; Sharlin, Ehud; Oehlberg, Lora; Somanath, Sowmya
Autonomous Vehicle (AV) technology promises to revolutionize human life. The promise of AVs includes reduced highway congestion, more efficient energy usage, and cheaper goods and services. However, without careful design, removing human drivers from vehicles will eliminate the natural communication channels which enable pedestrians to navigate safely. This thesis aims to design, present, and study anthropomorphic interfaces for autonomous vehicles, with the objective of enabling AVs to communicate with pedestrians through non-verbal cues. Non-verbal human communication is vital in human relationships. People use non-verbal communication when speech is impractical, such as when interacting with vehicles. When looking into ways in which AVs can use non-verbal communication to interact with pedestrians, we were inspired by the prospect of using anthropomorphic interfaces. This concept is well explored in Human-Robot Interaction (HRI) but has not been investigated in the context of AVs. For this thesis, we explored the design of anthropomorphic interfaces for autonomous vehicles. First, we proposed three types of anthropomorphic interfaces for AVs: facial expressions, hand gestures, and humanoid torsos. We developed a design space for each category using sketches and a low-fi prototype. Then, to research the benefits and limitations of anthropomorphic AVs, we implemented our AV interfaces in a Virtual Reality (VR) environment and developed two testbeds to evaluate their feasibility and scalability. Finally, we conducted two studies using the two testbeds. We investigated the study results using immersive analytics alongside traditional methods and revealed that anthropomorphic AVs could be helpful in AV-pedestrian interaction when designed by specific guidelines. Since we studied anthropomorphic AVs in VR, we were interested in the possibilities of analyzing the data of our study in an immersive environment. We designed a VR prototype specifically to analyze the data collected from the anthropomorphic AV study. The prototype provided basic immersive analytics features for the AV study data. We conducted an expert session with two domain experts to evaluate our immersive analytics prototype. The study contributed insights into the opportunities and challenges of utilizing immersive analytics to analyze AV studies.
Open Access
Development of a Standalone Compositional Simulator for Modelling Multiphase Flow and Temperature Distribution Along Wellbore
(2019-12) Xiong, Wanqiang; Chen, Zhangxing; Azaiez, Jalel; Chen, Shengnan; Qin, Guan; Swishchuk, A. V.
Well modeling of multiphase flow and temperature flow along a wellbore has wide applications in the petroleum industry especially in unconventional oil and gas recovery processes. Also, wellbore modeling can be applied in a geothermal well for optimizing production parameters. The main research works completed in this study include building mathematical equations for wellbore modeling and development of a standalone wellbore simulator. At first, a series of mathematical equations are built for wellbore modeling of fluid flow in tubing or annulus, heat loss to a surrounding formation and heat transfer in the formation. Then methods and workflows are determined for key steps in wellbore simulator development including discretization, a grid system, a solution method and a liner equation solver. A standalone compositional wellbore simulator is developed. Validation works against CMG SAM, CMG Flexwell and Eclipse Multi-Segment Well are conducted afterwards. Different scenarios have been modeled by the wellbore simulator that include hot water injection, steam injection, SAGD circulation, SAGD injection, multiphase well production, steam-solvent co-injection, liquid CO2 injection for a shale gas reservoir and geothermal well production. Different well trajectories and structures are handled such as vertical, deviated and horizontal wells, and the wells consisted of one or dual tubing strings. New correlations for more accurate heat loss calculations are regressed in this study based on CFD Fluent simulation and they can better estimate the convection heat transfer in annuli space with single tubing or dual-tubing strings. Also, a semi-numerical method and a fully numerical method for heat loss calculations are proposed. The semi-numerical method consists of heat loss through wellbore components calculated by correlations and heat loss in a surrounding formation numerically simulated, and the fully numerical method performs simulation for heat transfer both in wellbore components and the surrounding formation.
Open Access
Enhancing Hydrocarbon Recovery and Sensitivity Studies in Tight Liquid-Rich Gas Resources
(2017) Wang, Min; Chen, Shengnan; Chen, Zhangxing; Maini, Brij
Unconventional tight reservoirs refer to the formations with a permeability ranges from 0.001 to 0.1 millidarcy. Horizontal drilling coupled with multistage hydraulic fracturing is required in these formations to achieve economic production rates. Recovery factor in tight gas formations is typically less than 25% of the original gas in-place. Such low recovery is a strong motivation to investigate the application of enhancing hydrocarbon recovery methods in these reservoirs. In this study, enhanced hydrocarbon recovery methods are investigated for a Montney liquid rich gas reservoir, located in the Western Canadian Sedimentary Basin. Firstly, a heterogeneous reservoir model is built and history-matched based on the production data collected from the field. Production performance of three EHR methods including cycling gas injection, CO2 flooding and water injection are then compared and their economic feasibility are evaluated. Sensitivity analysis of operational and geological factors including primary production duration, bottom hole pressures (BHP) during primary production and EHR process, pressure-dependent matrix permeability, non- Darcy effects and hydraulic fracture conductivity is conducted and their effects on the well production performance are studied. Experimental design is adopted to further study the mechanism and optimize the enhancing recovery process by cyclic gas injection and CO2 injection. Results show that both cumulative oil and gas production are increased with fluid injection compared to primary depletion methods. In addition, cyclic gas and CO2 flooding is more feasible for the ultra-low unconventional tight gas reservoir than water flooding due to the water injection difficulty and low sweep efficiency in the reservoir. Cycling gas injection leads to both a higher gas and oil recovery and lower injection cost due to the on-site available gas source and minimal transport/purchase costs, gaining more economic benefits than that of CO2 flooding. Thus, it can be concluded that cyclic gas flooding in tight liquid rich gas reservoirs with hydraulically stimulated fractures could be a good way to enhance oil and gas production. Optimization study results indicate that two injection wells, short primary production time, high primary BHP and injection BHP, short injection time and low later period BHP lead to an optimal scheme of cyclic gas flooding and CO2 flooding methods.
Open Access
Experimental and Numerical Simulation of Combined Enhanced Oil Recovery with In Situ Upgrading in a Naturally Fractured Reservoir
(2016-01-25) Chávez Morales, Silvia María; Pereira-Almao, Pedro; Maini, Brij; Chen, Zhangxing; Mehta, Sudarshan A.; Lines, Laurence R.; Domínguez Esquivel, José Manuel
The purpose of this research work is to show laboratory experiments conducted at 1500 psi and 350 C, experimentally simulating a reservoir located in the Gulf of the Mexico. The experiments conducted used a novel process that involved a hot fluid to be injected with an ultra-dispersed nano catalyst. The results obtained showed that API gravity can be improved permanently as well as its viscosity, with the advantage of no coke or solid deposits formation. Laboratory analyses showed that by using this new process it is possible to enter into the matrix zone, expelling at least partially the oil confined inside. As a consequence of the temperature increase, matrix rock may expand and expel its oil; while temperatures decrease, the pores in the matrix could be contracted, generating additional oil expulsion from this area. As a consequence of this expansion-contraction in the reservoir the reserves could be increased. Also, a change in the permeability appears due to the temperature increases. The present study was focused in oil matrix extraction and in situ oil upgrading from a naturally fractured reservoir of heavy oil as a result of a hot fluid injection with nano catalyst. Moreover, the effects of capillary pressure, mobility, viscous effects, wettability, and gravitational drainage on the process were analyzed. Another aspect that was studied is how the thermal expansion generated as a consequence of the process could expel the oil confined in the matrix.
Open Access
An Exploration of Numerical Methods for Thermally-Induced Convection in Storage Tanks and Films
(2021-07-19) Pletnyov, Fedir; Jeje, Ayodeji; Azaiez, Jalel; Trifkovic, Milana; Chen, Zhangxing; Mohamad, Abdulmajeed; Upreti, Simant Ranjan
The study is on conditions for onset of convection, the transient and steady states velocity and temperature patterns in 2D and 3D coordinates for fluids in vertical cylindrical storage tanks. The Navier-Stokes and energy equations are formulated using vorticity, stream function (2D) / vector potential (3D) and temperature as the dependent variables, with and without dynamic free surfaces. Solving the transport equations and exploring conditions for multiple solutions, of which only certain patterns may be realizable, is time-consuming. The development of computationally efficient algorithms is crucial to reduce computation overheads. In this work, software package for the simulation of 2D and 3D problems with parallel implementation was developed. For 2D simulation, the numerical methods in package include Gauss-Seidel with Red-Black (GS-RB) ordering, Alternating Direction Implicit with Fast Fourier Transform (ADI + FFT) and with Evolutionary Factorization with Logarithmic time step (ADI+EFL), Geometric Multigrid (GMG), Jacobian Free Newton-Krylov (JFNK). For 3D simulation, GS-RB (parallel) and ADI-EF (Samarskii-Andreev) with FFT for the vector potential equations were developed. The non-linear systems of PDE were approximated using central (CFD) and monotonic - conservative (MCFD) finite differences schemes. The boundary conditions for vorticity in 3D were derived using the one grid step methods for a second order accuracy. For 2D simulations, the Polezhaev - Gryaznov method was extended for the axisymmetric domain. These approaches significantly improved CPU performance. The investigation was restricted to one component liquids, and cylindrical tanks with evaporation at the free surfaces were of primary interest. Specification of appropriate boundary conditions for the free surface is difficult as the interface may be deformed due to the inertia of ascending and descending streams and gradients of the interfacial tension. The contour is unknown a priori. In lien of detailed calculations, evaporation was incorporated through the application of Hashemi-Wesson’s empirical correlation between vaporization rates and the local surface temperature. To understand the interfacial dynamics and to develop the numerical scheme for modeling evolving surface contours, deformation of thin liquid layers locally heated along strips was explored.
Open Access
Formaldehyde-MEA Triazine Based Hydrogen Sulfide Scavenger Behavior Study and Applications in the Oil and Gas Industry
(2020-08-03) Du, Steven Yuhai; Chen, Zhangxing; Song, Hua; Sumon, Kazi Z.
Hydrogen sulfide (H2S) is an environmentally hazardous, corrosive and toxic gas in oil and gas productions. It must be removed to meet the pre-determined specification. There are many chemicals being used in the gas sweetening process. Formaldehyde-MEA Triazine is one of the common H2S scavengers in use. The objective of this research was to review different chemistries and field applications applicable as H2S scavengers in oil and gas, understand the Formaldehyde-MEA Triazine’s properties and behaviors in the sweetening process, and determine technical achievements on custom-made finished blends for successful field applications. The Formaldehyde-MEA Triazine is synthesized by the reaction of formaldehyde and monoethanolamine (MEA). Triazine, water, free formaldehyde or free MEA are fundamental components. Each ingredient has its unique function in process scavenging H2S. There are three steps for triazine’s chemical reaction absorbing H2S. Free formaldehyde can boost the capacity and breakthrough efficiency. However, it makes triazine degradation for shorter shelf life as well. A sufficient water amount, minimum 40% more than triazine, is a must to avoid pre-mature breakthrough in bubble tower uses. Triazine based H2S scavengers are custom made blends for field use. Besides the Formaldehyde-MEA Triazine, other factors such as the solvent package, other additives, plant synthesis, low temperature operation, spent solids treatment, sour liquid sweetening and capacity monitoring are all important considerations for successful H2S sweetening applications in the western Canadian oil and gas industry.
Open Access
Geological Susceptibility to Hydraulic Fracturing-Induced Seismicity in the Montney Formation
(2022-05) Wozniakowska, Paulina Gabriela; Eaton, David WS; Gilbert, Hersh Joseph; Trad, Daniel Osvaldo; Pedersen, Per Kent; Chen, Zhangxing; Eberhardt, Erik
This thesis focuses on induced (anthropogenic) seismicity related to hydraulic fracturing operations in the Montney Formation - a geological unit of Triassic age located in the Western Canada Sedimentary Basin. Originally a conventional oil and gas play, the Montney Formation is currently one of the most prolific unconventional resource plays worldwide. Documented cases of induced seismicity in the Montney play occur in distinct clusters, indicative of local variability of factors influencing the seismic activation potential (SAP). Notably, virtually all induced seismicity related to hydraulic fracturing, to date, has occurred in British Columbia despite similar levels of industrial activity in Alberta. This implies that geological trends may have a more significant impact on SAP than operational factors. This thesis presents several new methodologies for investigating the complex interplay between subsurface conditions and induced seismicity distribution. Three independent workflows, based on machine learning-based analysis, structural interpretation, and statistical inference, respectively, were developed to evaluate hypotheses regarding the influence of geological, geomechanical and structural controls of hydraulic fracturing-induced seismicity in the Montney Formation. First, a machine learning model was used to identify areas within the Montney that are characterized by the highest geological susceptibility to induced seismicity. The results suggest that distance to the Cordilleran deformation front and injection depth are the most important factors influencing the observed seismicity trends. Next, a multi-step workflow based on trend-surface analysis combined with geophysical data interpretation allowed major structural trends (structural corridors) to be delineated throughout the Montney play. The results of machine learning and structural interpretation were used to formulate hypotheses regarding geological factors influencing observed cluster characteristics of seismicity in the Montney. These hypotheses were independently tested using SimSeis – a newly developed tool for statistical inference based on a stochastic simulation approach. Using this tool, sets of synthetic catalogs are generated according to assumed spatial relationship(s) between geological susceptibility and/or mapped structural corridors and further compared against a Null hypothesis, corresponding to a random spatial association of induced seismicity with hydraulically fractured wells. While each of the alternative models performed significantly better than the Null hypothesis, a machine-learning model based on geological susceptibility achieved the best results. SimSeis is customizable and can be applied to investigate mechanisms that influence the distribution of induced seismicity distribution in other unconventional plays and thus enhance currently existing seismic-risk mitigation strategies.
Open Access
Immiscible Radial Newtonian and non-Newtonian Flow Displacements in Porous Media
(2019-09-12) Lee, Young Hoon; Azaiez, Jalel; Gates, Ian Donald; Chen, Zhangxing; Nowicki, Edwin P.
Immiscible flows that involve radial displacements of shear-thinning or shear-thickening fluids by a Newtonian fluid in a homogeneous porous medium, are modeled numerically. The interfacial instabilities are tracked in time for different values of the rheological parameters, namely the Deborah number (De) and the power-law index (n) and are characterized through the effective number of fingers and the finger area density. The results of the study reveal that the effects of these two parameters on the instability are not monotonic, and it is found that the flow is least unstable for some critical value of either De or n. The dependence of these critical values in particular on the mobility ratio (M) and Capillary number (Ca) is analyzed. It is found that when all other parameters are fixed, the critical Deborah number (Dec) increases as the power-law index increases in shear-thinning fluids or decreases in shear-thickening ones. Similarly, the critical power-law index (nc) increases with increasing (decreasing) Deborah number in shear-thinning (shear-thickening) flows. Furthermore, both critical parameters are found to vary monotonically with the mobility ratio, with the dependence most noticeable at small values of M. Their variation with the Capillary number is however non-monotonic reaching an extremum at an intermediate value of Ca. An examination of the rate of shear strain at the interface reveals that it consistently shows the smoothest variation and smallest average value at the critical parameter. In addition to non-Newtonian flow displacements, immiscible radial displacement flows between two Newtonian fluids in a non-homogeneous porous media are also examined numerically. The non-homogeneous porous medium is modeled to vary periodically in the radial direction. Simulations are performed for different values of the Capillary number (Ca) and the mobility ratio (M) varying the frequency of the periodic permeability. The results show that the periodic permeability has negligible effects on the finger structures when the Capillary number and the mobility ratio are small. However, the instability of an interface can be noticeably enhanced in a higher frequency periodic permeability field when the Capillary number and the mobility ratio are large enough.
Open Access
Impact of Biofilm Formation in Microbial Enhanced Oil Recovery Performance
(2018-12-19) Cao, Jiayi; Chen, Zhangxing; De La Hoz Siegler, H.; Shor, Roman J.; Hejazi, Seyed Hossein
The complex trade-off between the effects of biosurfactant generation and biofilm growth has been a challenge for successful simulation and field-scale implementation of microbial-enhanced oil recovery (MEOR). In this work, a two-phase, two-dimensional MEOR model is developed, including effects from interfacial tension, porosity and permeability reduction. Empirical models are validated against experimental data. The model is discretized through two-point flux-approximation, and the numerical solution is validated against the two-phase Buckley-Leverett equation. The model shows a good match with previous MEOR simulation results. Monte Carlo simulation-based sensitivity analyses of various operational parameters in a homogeneous reservoir highlight the importance of bacteria injection concentration, which can result in 16% difference in oil recovery by minimizing biofilm formation and optimizing biosurfactant production. Variation in biosurfactant critical micelle concentration and biofilm density is found to increase oil recovery by up to 15%, indicating that both strain selection and injection concentration should accommodate reservoir rock and fluid properties.