Asia

Abstract K Sand of Field N is highly permeable and has variation in viscosity ranging from 5cP to 120cP. K sand has been producing since 1969 and has recovered about 34%. It produces with strong edge water drive mechanism. The primary recovery is about 20-22% where viscosity is 50 to 120cP, produces oil with 90% Water cut. The early rise in water cut was because of water fingers due to adverse mobility ratio. The poor areal sweep has affected the primary recovery which necessitated the application of suitable EOR. The Polymer EOR scheme was conceptualised to address adverse mobility ratio and enhance the sweep efficiency to maximize oil production. The project area was selected for polymer flood considering the moderate primary recovery due to poor areal sweep, structurally up dip area to avoid polymer dilution through aquifer, sand continuity and good reservoir facies. In the first phase, 8 inverted five spot polymer patterns were commissioned. Injection rate is 50 m/d/well and polymer viscosity is 27cP considering the mobility ratio and high dilution effects. The paper explains the efficient planning, monitoring activities, innovative approach to execute the scheme and mid-course correction to improve the performance of the project. The optimised project has resulted in multi-fold increase in production in challenging reservoir conditions. The project is being monitored using pattern balancing based on the production performance monitoring, polymer concentration mapping, historical exploitation, revival of vintage wells, recompletion, and perforation optimization and Injection fluid quality control. The down dip (towards aquifer) loss of polymer is controlled by monitoring liquid rates and polymer presence in the offset wells. Also, to assist the water-cut reduction in updip wells, higher drawdown strategy is implemented for polymer-bank movement in the structural highs. Monitoring of injection fluid through down hole sampling is used to ensure desired quality of polymer. Efficient monitoring of the project has resulted in production enhancement from 100tpd to 260tpd with peak production of 300tpd from targeted area. The innovative approach is to execute the project on fast track through hired injection services. This approach has helped in early realisation of oil and generation of data for preparation of expansion of polymer scheme.

OnePetro

doi: 10.2118/214379-MS

SPE

SPE-214379-MS

SPE EuropEC - Europe Energy Conference featured at the 84th EAGE Annual Conference & Exhibition

Country: Asia > India (0.83)

Industry: Energy > Oil & Gas > Upstream (1.00)

Oilfield Places:

Asia > India > Rajasthan > Cambay Basin (0.99)
Asia > India > Gujarat > Cambay Basin (0.99)

SPE Disciplines: Reservoir Description and Dynamics > Improved and Enhanced Recovery > Chemical flooding methods (1.00)

Technology: Information Technology (0.66)

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Development of a Deterministic Total Organic Carbon (TOC) Predictor for Shale Reservoirs

Khan, Mohammad Rasheed (SLB) | Kalam, Shams (King Fahd University of Petroleum & Minerals) | Asad, Abdul (SPRINT Oil & Gas services) | A. Abu-khamsin, Sidqi (King Fahd University of Petroleum & Minerals)

OnePetroJune, 2023

Abstract Unconventional reservoirs like shale oil/gas are expected to play a major role in many unexplored regions, globally. Shale resource evaluation involves the estimation of Total Organic Carbon (TOC) which correlates to the prospective capability of generating and containing hydrocarbons. Direct measurement of TOC through geochemical analysis is often not feasible, and hence researchers have focused on indirect methods to estimate TOC using analytical and statistical techniques. Accordingly, this work proposes the application of artificial intelligence (AI) techniques to leverage routinely available well logs for the prediction of TOC. Multiple algorithms are developed and compared to rank the most optimum solution based on efficiency analysis. Support Vector Regression (SVR), Random Forest (RF), and XGBoost algorithms are utilized to analyze the well-log data and develop intelligent models for shale TOC. A process-based approach is followed starting with systematic data analysis, which includes the selection of the most relevant input parameters, data cleaning, filtering, and data-dressing, to ensure optimized inputs into the AI models. The data utilized in this work is from major shale basins in Asia and North America. The AI models are then used to develop TOC predictor as a function of fundamental open-hole logs including sonic, gamma-ray, resistivity, and density. Furthermore, to strengthen AI input-output correlation mapping, a k-fold cross-validation methodology integrating with the exhaustive-grid search approach is adopted. This ensures the optimized hyperparameters of the intelligent algorithms developed in this work are selected. Finally, developed models are compared to geochemically derived TOC using a comprehensive error analysis schema. The proposed models are teted for veracity by applying them on blind dataset. An error metrics schema composed of root-mean-squared-error, and coefficient of determination, is developed. This analysis ranks the respective AI models based on the highest performance efficiency and lowest prediction error. Consequently, it is concluded that the XGBoost and SVR-based TOC predictions are inaccurate yielding high deviations from the actual measured values in predictive mode. On the other hand, Random Forest TOC predictor optimized using k-fold validation produces high R values of more than 0.85 and reasonably low errors when compared to true values. The RF method overpowers other models by mapping complex non-linear interactions between TOC and various well logs.

OnePetro

doi: 10.2118/214383-MS

SPE

SPE-214383-MS

SPE EuropEC - Europe Energy Conference featured at the 84th EAGE Annual Conference & Exhibition

Country:

Asia (0.90)
North America > Canada (0.29)
Europe > Austria (0.28)

Geophysics: Geophysics (0.46)

Industry: Energy > Oil & Gas > Upstream (1.00)

Oilfield Places:

North America > United States > South Dakota > Williston Basin > Bakken Shale Formation (0.99)
North America > United States > North Dakota > Williston Basin > Bakken Shale Formation (0.99)
North America > United States > Montana > Williston Basin > Bakken Shale Formation (0.99)
(6 more...)

SPE Disciplines:

Reservoir Description and Dynamics > Unconventional and Complex Reservoirs > Shale oil (1.00)
Reservoir Description and Dynamics > Unconventional and Complex Reservoirs > Shale gas (1.00)
Reservoir Description and Dynamics > Formation Evaluation & Management > Open hole/cased hole log analysis (1.00)
Data Science & Engineering Analytics > Information Management and Systems > Artificial intelligence (1.00)

Technology: Information Technology > Artificial Intelligence > Machine Learning > Statistical Learning > Support Vector Machines (0.87)

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Sun Powered Green Hydrogen - A Comparative Analysis from the Kingdoms Of Morocco and Saudi Arabia

Szemat-Vielma, Waldemar (SLB) | Scheibz, Jurgen (Texplor Austria) | Kasraoui, Nihad (CEPSA) | Al-Omar, Faisal (K.A.CARE)

OnePetroJune, 2023

The renewable energy sector, particularly the solar PV generation, is to play a key role in the energy transition and decarbonization process and the green hydrogen production is a subsequent element of this decarbonization process as a clean energy carrier. When power output from these renewable installations exceeds the grid requirements, instead of stopping the energy generation, that power surplus can be used to produce hydrogen by electrolysis process. Despite being a technically simple process to produce via electrolysis, fuel cost and equipment are the two most significant economical elements to consider as part of the LCOH equation and act as economical boundary conditions. Combining an in-depth analysis while applying the financial modeling toolbox, this project has evaluated specific conditions for solar PV installations in Morocco and Saudi Arabia markets in terms of a techno-economic analysis for a potential investment for green hydrogen production in 2021 as well as near future projections in 2023 and 2025. The most potential application of green hydrogen production and usage is to decarbonize heavy industries (e.g., cement and steel) that cannot be electrified but this will require an extensive transport infrastructure with low-cost incidence for the green hydrogen to be an economically viable solution. Near future projects will require public funding in the form of grants or tax redemption to scale up to economical maturity. After carrying out a detailed financial modeling and a discounted cash flow valuation model, the resulting LCOH for Morocco is $3,2695/kg while Saudi is $1,5757/kg as of the end of 2021 with a projected reduction to reach $2,3678/kg and $1,4417/kg respectively in 2025, which means that by 2025 both countries will be below the $1,5-2,5/kg green hydrogen threshold, on a competitive level with fossil fuels, enabling both countries to grasp unique commercial opportunities to lead the implementation of a green business models towards a hydrogen economy, and eventually a net zero world. The paper will elaborate on the rational driving the need for green hydrogen, will elaborate on the geopolitical framework supporting this emerging business and dives in with the techno-economic analysis while creating a 2023-2025 look-ahead. 2 SPE-214375-MS

OnePetro

doi: 10.2118/214375-MS

SPE

SPE-214375-MS

SPE EuropEC - Europe Energy Conference featured at the 84th EAGE Annual Conference & Exhibition

Country:

Asia > Middle East > Saudi Arabia (1.00)
Africa > Middle East > Morocco (1.00)

Genre: Financial News (0.34)

Industry: Energy > Renewable > Hydrogen (1.00)

SPE Disciplines:

Management > Asset and Portfolio Management (1.00)
Health, Safety, Environment & Sustainability > Sustainability/Social Responsibility > Sustainable development (1.00)
Health, Safety, Environment & Sustainability > Environment > Climate change (1.00)

Technology: Information Technology (0.46)

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Business Model of Carbon Capture and Storage (CCS) Projects for High-CO2 Fields

OnePetroJune, 2023

Abstract High-CO2 gas fields present a dilemma to Host Government wanting to both ensure security of supply and achieve net zero aspiration. While carbon capture and storage (CCS) technology holds promise of technical feasibility to unlock these fields, its commercial success ultimately hinges on the choice of an appropriate business model. This study compares the economics of the traditional business model i.e., CCS as part of the upstream petroleum operation dedicated to a Production Sharing Contract (PSC) vs. the alternative business model i.e., a regional CCS hub separately managed by a Special-Purpose Vehicle (SPV). To maximize the return on its investment in a gas value chain, Host Government aims to minimize the upstream cost of gas (COG), which in turn comprises the technical cost, fiscal/tax charge, and cost of capital components. Thus, in this paper, the business models are compared in terms of their COG, and the reasons for the differences are further analyzed by looking at the drivers affecting the components. To illustrate the comparison numerically, synthetic technical data based on several recent CCS projects are evaluated under Malaysian petroleum fiscal arrangement and tax regime. The scope of the CCS projects contemplated in this study is restricted to managing the CO2 inherent in upstream high-CO2 gas fields. The paper finds that the alternative business model outdoes the traditional in several ways. The economies of scale of a hub design optimize capital expenditure, while utilization by multiple users reduces hub operator’s risk, potentially lowering tariff. The SPV can better realize tax incentives and also benefit from a lower tax rate. In PSCs where cost recovery provisions prioritize operating expenditure over capital expenditure, upstream Contractors may prefer paying tariff per usage rather than building their own CCS facility up front. Access to cheaper financing from environmental, social, and governance (ESG) investors and government agencies, coupled with the perception of lower business risks, should also translate into a lower cost of capital. There are various spin-offs and qualitative benefits too. While the paper affirms the intuitive expectation that the alternative business model generally surpasses the traditional, it also cautions that the optimal choice may switch beyond certain thresholds (number of fields, distance between PSCs, volume of CO2, etc.). In addition to the between-model selection problem, the paper also discusses within-model fine tunings and optimization. This paper lays out important caveats and considerations that might be of interest to petroleum authority and government policymakers tasked with the development of business model for upstream CCS projects.

OnePetro

doi: 10.2118/214359-MS

SPE

SPE-214359-MS

SPE EuropEC - Europe Energy Conference featured at the 84th EAGE Annual Conference & Exhibition

Country:

Asia (1.00)
Europe (0.93)
North America > United States (0.68)

Genre: Research Report > New Finding (0.34)

Industry: Energy > Oil & Gas > Upstream (1.00)

SPE Disciplines:

Reservoir Description and Dynamics > Storage Reservoir Engineering > CO2 capture and sequestration (1.00)
Health, Safety, Environment & Sustainability > Environment > Climate change (1.00)

Technology: Information Technology > Artificial Intelligence (0.34)

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Case Study of the Use of a Digital Twin for Leak Detection and Quantification in Underground Gas Storage Wells

Baronio, Emanuele (Snam Spa) | Abdo, Elia (Snam Spa) | Mauro, Stefano (Politecnico di Torino) | Troise, Mario (Politecnico di Torino) | Salamina, Laura (Politecnico di Torino)

OnePetroJune, 2023

Abstract Underground gas storage (UGS) are essential components in energy security. However, UGS wells present a complicated and delicate combination of elements where ensuring safe and secure functionality over long periods is paramount. Today, with the advancement of continuous remote monitoring and digitalization, evaluating the integrity of UGS wells has become quicker and more efficient. This paper showcases how a digital twin is used to evaluate and forecast the link between leaks and temperature and pressure trends in a UGS well, allowing the identification and quantification of defects and, subsequently, well barrier integrity. UGS wells present additional criticalities with respect to normal production wells due to its longer life span and the repetitive production and injection cycles. This makes early and accurate leak detection essential for a safe management of the well barriers. The proposed digital twin has been developed using material and energy balances and considering each annulus as a separate control volume. Each control volume can exchange heat and mass through predesigned barriers. Simulating evolution in time of pressure and temperature in the control volumes., and comparing results with data from field, allows the identification of position and size of leaks. A genetic algorithm is applied to optimize placement of leaks on their specific barriers. The system aims to identify the position and dimension of possible leaks by matching historical pressure, temperature, and flow data. Once a leak is identified, a risk assessment is conducted to evaluate the overall integrity of the well. If the status of the well is found to be critical enough, an intervention may be planned. The system has been in use for little over a year and has shown great potential in accurate and efficient identification of leaks. This has accelerated the process of well integrity evaluation and allowed timely interventions on wells that required it. On the other hand, the process has highlighted cases where previous assumptions about leak location and size were corrected using the digital twin, therefore reducing the costs of interventions. Finally, the model showcased a clear readiness for predictive capabilities aimed to select, plan and design fit for purpose mitigating actions. This paper highlights the power that a digital twin can present leveraging field data with advanced algorithms. The paper also showcases workflows that allow convenient, efficient, and timely evaluation of well integrity, which leads to safer operating conditions and lower operational costs.

OnePetro

doi: 10.2118/214357-MS

SPE

SPE-214357-MS

SPE EuropEC - Europe Energy Conference featured at the 84th EAGE Annual Conference & Exhibition

Country:

Europe (0.68)
North America > United States (0.47)
Asia > Middle East > UAE (0.29)

Industry: Energy > Oil & Gas > Upstream (1.00)

SPE Disciplines:

Reservoir Description and Dynamics > Storage Reservoir Engineering > Natural gas storage (1.00)
Health, Safety, Environment & Sustainability (1.00)
Data Science & Engineering Analytics > Information Management and Systems (1.00)

Technology:

Information Technology > Data Science > Data Mining (0.88)
Information Technology > Artificial Intelligence (0.67)

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AI Grid Design for Fast Reservoir Simulation

Nghiem, Long (Computer Modelling Group Ltd.) | Dang, Cuong (Computer Modelling Group Ltd.) | Nguyen, Ngoc (Computer Modelling Group Ltd.) | Yang, Chaodong (Computer Modelling Group Ltd.) | Luo, Jia (Computer Modelling Group Ltd.)

OnePetroJune, 2023

Abstract Reservoir simulators based on physics provide the most accurate method for predicting oil and gas recovery, in particular from waterflood and EOR processes. However, detailed full-field simulation can be computationally demanding. In recent years, there have been attempts in accelerating reservoir simulation by combining simplification of the gridding requirement with data-driven approaches while maintaining the full physics. One such approach is the physics-based data-driven flow network model where 1D or 2D grids connecting the wells are configured and simulated. The parameters of the flow network model are then tuned to match full 3D simulation or field-data. Even though the grid has been simplified, a large number of parameters are needed to reproduce the 3D simulation results. In this paper, an approach similar to the flow network model is presented. The main contribution of this paper is the parameterization of the gridding process between the wells such that a minimal number of parameters are needed. Essentially, the grids between the wells are configured to model accurately the flow behavior. The corner-point grid geometry is kept so that current simulators could be used with the proposed method. In this paper, the grid geometry is determined with AI methods for one waterflood run. The grid could be used subsequently for waterflood with widely different injection/production scenarios and even for chemical flood. The ability of the approach to derive the grid from a single waterflood run is another significant contribution of this paper.

OnePetro

doi: 10.2118/214354-MS

SPE

SPE-214354-MS

SPE EuropEC - Europe Energy Conference featured at the 84th EAGE Annual Conference & Exhibition

Country:

North America > United States (0.30)
Europe > Austria (0.28)
Asia > Middle East > Israel > Mediterranean Sea (0.24)

Industry: Energy > Oil & Gas > Upstream (1.00)

SPE Disciplines:

Reservoir Description and Dynamics > Reservoir Simulation (1.00)
Reservoir Description and Dynamics > Improved and Enhanced Recovery > Waterflooding (1.00)
Data Science & Engineering Analytics > Information Management and Systems (1.00)

Technology:

Information Technology > Modeling & Simulation (1.00)
Information Technology > Artificial Intelligence > Representation & Reasoning (0.68)

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Successful Additional Carbon Intensity Reduction and Oil Gain through Polymer Injection Optimization in Heavy Oil Field in the South of Oman

Al-Hajri, Hamood S. (Petroleum Development Oman) | Al-Sawafi, Marwan (Petroleum Development Oman) | Al-Hashimi, Abdulaziz R. (Petroleum Development Oman) | Al-Hadidi, Khalsa (Petroleum Development Oman) | Al-Kindi, Osama M. (Petroleum Development Oman) | Al-Amri, Mohammed (Petroleum Development Oman) | Al-Abri, Mohammed (Petroleum Development Oman) | Al-Hinai, Suleiman (Petroleum Development Oman)

OnePetroJune, 2023

Abstract Water and chemical EOR are the main secondary recovery mechanisms in many heavy oil fields in Oman. The development concept during EOR phase is through intense infill drilling with narrow well spacing. Field-M is currently under secondary recovery phase with both water and chemical EOR (Polymer) development. During this phase, water production increases significantly and all undesired water is being disposed through disposal wells. This increases carbon intensity as disposal process generates CO2 emissions with no additional benefit, which considered as uneconomical emissions. Due to increased amount of produced water during this phase, water handling capacity (including water disposal) was fully utilized to maximize oil production from this field. Creative solutions were certainly needed reduce uneconomical water disposal and increase oil gain. As per the field development, certain pre-defined polymer dosage need to be mixed with treated produced water to achieve a viscosity of around 15 cp to ensure effectiveness of chemical EOR. Field-M injection strategy was suggested to be under controlled fracture condition to maximize throughput. In controlled fracture injection environment, monitoring fracture propagation is very important as it can cause direct interference with producers leading to injection fluid short circuiting. Fracture propagation can be determined using pressure fall off test. In addition, water quality must be monitored regularly as it plays a major role in fracture propagation. Effective surveillance and sampling plan was generated and implemented to ensure to ensure effectiveness of the polymer injection and to capture any opportunities related to increasing injection within the field. The analytical work showed that fracture propagation is a function of injection pressure, injection rate, fluid properties (in this case produced water quality and polymer quality) and in-situ stresses. Most of this parameters are controls though effective surveillance, metering & sampling. However in-situ stress condition is dynamic as the reservoir pressure keeps changing based on dynamic changes in injection and offtake. Thus, fracture propagation was monitored carefully through periodic temperature surveys and pressure fall off test to identify opportunities to optimize injection in some of the injectors. The findings from these activities enabled increasing injection rate up to 30% in some of the injection patterns. This optimization provided additional sink for the produced water reducing water disposal and uneconomical CO2 emissions by at least 5%. This is considered this as the first step toward zero water disposal goal. In addition increasing injection in these patterns resulted in significant increase in oil gain associated with polymer injection peaking to maximum of 42% in some of the injector/producers patterns. The effective use of surveillance data was key enabler to achieve ultimate goal of increasing polymer injection and reduce carbon intensity within the field. This goal was achieved with significant gain of oil.

OnePetro

doi: 10.2118/214364-MS

SPE

SPE-214364-MS

SPE EuropEC - Europe Energy Conference featured at the 84th EAGE Annual Conference & Exhibition

Country: Asia > Middle East > Oman (0.72)

Genre: Overview > Innovation (0.34)

Industry:

Water & Waste Management > Water Management > Lifecycle > Disposal/Injection (1.00)
Energy > Oil & Gas > Upstream (1.00)

SPE Disciplines:

Well Completion > Hydraulic Fracturing (1.00)
Reservoir Description and Dynamics > Improved and Enhanced Recovery > Chemical flooding methods (1.00)
Production and Well Operations > Well Operations and Optimization > Produced water management and control (1.00)
(2 more...)

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Potential Evaluation on the Artificial Geothermal Energy of Post Steamed Heavy Oil Reservoirs

Dong, Xiaohu (China University of Petroleum-Beijing) | Zhang, Hao (China University of Petroleum-Beijing) | Lu, Ning (China University of Petroleum-Beijing) | Xiao, Zhan (China University of Petroleum-Beijing) | Lyu, Xiaocong (China University of Petroleum-Beijing) | Liu, Huiqing (China University of Petroleum-Beijing) | Chen, Zhangxin (University of Calgary)

OnePetroJune, 2023

Abstract Steam injection process is usually the primary extraction method for heavy oil reservoirs. But, in recent decades, with the steam injection operation continues, most of the steamed heavy oil reservoirs have achieved a depleted status (residual oil zone). Meanwhile, for most post steamed heavy oil reservoirs, the average formation temperature can reach above 150℃. It indicates that they can be considered as a potential artificial geothermal energy source. In this work, those post steamed heavy oil reservoirs are proposed as a source of artificial geothermal energy, and the extraction potential is evaluated. A heavy oil reservoir simulation model is firstly constructed based on a geological model which involves a five-spot well pattern of steam flooding operation in Shengli oilfield, Sinopec. This model can be used to represent a depleted status of a steamed heavy oil reservoir. Subsequently, based on this five-spot well pattern of steam flooding, a geothermal heat extraction model is developed. In order to accurately evaluate the extraction potential of this artificial geothermal energy, the wellbore heat loss is also considered by using a discretized wellbore model. Thus, two different extraction methods of water injection and CO2 injection are simulated. Then, based on the simulation model, the factors that control the heat extraction rate in high temperature depleted heavy oil reservoirs are also discussed. Results show that a post steamed heavy oil reservoir can be a potential source of geothermal energy. By using the existing steam flooding well pattern, the initial investment is reduced, thus, a high-efficient development can be achieved. From the simulation results, it is found that the method of geothermal energy extraction in high temperature depleted heavy oil reservoir (165 ℃, 2 MPa) using CO2 can achieve a high-speed geothermal energy extraction process in the early stage (<1.5 years). In comparison, a method of water injection process performs better within a longer time period (>1.5 years). Simultaneously, it is found that the bottom-hole pressure, heat extraction time and CO2 injection rate can have the biggest impact on the heat extraction rate. Because of the high temperature condition, the post steamed heavy oil reservoirs can have a huge potential of heat mining. The technology of geothermal energy extraction can further enhance their development value and prolong the working life.

OnePetro

doi: 10.2118/214415-MS

SPE

SPE-214415-MS

SPE EuropEC - Europe Energy Conference featured at the 84th EAGE Annual Conference & Exhibition

Country:

Europe (0.68)
Asia > China > Shandong (0.25)

Genre: Research Report > New Finding (0.66)

Industry:

Energy > Oil & Gas > Upstream (1.00)
Water & Waste Management > Water Management > Lifecycle > Disposal/Injection (0.80)

Oilfield Places: Asia > China > Shandong > North China Basin > Shengli Field (0.99)

SPE Disciplines:

Reservoir Description and Dynamics > Unconventional and Complex Reservoirs > Oil sand, oil shale, bitumen (1.00)
Reservoir Description and Dynamics > Reservoir Characterization (1.00)
Reservoir Description and Dynamics > Improved and Enhanced Recovery (1.00)

Technology: Information Technology > Modeling & Simulation (1.00)

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Potential of Deep Eutectic Solvents in the Upstream Oil and Gas Industry

Hamdi, Zakaria (Heriot-Watt University) | Koshekov, Shaberdi (Politecnico Di Torino) | Bataee, Mahmood (Curtin University Malaysia)

OnePetroJune, 2023

Abstract Oil and gas will be the main part of our future energy sources, despite of emerging and expanding of renewable energies. Enhanced Oil Recovery (EOR) plays an important role in the future oil and gas industry as the conventional oil reserves will shrink. Heavy oil reservoirs will be the main target of EOR methods because of the high number of existing heavy oil reservoirs. Surfactants are the most efficient chemical EOR method for many unconventional reservoirs as previous studies suggest. The problem with this EOR method is that these projects have high costs and raised environmental concerns. Ionic liquids (ILs) are introduced as an alternative material to surfactants, however, the cost of their synthesis and purification processes are high. Besides, some of them are toxic and have non-biodegradable properties which limit their commercial usage. Recently, a new form of ILs produced and called Deep Eutectic Solvents (DESs). The discovered material is more affordable and environmentally friendly and hence, it is considered to be an alternative material for existing conventional ILs. DESs are cheap, easy to produce, non-toxic, reusable, bio-degradable, and environmentally friendly. These materials consist of two or more cheap and safe components which will form a eutectic mixture. The melting point of the final mixture is lower than its components. In this study, the effectiveness of DESs in the EOR is analysed and evaluated to consider it as a new injection material for chemical EOR. This material has specific properties which improve the efficiency of EOR processes. Some of the favourable properties are stable emulsion between phases, interfacial tension (IFT) reduction, wettability change, recovery enhancement, and avoiding formation damage which is discussed and analysed in this paper. Moreover, the cost of the process is hugely reduced compared with other chemical injection methods. As the result, the main factor for the recovery enhancement is wettability alteration and the chance of viscosity. Besides, only malonic and acid-based DESs formed emulsions with oil, and the other types of DESs did not show emulsification properties. The IFT value increased for heavy oil reservoirs, while for reservoirs with light/medium oil IFT was reduced. Furthermore, DESs did not show formation damage which is a bonus point for this method. As the final result, Choline Chloride Glycerol showed the best recovery with an extra 30% to the original production.

OnePetro

doi: 10.2118/214427-MS

SPE

SPE-214427-MS

SPE EuropEC - Europe Energy Conference featured at the 84th EAGE Annual Conference & Exhibition

Country:

Asia > Middle East (0.47)
Europe > Austria (0.28)

Genre: Research Report > New Finding (1.00)

Industry:

Energy > Oil & Gas > Upstream (1.00)
Materials > Chemicals > Commodity Chemicals > Petrochemicals (0.75)

SPE Disciplines:

Reservoir Description and Dynamics > Unconventional and Complex Reservoirs > Oil sand, oil shale, bitumen (1.00)
Reservoir Description and Dynamics > Improved and Enhanced Recovery > Chemical flooding methods (1.00)

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Discussion on the Wettability Alteration Behavior Induced by CO2-Brine-Silica Interaction and Its Effect on the Performance of Hybrid Steam-CO2 Flooding

Li, Yu (China university of petroleum, Beijing) | Liu, Huiqing (China university of petroleum, Beijing) | Luo, Chen (China university of petroleum, Beijing) | Dong, Xiaohu (China university of petroleum, Beijing) | Wang, Qing (China university of petroleum, Beijing) | Liu, Chuan (China university of petroleum, Beijing) | Wang, Zhipeng (China university of petroleum, Beijing)

OnePetroJune, 2023

Abstract Hybrid steam-CO2 flooding, mature technology to enhance oil recovery, promotes the deposition of asphaltene from heavy oil and the CO2-brine-silica interaction to change the wettability of silica surface. The asphaltene deposition can promote lipophilicity of the silica surface while the CO2-brine-silica interaction can enhance its hydrophilicity. Therefore, aiming to study the wettability alteration during hybrid steam-CO2 flooding, we explore the interaction characteristics of CO2 with oil and brine on the silica surface. In this work, a series of experiments are conducted to reveal the wettability alteration of silica by the interaction of CO2 with different fluids under different conditions. The CO2-brine-silica interaction experiments and the CO2-oil-silica experiments are carried out in the temperature and pressure-resistant vessel to comprehensively acquire the silica under the influence of various fluids in the static process. In addition, based on the core flooding experiments, computerized tomography (CT) technology is applied to realistically and automatically extract the dynamic contact angle in the dynamic process. The result of contact angle from CO2-brine-silica interaction experiments shows the interaction between CO2 and brine evidently enhances the hydrophilicity of the silica surface under high temperature, and the ability of CO2 and brine to promote the increase of hydrophilicity is much greater than that in the absence of CO2. Moreover, the result of contact angle from CO2-oil-silica experiments indicates the increase of temperature and CO2 pressure makes the silica surface covered by heavy oil present the tendency of hydrophobia. The micro-CT images from core displacement experiments are automatically processed by an intelligent algorithm to extract the remaining oil distribution and display the data of dynamic contact angle. Under the influence of steam, the remaining oil mainly performs the form of membrane oil attached to the silica surface. Furthermore, the edges of the remaining oil take on an irregular shape and the contact angle reflecting hydrophobicity reach 45.2% after steam flooding. After the stage of CO2 flooding, the obvious reduction in membrane oil thickness occurs and the number of contact angles reflecting hydrophobicity decreases to 35.3%. Moreover, the oil film gradually transforms into many oil droplets on the surface under the steam and CO2, which may be conducive to the migration of heavy oil in a porous medium. Taking static and dynamic characteristics of contact angle into account under different environments, the conditions and mechanism of wettability alteration can serve as a perspective for CO2 application in pore-scale displacement.

OnePetro

doi: 10.2118/214436-MS

SPE

SPE-214436-MS

SPE EuropEC - Europe Energy Conference featured at the 84th EAGE Annual Conference & Exhibition

Country:

Asia > China (0.28)
Europe > Austria (0.28)

Industry: Energy > Oil & Gas > Upstream (1.00)

Oilfield Places: Asia > China > Shandong > North China Basin > Shengli Field (0.99)

SPE Disciplines:

Reservoir Description and Dynamics > Unconventional and Complex Reservoirs > Oil sand, oil shale, bitumen (1.00)
Reservoir Description and Dynamics > Improved and Enhanced Recovery > Chemical flooding methods (1.00)

Technology: Information Technology (0.88)

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Multi-Fold Increase in Production Through Polymer Flooding Application in Viscous Oil Active Aquifer Driven Reservoir of Mehsana Asset, India

Development of a Deterministic Total Organic Carbon (TOC) Predictor for Shale Reservoirs

Sun Powered Green Hydrogen - A Comparative Analysis from the Kingdoms Of Morocco and Saudi Arabia

Business Model of Carbon Capture and Storage (CCS) Projects for High-CO2 Fields

Case Study of the Use of a Digital Twin for Leak Detection and Quantification in Underground Gas Storage Wells

AI Grid Design for Fast Reservoir Simulation

Successful Additional Carbon Intensity Reduction and Oil Gain through Polymer Injection Optimization in Heavy Oil Field in the South of Oman

Potential Evaluation on the Artificial Geothermal Energy of Post Steamed Heavy Oil Reservoirs

Potential of Deep Eutectic Solvents in the Upstream Oil and Gas Industry

Discussion on the Wettability Alteration Behavior Induced by CO2-Brine-Silica Interaction and Its Effect on the Performance of Hybrid Steam-CO2 Flooding

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