Mobeen Murtaza, Zeeshan Tariq, M. Kamal, A. Rana, S. Patil, M. Mahmoud, Dhafer Al-Shehri
Clay swelling and dispersion in tight sandstones can have an influence on the formation's mechanical properties and productivity. Hydraulic fracturing is a typical stimulation technique used to increase the production of sandstone formations that are too compact. The interaction of clay in sandstone with a water-based fracturing fluid causes the clays to disperse and swell, which weakens the rock and reduces its productivity. Several swelling inhibitors, including inorganic salts, silicates, and polymers, are regularly added to fracturing fluids. Concerns linked with these additions include a decrease in production owing to formation damage and environmental concerns associated with their disposal. In this study, we introduced naturally existing material as a novel green swelling inhibitor. The performance of the novel green inhibitor was examined by its impact on the mechanical properties of the rock. Acoustic strength and scratch tests were conducted to evaluate rock mechanical parameters such as unconfined compressive strength. Further inhibition potential was evaluated by conducting linear swell and capillary suction timer tests. The contact angle was measured on a sandstone surface for wettability change. The results showed the novel green additive provided strong inhibition to clays. The reduction in linear swelling and rise in capillary suction time showed the inhibition potential and water control potential of the biomaterial. Furthermore, mechanical properties were lower than DI-treated rock sample tested under dry conditions. With all these benefits, using green novel additive makes rock more stable and reduces damage to the formation. The green additive is economical and an environment-friendly solution to clay swelling. It is an effective recipe for reducing the formation damage caused by clay swelling.
{"title":"Application of a Novel Green and Biocompatible Clay Swelling Inhibitor in Fracturing Fluid Design","authors":"Mobeen Murtaza, Zeeshan Tariq, M. Kamal, A. Rana, S. Patil, M. Mahmoud, Dhafer Al-Shehri","doi":"10.2118/213030-ms","DOIUrl":"https://doi.org/10.2118/213030-ms","url":null,"abstract":"\u0000 Clay swelling and dispersion in tight sandstones can have an influence on the formation's mechanical properties and productivity. Hydraulic fracturing is a typical stimulation technique used to increase the production of sandstone formations that are too compact. The interaction of clay in sandstone with a water-based fracturing fluid causes the clays to disperse and swell, which weakens the rock and reduces its productivity. Several swelling inhibitors, including inorganic salts, silicates, and polymers, are regularly added to fracturing fluids. Concerns linked with these additions include a decrease in production owing to formation damage and environmental concerns associated with their disposal. In this study, we introduced naturally existing material as a novel green swelling inhibitor. The performance of the novel green inhibitor was examined by its impact on the mechanical properties of the rock. Acoustic strength and scratch tests were conducted to evaluate rock mechanical parameters such as unconfined compressive strength. Further inhibition potential was evaluated by conducting linear swell and capillary suction timer tests. The contact angle was measured on a sandstone surface for wettability change.\u0000 The results showed the novel green additive provided strong inhibition to clays. The reduction in linear swelling and rise in capillary suction time showed the inhibition potential and water control potential of the biomaterial. Furthermore, mechanical properties were lower than DI-treated rock sample tested under dry conditions. With all these benefits, using green novel additive makes rock more stable and reduces damage to the formation. The green additive is economical and an environment-friendly solution to clay swelling. It is an effective recipe for reducing the formation damage caused by clay swelling.","PeriodicalId":158776,"journal":{"name":"Day 3 Wed, May 24, 2023","volume":"113 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114303425","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In situ bitumen extraction from oil sands using thermal recovery processes has faced challenges due to reliance on steam. Additionally, the produced bitumen is highly viscous and needs to be diluted with lighter hydrocarbon products, such as field condensates, for pipeline transportation. Therefore, exploring less energy-intensive options to produce and transport bitumen economically with less environmental impact is essential. This work aimed to study the liquid-liquid equilibrium (LLE) of CO2 and bitumen at ambient temperature. First, the impact of CO2 feed mass fraction and pressure on equilibrium mixture properties are investigated. In the next step, the effect of ethyl acetate (EA) as an additive on the equilibrium properties of the mixture is studied. The equilibrium properties of the mixtures, including CO2 solubility in the heavy liquid phase, the viscosity of the heavy liquid phase, and the densities of light and heavy liquid phases, are reported. The results suggest that the viscosity of bitumen is considerably reduced by mixing it with liquid CO2 at ambient temperature. It was also shown that the bitumen viscosity could be further reduced by the addition of ethyl acetate as a co-solvent.
{"title":"Liquid-Liquid Equilibrium Studies of Carbon Dioxide/Bitumen System and Utilizing Ethyl Acetate as a Co-Solvent","authors":"Mohammad Shah Faisal Khan, H. Hassanzadeh","doi":"10.2118/213017-ms","DOIUrl":"https://doi.org/10.2118/213017-ms","url":null,"abstract":"\u0000 In situ bitumen extraction from oil sands using thermal recovery processes has faced challenges due to reliance on steam. Additionally, the produced bitumen is highly viscous and needs to be diluted with lighter hydrocarbon products, such as field condensates, for pipeline transportation. Therefore, exploring less energy-intensive options to produce and transport bitumen economically with less environmental impact is essential. This work aimed to study the liquid-liquid equilibrium (LLE) of CO2 and bitumen at ambient temperature. First, the impact of CO2 feed mass fraction and pressure on equilibrium mixture properties are investigated. In the next step, the effect of ethyl acetate (EA) as an additive on the equilibrium properties of the mixture is studied. The equilibrium properties of the mixtures, including CO2 solubility in the heavy liquid phase, the viscosity of the heavy liquid phase, and the densities of light and heavy liquid phases, are reported. The results suggest that the viscosity of bitumen is considerably reduced by mixing it with liquid CO2 at ambient temperature. It was also shown that the bitumen viscosity could be further reduced by the addition of ethyl acetate as a co-solvent.","PeriodicalId":158776,"journal":{"name":"Day 3 Wed, May 24, 2023","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116568194","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In-situ combustion (ISC) is a technology used for enhanced oil recovery for heavy oil reservoirs. In two ISC field pilots conducted in 1970s to 1980s in Canada, 10-20% mole fraction of hydrogen (H2) was produced accidentally. This presents a potential opportunity for petroleum industry to contribute to the energy transition by producing hydrogen directly from petroleum reservoirs. However, most ISC experiments have reported no or negligible hydrogen production, and the reason remains unclear. To address this issue, this study focuses on hydrogen generation from bitumen through in-situ combustion gasification (ISCG) at a laboratory scale. CMG was used to simulate the ISCG process in a combustion tube. Kinetics from previous ISC experiments and reactions for hydrogen generation were incorporated in the models. Heavy oil, oxygen, and water were simultaneously injected into the tube at a certain temperature. The ranges of key parameters were varied and analyzed for their impact on hydrogen generation. The study found that maintaining a temperature above 400 °C is essential for hydrogen generation, with higher temperatures yielding higher hydrogen mole fractions. A maximum of 28% hydrogen mole fraction was obtained at a water-oxygen ratio of 0.0018:0.9882 (volume ratio at ambient conditions) and a temperature about 735 °C. Higher oxygen content was found to be favorable for hydrogen generation by achieving a higher temperature, while increasing nitrogen from 0 to 78% led to a decrease in hydrogen mole fraction from 28% to 0.07%. Hydrogen generation is dominated by coke gasification and water-gas shift reactions at low and high temperatures, respectively. This research provides valuable insights into the key parameters affecting hydrogen generation from bitumen at a lab scale. The potential for petroleum industry to contribute to energy transition through large-scale, low-cost hydrogen production from reservoirs is significant.
{"title":"Hydrogen Generation from Heavy Oils via In-situ Combustion Gasification","authors":"Ping Song, Yunan Li, Zhen Yin, Q. Yuan","doi":"10.2118/212986-ms","DOIUrl":"https://doi.org/10.2118/212986-ms","url":null,"abstract":"\u0000 In-situ combustion (ISC) is a technology used for enhanced oil recovery for heavy oil reservoirs. In two ISC field pilots conducted in 1970s to 1980s in Canada, 10-20% mole fraction of hydrogen (H2) was produced accidentally. This presents a potential opportunity for petroleum industry to contribute to the energy transition by producing hydrogen directly from petroleum reservoirs. However, most ISC experiments have reported no or negligible hydrogen production, and the reason remains unclear. To address this issue, this study focuses on hydrogen generation from bitumen through in-situ combustion gasification (ISCG) at a laboratory scale. CMG was used to simulate the ISCG process in a combustion tube. Kinetics from previous ISC experiments and reactions for hydrogen generation were incorporated in the models. Heavy oil, oxygen, and water were simultaneously injected into the tube at a certain temperature. The ranges of key parameters were varied and analyzed for their impact on hydrogen generation. The study found that maintaining a temperature above 400 °C is essential for hydrogen generation, with higher temperatures yielding higher hydrogen mole fractions. A maximum of 28% hydrogen mole fraction was obtained at a water-oxygen ratio of 0.0018:0.9882 (volume ratio at ambient conditions) and a temperature about 735 °C. Higher oxygen content was found to be favorable for hydrogen generation by achieving a higher temperature, while increasing nitrogen from 0 to 78% led to a decrease in hydrogen mole fraction from 28% to 0.07%. Hydrogen generation is dominated by coke gasification and water-gas shift reactions at low and high temperatures, respectively. This research provides valuable insights into the key parameters affecting hydrogen generation from bitumen at a lab scale. The potential for petroleum industry to contribute to energy transition through large-scale, low-cost hydrogen production from reservoirs is significant.","PeriodicalId":158776,"journal":{"name":"Day 3 Wed, May 24, 2023","volume":"136 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123594491","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Nowadays, the only economic and effective way to exploit shale reservoirs is multi-stage fracturing of horizontal wells. The backflow after fracturing affects the damage degree of a fracturing fluid to a formation and fracture conductivity, and directly influences a fracturing outcome. At present, the backflow control of the fracturing fluid mostly adopts empirical methods, lacking a reliable theoretical basis. Therefore, it is of positively practical significance to reasonably optimize a flowback process and control the flowback velocity and flowback process of a fracturing fluid. On the other hand, the previous research on the productivity of multi-stage fracturing horizontal wells after fracturing is limited, and an equation derivation process has been simplified and approximated to a certain extent, so its accuracy is significantly affected. Based on previous studies, this paper established a new mathematical model. This model optimizes the flowback velocity after fracturing by dynamically adjusting a choke size and analyzes and predicts the production performance after fracturing. To maximize fracture clean-up efficiency, this work builds the model for a dynamic adjustment of choke sizes as wellhead pressure changes over time. It uses a two-phase (gas and liquid) flow model along the horizontal, slanted and vertical sections. The forces acting on proppant particles, filtration loss of water, the compressibility of a fracturing fluid, wellbore friction, a gas slippage effect, water absorption and adsorption are simultaneously considered. With the theories of mass conservation, we build a mathematical model for predicting production performance from multi-fractured horizontal wells with a dynamic two-phase model considering dual-porosity, stress-sensitivity, wellbore friction, gas adsorption and desorption. In this model, the gas production mechanisms from stimulated reservoir volume and gas and water relative permeabilities are employed. Based on shale reservoir parameters, wellhead pressure, a choke size, a gas/liquid rate, cumulative gas/liquid production, cumulative filtration loss and a flowback rate are simulated. In the simulations, the influential factors, such as shut-in soak time of the fracturing fluid, forced flowback velocity, fracturing stages and fracture half-length after fracturing, are studied. It is found by comparison that in the block studied, when a well is shut in four days after fracturing, the dynamic choke size is adjusted with wellhead pressure changing over time, the fracturing stage is 11, and the fracture half-length is 350 meters, the fracture conductivity after flowback is the largest, and the productivity of the horizontal well is the highest.
{"title":"Studying Factors to Optimize Flowback and Productivity of Mfhws in Shale Gas Formations","authors":"Guicheng Jing, Zhangxin Chen, Kai Zhang","doi":"10.2118/213005-ms","DOIUrl":"https://doi.org/10.2118/213005-ms","url":null,"abstract":"\u0000 Nowadays, the only economic and effective way to exploit shale reservoirs is multi-stage fracturing of horizontal wells. The backflow after fracturing affects the damage degree of a fracturing fluid to a formation and fracture conductivity, and directly influences a fracturing outcome. At present, the backflow control of the fracturing fluid mostly adopts empirical methods, lacking a reliable theoretical basis. Therefore, it is of positively practical significance to reasonably optimize a flowback process and control the flowback velocity and flowback process of a fracturing fluid. On the other hand, the previous research on the productivity of multi-stage fracturing horizontal wells after fracturing is limited, and an equation derivation process has been simplified and approximated to a certain extent, so its accuracy is significantly affected. Based on previous studies, this paper established a new mathematical model. This model optimizes the flowback velocity after fracturing by dynamically adjusting a choke size and analyzes and predicts the production performance after fracturing. To maximize fracture clean-up efficiency, this work builds the model for a dynamic adjustment of choke sizes as wellhead pressure changes over time. It uses a two-phase (gas and liquid) flow model along the horizontal, slanted and vertical sections. The forces acting on proppant particles, filtration loss of water, the compressibility of a fracturing fluid, wellbore friction, a gas slippage effect, water absorption and adsorption are simultaneously considered. With the theories of mass conservation, we build a mathematical model for predicting production performance from multi-fractured horizontal wells with a dynamic two-phase model considering dual-porosity, stress-sensitivity, wellbore friction, gas adsorption and desorption. In this model, the gas production mechanisms from stimulated reservoir volume and gas and water relative permeabilities are employed. Based on shale reservoir parameters, wellhead pressure, a choke size, a gas/liquid rate, cumulative gas/liquid production, cumulative filtration loss and a flowback rate are simulated. In the simulations, the influential factors, such as shut-in soak time of the fracturing fluid, forced flowback velocity, fracturing stages and fracture half-length after fracturing, are studied. It is found by comparison that in the block studied, when a well is shut in four days after fracturing, the dynamic choke size is adjusted with wellhead pressure changing over time, the fracturing stage is 11, and the fracture half-length is 350 meters, the fracture conductivity after flowback is the largest, and the productivity of the horizontal well is the highest.","PeriodicalId":158776,"journal":{"name":"Day 3 Wed, May 24, 2023","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123626246","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
V. Bulule, A. Sattari, K. Aminian, Mohamed El Sgher, Ameri Samuel
The shale formations, in addition to the gas present in the pores of the rock, contain gas in the adsorbed state in the organic matter within the rock. As the pressure depletes in the reservoir the adsorbed gas is released and augments the gas production. In addition, gas desorption can potentially lead to permeability enhancement due to shale matrix shrinkage. At the same time, the pressure depletion increases the effective stress causing shale permeability and hydraulic fracture conductivity impairments. The purpose of this study was to investigate the impact of the gas desorption on the productivity of Marcellus shale horizontal well with multiple hydraulic fracture stages. The impacts of hydraulic fracture properties including half-length, conductivity, and stage spacing on gas desorption were also investigated. To investigate the impact of the gas desorption on gas production from Marcellus shale, a reservoir model for a horizontal well completed with multiple hydraulic fracture stages was used. The model has been developed based on the available information from several existing Marcellus shale horizontal wells in West Virginia. The laboratory and published data relative to adsorbed gas and the geomechanical factors were analyzed and geomechanical multipliers were generated and incorporated in the model. The geomechanical multipliers account for the impairments in hydraulic fracture conductivity and the reduction in the formation (matrix and fissure) permeability as well as the shale shrinkage caused by the reservoir depletion. The model was then utilized to investigate the impact of different parameters including Langmuir pressure and volume, fracture half-lengths, fracture spacings, and fracture conductivity on gas desorption and gas production. The inclusion of geomechanical multipliers provided more realistic production predictions and better understanding of the desorbed gas impact. The gas desorption was found to have a significant impact on the productivity during later stages of the production. This is contributed to pressure depletion required for desorption to become significant. The contribution of the desorbed gas to production increases as the fracture half-length increases and the fracture spacing decreases. Therefore, it can be concluded that desorption of gas depends on the stimulated reservoir volume.
{"title":"The Impacts of Gas Adsorption on the Productivity of Marcellus Shale Horizontal Well","authors":"V. Bulule, A. Sattari, K. Aminian, Mohamed El Sgher, Ameri Samuel","doi":"10.2118/212999-ms","DOIUrl":"https://doi.org/10.2118/212999-ms","url":null,"abstract":"The shale formations, in addition to the gas present in the pores of the rock, contain gas in the adsorbed state in the organic matter within the rock. As the pressure depletes in the reservoir the adsorbed gas is released and augments the gas production. In addition, gas desorption can potentially lead to permeability enhancement due to shale matrix shrinkage. At the same time, the pressure depletion increases the effective stress causing shale permeability and hydraulic fracture conductivity impairments. The purpose of this study was to investigate the impact of the gas desorption on the productivity of Marcellus shale horizontal well with multiple hydraulic fracture stages. The impacts of hydraulic fracture properties including half-length, conductivity, and stage spacing on gas desorption were also investigated.\u0000 To investigate the impact of the gas desorption on gas production from Marcellus shale, a reservoir model for a horizontal well completed with multiple hydraulic fracture stages was used. The model has been developed based on the available information from several existing Marcellus shale horizontal wells in West Virginia. The laboratory and published data relative to adsorbed gas and the geomechanical factors were analyzed and geomechanical multipliers were generated and incorporated in the model. The geomechanical multipliers account for the impairments in hydraulic fracture conductivity and the reduction in the formation (matrix and fissure) permeability as well as the shale shrinkage caused by the reservoir depletion. The model was then utilized to investigate the impact of different parameters including Langmuir pressure and volume, fracture half-lengths, fracture spacings, and fracture conductivity on gas desorption and gas production. The inclusion of geomechanical multipliers provided more realistic production predictions and better understanding of the desorbed gas impact. The gas desorption was found to have a significant impact on the productivity during later stages of the production. This is contributed to pressure depletion required for desorption to become significant. The contribution of the desorbed gas to production increases as the fracture half-length increases and the fracture spacing decreases. Therefore, it can be concluded that desorption of gas depends on the stimulated reservoir volume.","PeriodicalId":158776,"journal":{"name":"Day 3 Wed, May 24, 2023","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116362118","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Hardikkumar Zalavadia, Utkarsh Sinha, Prithvi Singh, S. Sankaran
Routinely analyzing producing well performance in unconventional field is critical to maintain their profitability. In addition to continuous analysis, there is an increasing need to develop models that are scalable across entire field. Pure data-driven approaches, such as DCA, are prevalent but fail to capture essential physical elements, compounded by lack of key operational parameters such as pressures and fluid property changes across large number of wells. Traditional models such as numerical simulations face a scalability challenge to extend to large well counts with rapid pace of operations. Other widely used method is rate transient analysis (RTA), which requires identification of flow regimes and mechanistic model assumptions, making it interpretive and non-conducive to field-scale applications. The objective in this study is to build data-driven and physics-constrained reservoir models from routine data (rates and pressures) for pressure-aware production forecasting. We propose a hybrid data-driven and physics informed model based on sparse nonlinear regression (SNR) for identifying rate-pressure relationships in unconventionals. Hybrid SNR is a novel framework to discover governing equations underlying fluid flow in unconventionals, simply from production and pressure data, leveraging advances in sparsity techniques and machine learning. The method utilizes a library of data-driven functions along with information from standard flow-regime equations that form the basis for traditional RTA. However, the model is not limited to fixed known relationships of pressure and rates that are applicable only under certain assumptions (e.g. planar fractures, single-phase flowing conditions etc.). Complex, non-uniform fractures, and multi-phase flow of fluids do not follow the same diagnostics behavior but exhibits more complex behavior not explained by analytical equations. The hybrid SNR approach identifies these complexities from combination of the most relevant pressure and time features that explain the phase rates behavior for a given well, thus enables forecasting the well for different flowing pressure/operating conditions. In addition, the method allows identification of dominant flow regimes through highest contributing terms without performing typical line fitting procedure. The method has been validated against synthetic model with constant and varying bottom hole pressures. The results indicate good model accuracies to identify relevant set of features that dictate rate-pressure behavior and perform production forecasts for new bottom-hole pressure profiles. The method is robust since it can be applied to any well with different fluid types, flowing conditions and does not require any mechanistic fracture or simulation model assumptions and hence applicable to any reservoir complexity. The novelty of the method is that the hybrid SNR can resolve several modes that govern the flow process simultaneously that can provide physical in
{"title":"Discovery of Unconventional Reservoir Flow Physics for Production Forecasting Through Hybrid Data-Driven and Physics Models","authors":"Hardikkumar Zalavadia, Utkarsh Sinha, Prithvi Singh, S. Sankaran","doi":"10.2118/213004-ms","DOIUrl":"https://doi.org/10.2118/213004-ms","url":null,"abstract":"\u0000 Routinely analyzing producing well performance in unconventional field is critical to maintain their profitability. In addition to continuous analysis, there is an increasing need to develop models that are scalable across entire field. Pure data-driven approaches, such as DCA, are prevalent but fail to capture essential physical elements, compounded by lack of key operational parameters such as pressures and fluid property changes across large number of wells. Traditional models such as numerical simulations face a scalability challenge to extend to large well counts with rapid pace of operations. Other widely used method is rate transient analysis (RTA), which requires identification of flow regimes and mechanistic model assumptions, making it interpretive and non-conducive to field-scale applications. The objective in this study is to build data-driven and physics-constrained reservoir models from routine data (rates and pressures) for pressure-aware production forecasting.\u0000 We propose a hybrid data-driven and physics informed model based on sparse nonlinear regression (SNR) for identifying rate-pressure relationships in unconventionals. Hybrid SNR is a novel framework to discover governing equations underlying fluid flow in unconventionals, simply from production and pressure data, leveraging advances in sparsity techniques and machine learning. The method utilizes a library of data-driven functions along with information from standard flow-regime equations that form the basis for traditional RTA. However, the model is not limited to fixed known relationships of pressure and rates that are applicable only under certain assumptions (e.g. planar fractures, single-phase flowing conditions etc.). Complex, non-uniform fractures, and multi-phase flow of fluids do not follow the same diagnostics behavior but exhibits more complex behavior not explained by analytical equations. The hybrid SNR approach identifies these complexities from combination of the most relevant pressure and time features that explain the phase rates behavior for a given well, thus enables forecasting the well for different flowing pressure/operating conditions. In addition, the method allows identification of dominant flow regimes through highest contributing terms without performing typical line fitting procedure.\u0000 The method has been validated against synthetic model with constant and varying bottom hole pressures. The results indicate good model accuracies to identify relevant set of features that dictate rate-pressure behavior and perform production forecasts for new bottom-hole pressure profiles. The method is robust since it can be applied to any well with different fluid types, flowing conditions and does not require any mechanistic fracture or simulation model assumptions and hence applicable to any reservoir complexity.\u0000 The novelty of the method is that the hybrid SNR can resolve several modes that govern the flow process simultaneously that can provide physical in","PeriodicalId":158776,"journal":{"name":"Day 3 Wed, May 24, 2023","volume":"87 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122750642","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In situ formation of foamy oil has been widely utilized to improve the heavy oil recovery, especially considering its cost efficiency. Therefore, the stability and strength of generated foam actually play a crucial role on the foamy oil recovery. In this work, the effects of nanoparticles (NPs), the additives in a CO2-heavy oil system, on the so-called NPs-stabilized foam of CO2-heavy oil systems are experimentally and mathematically assessed. Specifically, a visual high temperature high pressure (HTHP) foam generator is utilized to investigate the foam stability of NPs- CO2-heavy oil system. The effects of different NPs concentrations and NPs types on the foam stability is systematically observed and analyzed with measuring the relationship between the height of foam column and time under nonequilibrium conditions. Then, a mathematical model is proposed to quantify processes of NPs-stabilized foam generation and collapse according to the experimental results. The results show that NPs of SiO2 with a size of 20-30 nm can effectively improve the foam stability and generation of CO2-heavy oil system compared with pure CO2-heavy oil foam. The concentration of NPs impose impact on the foam properties to some degree. Also, different types of NPs, SiO2, Al2O3 and MgO, on the foam stability are experimentally probed mainly to unveil the difference between metallic NPs and non-metallic NPs. Finally, the exponential functions with parameters characterizing concentration and nonequilibrium conditions are developed to quantify the foam generation and stability under nonequilibrium conditions.
泡沫油原位地层被广泛用于提高稠油采收率，特别是考虑到其成本效益。因此，生成泡沫的稳定性和强度实际上对泡沫采油起着至关重要的作用。在这项工作中，纳米颗粒(NPs)的影响，添加剂在二氧化碳重油体系中，对所谓的NPs稳定泡沫的二氧化碳重油体系进行了实验和数学评估。具体而言，利用可视化高温高压泡沫发生器研究了NPs- co2 -重油体系的泡沫稳定性。通过测量非平衡条件下泡沫柱高度与时间的关系，系统地观察和分析了不同NPs浓度和NPs类型对泡沫稳定性的影响。然后，根据实验结果，提出了量化nps稳定泡沫产生和崩塌过程的数学模型。结果表明，与纯co2 -重油泡沫相比，粒径为20 ~ 30 nm的SiO2纳米颗粒能有效改善泡沫稳定性和co2 -重油体系的生成。NPs的浓度对泡沫性能有一定的影响。同时，通过实验考察了不同类型NPs (SiO2、Al2O3和MgO)对泡沫稳定性的影响，主要揭示了金属NPs与非金属NPs之间的差异。最后，建立了具有浓度和非平衡条件参数的指数函数，量化了非平衡条件下泡沫的产生和稳定性。
{"title":"Effects of Nano-Particles on Foamy Oil of CO2-Heavy Oil System under Nonequilibrium Conditions","authors":"Yu Shi, Wang Lv, Yin Zhang, Guangya Zhu","doi":"10.2118/213019-ms","DOIUrl":"https://doi.org/10.2118/213019-ms","url":null,"abstract":"\u0000 In situ formation of foamy oil has been widely utilized to improve the heavy oil recovery, especially considering its cost efficiency. Therefore, the stability and strength of generated foam actually play a crucial role on the foamy oil recovery. In this work, the effects of nanoparticles (NPs), the additives in a CO2-heavy oil system, on the so-called NPs-stabilized foam of CO2-heavy oil systems are experimentally and mathematically assessed. Specifically, a visual high temperature high pressure (HTHP) foam generator is utilized to investigate the foam stability of NPs- CO2-heavy oil system. The effects of different NPs concentrations and NPs types on the foam stability is systematically observed and analyzed with measuring the relationship between the height of foam column and time under nonequilibrium conditions. Then, a mathematical model is proposed to quantify processes of NPs-stabilized foam generation and collapse according to the experimental results. The results show that NPs of SiO2 with a size of 20-30 nm can effectively improve the foam stability and generation of CO2-heavy oil system compared with pure CO2-heavy oil foam. The concentration of NPs impose impact on the foam properties to some degree. Also, different types of NPs, SiO2, Al2O3 and MgO, on the foam stability are experimentally probed mainly to unveil the difference between metallic NPs and non-metallic NPs. Finally, the exponential functions with parameters characterizing concentration and nonequilibrium conditions are developed to quantify the foam generation and stability under nonequilibrium conditions.","PeriodicalId":158776,"journal":{"name":"Day 3 Wed, May 24, 2023","volume":"85 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130052047","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
C. Sistrunk, Andrew Travis Brashear, D. Hill, D. Zhu, Tohoko Tajima
When rocks are fractured in tension, the fracture surfaces created are rough, with a wide range of surface morphologies possible. In previous studies of propped fracture conductivity using fractured samples, the fracture surface topography was found to have a strong influence on fracture conductivity and stimulation efficiency. Fracture surface patterns (relatively uniform, randomly rough, step changes, ridges and valleys) strongly affect propped fracture conductivity. Different types of surfaces can result in propped fracture conductivities differing by an order of magnitude or more for identical proppant loading conditions. To generate quantitative correlations including surface topographic effects, consistent samples with well-defined surfaces should be used in the experiments. However, when using actual rock samples to create realistic fracture surfaces by fracturing them in tension, the surfaces created are never the same, even using small samples all taken from the same block. This lack of repeatability in fracture surfaces greatly complicates identification of the effects of the rough surfaces on propped fracture conductivity. To overcome this, we created repeatable rough fracture surfaces using 3D-printing technology. First, we geostatistically generated a numerical depiction of a rough fracture surface. Then the surface was printed with resin using a 3D-printer. The hardened resin model of the rock sample was used to make a mold, which was in turn used to create a rock sample made of cement. High strength cement was used so that the samples had similar mechanical properties to unconventional reservoir rocks. With this methodology, we created multiple samples with identical surface roughness and features, allowing us to isolate and test other parameters, such as proppant size and concentration. Fracture conductivity tests were conducted using a modified API conductivity cell and artificial rock samples that are nominally 7 inches long and 2 inches wide. A well-established protocol to generate propped fracture conductivity as a function of closure stress was employed to test three different proppant concentrations on identical rough surfaces. For all three experiments, 100 mesh sand was used. The study demonstrates how proppant concentration affects propped fracture conductivity behavior in a systematic way.
{"title":"The Effect of Fracture Surface Roughness on Propped Fracture Conductivity Using 3D-Printed Fracture Surfaces","authors":"C. Sistrunk, Andrew Travis Brashear, D. Hill, D. Zhu, Tohoko Tajima","doi":"10.2118/213032-ms","DOIUrl":"https://doi.org/10.2118/213032-ms","url":null,"abstract":"\u0000 When rocks are fractured in tension, the fracture surfaces created are rough, with a wide range of surface morphologies possible. In previous studies of propped fracture conductivity using fractured samples, the fracture surface topography was found to have a strong influence on fracture conductivity and stimulation efficiency. Fracture surface patterns (relatively uniform, randomly rough, step changes, ridges and valleys) strongly affect propped fracture conductivity. Different types of surfaces can result in propped fracture conductivities differing by an order of magnitude or more for identical proppant loading conditions. To generate quantitative correlations including surface topographic effects, consistent samples with well-defined surfaces should be used in the experiments. However, when using actual rock samples to create realistic fracture surfaces by fracturing them in tension, the surfaces created are never the same, even using small samples all taken from the same block. This lack of repeatability in fracture surfaces greatly complicates identification of the effects of the rough surfaces on propped fracture conductivity.\u0000 To overcome this, we created repeatable rough fracture surfaces using 3D-printing technology. First, we geostatistically generated a numerical depiction of a rough fracture surface. Then the surface was printed with resin using a 3D-printer. The hardened resin model of the rock sample was used to make a mold, which was in turn used to create a rock sample made of cement. High strength cement was used so that the samples had similar mechanical properties to unconventional reservoir rocks. With this methodology, we created multiple samples with identical surface roughness and features, allowing us to isolate and test other parameters, such as proppant size and concentration.\u0000 Fracture conductivity tests were conducted using a modified API conductivity cell and artificial rock samples that are nominally 7 inches long and 2 inches wide. A well-established protocol to generate propped fracture conductivity as a function of closure stress was employed to test three different proppant concentrations on identical rough surfaces. For all three experiments, 100 mesh sand was used. The study demonstrates how proppant concentration affects propped fracture conductivity behavior in a systematic way.","PeriodicalId":158776,"journal":{"name":"Day 3 Wed, May 24, 2023","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127098882","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
C. M. Smith, Michael P. Smith, P. Gordon, T. Smith, Edward D. Duncan
Coming into 2021 previous work had identified major potential oil targets throughout the Brookian Campanian Section and in the Kuparuk River Sands of Great Bear Pantheon's (GBP) Talitha and Alkaid units and Theta West leasehold on the North Slope of Alaska which sit immediately adjacent to the Dalton Highway and Tans Alaska Pipeline System approximately 20 miles south of the town of Dead Horse in Prudhoe Bay. These identified targets were based on a combination of previous drilling by ARCO with their Pipeline State 1 well (drilled in 1988) and Alkaid 1 drilled by GBP (drilled in 2015 by Great Bear Petroleum at the time) in addition to 3D seismic owned by GBP. Following Great Bear Petroleum's merger in 2019 with Pantheon Resources to become Great Bear Pantheon and a successful test at the Alkaid 1 well an expanded project of exploration and appraisal wells was launched. This project began with the drilling of the Talitha A exploration well and continued with the Theta West 1 and Alkaid 2 wells. All these wells encountered multiple and significant oil accumulations in the Brookian Campanian Section. A key part of these exploration and appraisal wells was the analysis of sealed at well site and unsealed gently airdried drill cuttings by Rock Volatiles Stratigraphy (RVS) (also known as Volatiles Analysis Service (VAS)) developed by Advanced Hydrocarbon Stratigraphy (AHS). RVS enables the direct measurement of the C1-10 hydrocarbons, water, and several other volatile compounds relevant to evaluating petroleum systems via a gentle extraction, identification, and quantification process on a novel cryo-trap mass spectroscopy system developed in house by AHS. The RVS results have been especially helpful in the analysis of the Brookian Campanian Section given the petrophysically challenging nature of the play, representing an independent measurement relating to hydrocarbons (HC) and water that can be paired with the petrophysics to provide greater confidence in the identification of pay zones. RVS analysis and interpretation is done blind with no additional information beforehand significantly diminishing opportunities for bias in the interpretation of the results before being paired with other datasets. Beyond observations about HC and water content, significant additional information about the petroleum system such as oil quality (API gravity and biological activity), rock/reservoir properties, seals/compartments, and overall strength of the system was provided via RVS. Many of these results were used in the planning of subsequent well site activities like perforations and have been proven accurate in resulting flow tests. When combined with other data like 3D seismic the RVS data enables an immense appreciation of the world class asset that the multiple continuous accumulations in the Brookian Campanian Section of GBP's acreage represents.
进入2021年，之前的工作已经确定了整个Brookian Campanian区段和Great Bear Pantheon (GBP)的Talitha和Alkaid单元的Kuparuk River Sands以及阿拉斯加北坡的Theta West租赁地的主要潜在石油目标，这些区域紧邻道顿高速公路和Tans阿拉斯加管道系统，位于普拉德霍湾Dead Horse镇以南约20英里处。这些确定的目标是基于ARCO之前钻探的Pipeline State 1井(1988年钻探)和GBP钻探的Alkaid 1井(当时由Great Bear Petroleum公司于2015年钻探)以及GBP拥有的3D地震数据。继Great Bear Petroleum于2019年与Pantheon Resources合并成为Great Bear Pantheon之后，在Alkaid 1井进行了成功的测试，并启动了一个扩大的勘探和评评井项目。该项目从钻探Talitha A探井开始，并继续钻探Theta West 1和Alkaid 2井。所有这些井都在布鲁克坎帕尼亚段遇到了多个重要的石油聚集。这些勘探和评价井的关键部分是利用先进油气地层学(AHS)开发的岩石挥发物地层学(RVS)(也称为挥发物分析服务(VAS))对井场密封和未密封的缓慢风干钻屑进行分析。RVS可以直接测量C1-10碳氢化合物、水和其他几种挥发性化合物，这些化合物与评价石油系统有关，通过温和的提取、鉴定和定量过程，在AHS开发的新型低温阱质谱系统上进行。考虑到储层岩石物理性质的挑战性，RVS的结果对Brookian Campanian剖面的分析特别有帮助，代表了与碳氢化合物(HC)和水相关的独立测量，可以与岩石物理相结合，为识别产层提供更大的信心。RVS分析和解释是盲目进行的，事先没有额外的信息，这大大减少了在与其他数据集配对之前对结果进行解释时出现偏倚的机会。除了HC和含水量的观测结果外，RVS还提供了有关石油系统的重要附加信息，如油品质量(API重力和生物活性)、岩石/储层性质、密封/隔室以及系统的整体强度。这些结果中的许多都被用于后续井场活动的规划，如射孔，并在由此产生的流量测试中被证明是准确的。当与3D地震等其他数据相结合时，RVS数据可以对GBP的Brookian Campanian部分的多个连续油气藏进行巨大的增值。
{"title":"Advanced Hydrocarbon Stratigraphy (AHS) Use of Proprietary Rock Volatiles Stratigraphy (RVS) System to Analyze Cutting Samples of Great Bear Pantheon's Exploration Wells on the North Slope","authors":"C. M. Smith, Michael P. Smith, P. Gordon, T. Smith, Edward D. Duncan","doi":"10.2118/214493-ms","DOIUrl":"https://doi.org/10.2118/214493-ms","url":null,"abstract":"\u0000 Coming into 2021 previous work had identified major potential oil targets throughout the Brookian Campanian Section and in the Kuparuk River Sands of Great Bear Pantheon's (GBP) Talitha and Alkaid units and Theta West leasehold on the North Slope of Alaska which sit immediately adjacent to the Dalton Highway and Tans Alaska Pipeline System approximately 20 miles south of the town of Dead Horse in Prudhoe Bay. These identified targets were based on a combination of previous drilling by ARCO with their Pipeline State 1 well (drilled in 1988) and Alkaid 1 drilled by GBP (drilled in 2015 by Great Bear Petroleum at the time) in addition to 3D seismic owned by GBP. Following Great Bear Petroleum's merger in 2019 with Pantheon Resources to become Great Bear Pantheon and a successful test at the Alkaid 1 well an expanded project of exploration and appraisal wells was launched. This project began with the drilling of the Talitha A exploration well and continued with the Theta West 1 and Alkaid 2 wells. All these wells encountered multiple and significant oil accumulations in the Brookian Campanian Section. A key part of these exploration and appraisal wells was the analysis of sealed at well site and unsealed gently airdried drill cuttings by Rock Volatiles Stratigraphy (RVS) (also known as Volatiles Analysis Service (VAS)) developed by Advanced Hydrocarbon Stratigraphy (AHS). RVS enables the direct measurement of the C1-10 hydrocarbons, water, and several other volatile compounds relevant to evaluating petroleum systems via a gentle extraction, identification, and quantification process on a novel cryo-trap mass spectroscopy system developed in house by AHS. The RVS results have been especially helpful in the analysis of the Brookian Campanian Section given the petrophysically challenging nature of the play, representing an independent measurement relating to hydrocarbons (HC) and water that can be paired with the petrophysics to provide greater confidence in the identification of pay zones. RVS analysis and interpretation is done blind with no additional information beforehand significantly diminishing opportunities for bias in the interpretation of the results before being paired with other datasets. Beyond observations about HC and water content, significant additional information about the petroleum system such as oil quality (API gravity and biological activity), rock/reservoir properties, seals/compartments, and overall strength of the system was provided via RVS. Many of these results were used in the planning of subsequent well site activities like perforations and have been proven accurate in resulting flow tests. When combined with other data like 3D seismic the RVS data enables an immense appreciation of the world class asset that the multiple continuous accumulations in the Brookian Campanian Section of GBP's acreage represents.","PeriodicalId":158776,"journal":{"name":"Day 3 Wed, May 24, 2023","volume":"19 Suppl 1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133011823","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Optimization of production networks is key for managing efficient hydrocarbon production as part of closed-loop asset management. Large-scale surface network optimization is a challenging task that involves high nonlinearity with numerous constraints. In existing tools, the computational cost of solving the surface network optimization can exponentially increase with the size and complexities of the network using traditional approaches involving nonlinear programming methods. In this study, we accelerate the large-scale surface network optimization by using a distributed agent optimization algorithm called alternating direction method of multipliers (ADMM). We develop and apply the ADMM algorithm for large-scale network optimization with over 1000 wells and interconnecting pipelines. In the ADMM framework, a large-scale network system is broken down into many small sub-network systems. Then, a smaller optimization problem is formulated for each sub-network. These sub-network optimization problems are solved in parallel using multiple computer cores so that the entire system optimization will be accelerated. A large-scale surface network involves many inequality and equality constraints, which are effectively handled by using augmented Lagrangian method to enhance the robustness of convergence quality. Additionally, proxy or hybrid models can also be used for pipe flow and pressure calculation for every network segment to further speed up the optimization. The proposed ADMM optimization method is validated by several synthetic cases. We first apply the proposed method to surface network simulation problems of various sizes and complexities (configurations, fluid types, pressure regimes, etc.), where the pressure for all nodes and fluxes in all links will be calculated with a specified separator pressure and reservoir pressures. High accuracy was obtained from the ADMM framework compared with a commercial simulator. Next, the ADMM is applied to network optimization problems, where we optimize the pressure drop across a surface choke for every well to maximize oil production. In a large-scale network case with over 1000 wells, we achieve 2X – 3X speedups in computation time with reasonable accuracy from the ADMM framework compared with benchmarks. Finally, we apply the proposed method to a field case, and validate that the ADMM framework properly works for the actual field applications. A novel framework for surface network optimization was developed using the distributed agent optimization algorithm. The proposed framework provides superior computational efficiency for large- scale network optimization problems compared with existing benchmark methods. It enables more efficient and frequent decision-making of large-scale petroleum field management to maximize the hydrocarbon production subject to numerous system constraints.
{"title":"Distributed Agent Optimization for Large-Scale Network Models","authors":"M. Nagao, S. Sankaran, Zhenyu Guo","doi":"10.2118/213022-ms","DOIUrl":"https://doi.org/10.2118/213022-ms","url":null,"abstract":"\u0000 Optimization of production networks is key for managing efficient hydrocarbon production as part of closed-loop asset management. Large-scale surface network optimization is a challenging task that involves high nonlinearity with numerous constraints. In existing tools, the computational cost of solving the surface network optimization can exponentially increase with the size and complexities of the network using traditional approaches involving nonlinear programming methods. In this study, we accelerate the large-scale surface network optimization by using a distributed agent optimization algorithm called alternating direction method of multipliers (ADMM).\u0000 We develop and apply the ADMM algorithm for large-scale network optimization with over 1000 wells and interconnecting pipelines. In the ADMM framework, a large-scale network system is broken down into many small sub-network systems. Then, a smaller optimization problem is formulated for each sub-network. These sub-network optimization problems are solved in parallel using multiple computer cores so that the entire system optimization will be accelerated. A large-scale surface network involves many inequality and equality constraints, which are effectively handled by using augmented Lagrangian method to enhance the robustness of convergence quality. Additionally, proxy or hybrid models can also be used for pipe flow and pressure calculation for every network segment to further speed up the optimization.\u0000 The proposed ADMM optimization method is validated by several synthetic cases. We first apply the proposed method to surface network simulation problems of various sizes and complexities (configurations, fluid types, pressure regimes, etc.), where the pressure for all nodes and fluxes in all links will be calculated with a specified separator pressure and reservoir pressures. High accuracy was obtained from the ADMM framework compared with a commercial simulator. Next, the ADMM is applied to network optimization problems, where we optimize the pressure drop across a surface choke for every well to maximize oil production. In a large-scale network case with over 1000 wells, we achieve 2X – 3X speedups in computation time with reasonable accuracy from the ADMM framework compared with benchmarks. Finally, we apply the proposed method to a field case, and validate that the ADMM framework properly works for the actual field applications.\u0000 A novel framework for surface network optimization was developed using the distributed agent optimization algorithm. The proposed framework provides superior computational efficiency for large- scale network optimization problems compared with existing benchmark methods. It enables more efficient and frequent decision-making of large-scale petroleum field management to maximize the hydrocarbon production subject to numerous system constraints.","PeriodicalId":158776,"journal":{"name":"Day 3 Wed, May 24, 2023","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116550006","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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