Xiangru Chen, Xin Tang, Cheng Liu, Xiaoyi Zhou, Sen Guo, Hong Yin
High-temperature pore reconstruction technology is a reservoir reconstruction measure that has emerged in recent years. It is of great significance to study the variation in pore structure characteristics of shale under high temperature for reservoir reconstruction. To study the effect of high temperature on shale pores, scanning electron microscopy (SEM) experiments and fluid injection experiments were used to analyze the variation of pore structure characteristics under high temperature. Studies have shown that temperature has a great influence on the morphology and distribution characteristics of shale pores. In particular, there is a temperature between 300°C and 400°C that is suitable for modifying pores. The distribution characteristics, surface area, and volume of pores vary dramatically under this temperature threshold. The pore morphology and distribution characteristics changed from small and sparse to large and dense. The Brunauer-Emmett-Teller (BET) surface area increased by 95%. The cumulative surface area of Barrett-Joyner-Halenda (BJH) adsorption and desorption increased by 71.7% and 72%, respectively. The pore volume of the 2-nm to 20-nm pore size increased by 63.2%. The pore volume of pore sizes greater than 20 nm increased by 191.6%. The pore variation characteristics were in line with the typing law, and the fitting result R2 ranged from 0.92201 to 0.99882.
{"title":"Implications of Temperature for the Modification of High-Overmature Shale Reservoirs: Experimental and Numerical Analysis","authors":"Xiangru Chen, Xin Tang, Cheng Liu, Xiaoyi Zhou, Sen Guo, Hong Yin","doi":"10.2118/219762-pa","DOIUrl":"https://doi.org/10.2118/219762-pa","url":null,"abstract":"\u0000 High-temperature pore reconstruction technology is a reservoir reconstruction measure that has emerged in recent years. It is of great significance to study the variation in pore structure characteristics of shale under high temperature for reservoir reconstruction. To study the effect of high temperature on shale pores, scanning electron microscopy (SEM) experiments and fluid injection experiments were used to analyze the variation of pore structure characteristics under high temperature. Studies have shown that temperature has a great influence on the morphology and distribution characteristics of shale pores. In particular, there is a temperature between 300°C and 400°C that is suitable for modifying pores. The distribution characteristics, surface area, and volume of pores vary dramatically under this temperature threshold. The pore morphology and distribution characteristics changed from small and sparse to large and dense. The Brunauer-Emmett-Teller (BET) surface area increased by 95%. The cumulative surface area of Barrett-Joyner-Halenda (BJH) adsorption and desorption increased by 71.7% and 72%, respectively. The pore volume of the 2-nm to 20-nm pore size increased by 63.2%. The pore volume of pore sizes greater than 20 nm increased by 191.6%. The pore variation characteristics were in line with the typing law, and the fitting result R2 ranged from 0.92201 to 0.99882.","PeriodicalId":22252,"journal":{"name":"SPE Journal","volume":null,"pages":null},"PeriodicalIF":3.6,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140760280","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Moises Velasco-Lozano, M. Balhoff, Luis E. Diaz-Paulino, Simón López-Ramírez, Ramiro Galvan-Castro
Chemical tracer modeling in porous media plays a key role in subsurface applications including oil recovery, aquifer remediation, and geothermal energy production. In oil reservoirs, chemical tracers are critical to quantifying the remaining oil saturation in porous media after displacing processes, enabling the correct evaluation of the sweep efficiency of recovery methods at the field scale. Even though the transport of solutes under single-phase flow has been modeled extensively with numerous solutions, there are no existing mathematical approaches to examine the displacement of solutes in two-phase flow conditions. Therefore, we present in this research work the first analytical solutions derived to model the transport of ideal and partitioning tracers in porous media with mobile water and oil phases. The models presented are derived from the classic study of fluid displacement by viscous forces and the analysis of dynamic phase distribution in porous media, where key transformation variables are introduced to simplify the nonlinear advection-dispersion equation (ADE) into a conventional partial differential expression. In our derivation process, it is recognized that the dispersion effect can be superimposed onto an ideal concentration front via a singular perturbation expansion, resulting in practical solutions that do not require complex numerical calculations or inversion methods. The solutions derived are verified with numerical simulations and validated with experimental data under different flow conditions for the transport of ideal and partitioning tracers, demonstrating that the complex mechanisms of hydrodynamic dispersion, partitioning, and adsorption are accurately modeled under two-phase flow. Thus, our solutions can be used to rapidly evaluate tracer transport under the existing flow conditions in porous media, significantly reducing the number of experiments and simulations to characterize and select the correct tracer to be used in field applications.
{"title":"Modeling of Chemical Tracers for Two-Phase Flow in Advective-Dominated Porous Media at Core Scale","authors":"Moises Velasco-Lozano, M. Balhoff, Luis E. Diaz-Paulino, Simón López-Ramírez, Ramiro Galvan-Castro","doi":"10.2118/219730-pa","DOIUrl":"https://doi.org/10.2118/219730-pa","url":null,"abstract":"\u0000 Chemical tracer modeling in porous media plays a key role in subsurface applications including oil recovery, aquifer remediation, and geothermal energy production. In oil reservoirs, chemical tracers are critical to quantifying the remaining oil saturation in porous media after displacing processes, enabling the correct evaluation of the sweep efficiency of recovery methods at the field scale. Even though the transport of solutes under single-phase flow has been modeled extensively with numerous solutions, there are no existing mathematical approaches to examine the displacement of solutes in two-phase flow conditions. Therefore, we present in this research work the first analytical solutions derived to model the transport of ideal and partitioning tracers in porous media with mobile water and oil phases.\u0000 The models presented are derived from the classic study of fluid displacement by viscous forces and the analysis of dynamic phase distribution in porous media, where key transformation variables are introduced to simplify the nonlinear advection-dispersion equation (ADE) into a conventional partial differential expression. In our derivation process, it is recognized that the dispersion effect can be superimposed onto an ideal concentration front via a singular perturbation expansion, resulting in practical solutions that do not require complex numerical calculations or inversion methods. The solutions derived are verified with numerical simulations and validated with experimental data under different flow conditions for the transport of ideal and partitioning tracers, demonstrating that the complex mechanisms of hydrodynamic dispersion, partitioning, and adsorption are accurately modeled under two-phase flow. Thus, our solutions can be used to rapidly evaluate tracer transport under the existing flow conditions in porous media, significantly reducing the number of experiments and simulations to characterize and select the correct tracer to be used in field applications.","PeriodicalId":22252,"journal":{"name":"SPE Journal","volume":null,"pages":null},"PeriodicalIF":3.6,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140760046","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This study analyzes the production behaviors of six deep coalbed-methane (CBM) wells (>1980 m) completed in the Ordos Basin and presents a machine-learning method to predict gas production for six target wells. The production behaviors of target wells are characterized with several months of rapidly declining pressure, following by several years of stabilized gas rate and pressure. Production data analysis suggests a relatively large amount of free gas (but limited free water) in coal seams under in-situ condition. The production mechanisms generally transit from free-gas expansion and fracture/cleat closure at early stage to gas desorption at later stage. We treated the target wells’ production data as time-series data and applied the Long Short-Term Memory (LSTM) model on the target wells for gas-rate predictions. We also employed a Bayesian-probabilistic method to optimize the LSTM model (BO-LSTM). Our results demonstrate the BO-LSTM model’s robustness in gas-rate predictions for target wells. Also, treating casing pressure and liquid level as inputs is sufficient for the BO-LSTM model to reach a reliable production forecast. This study provides a promising tool to forecast the gas production of deep-CBM wells using surface rates and pressure data. The findings of this study may guide the reservoir management and development-strategy optimizations of deep-CBM reservoirs.
{"title":"Production Forecast of Deep-Coalbed-Methane Wells Based on Long Short-Term Memory and Bayesian Optimization","authors":"Danqun Wang, Zhiping Li, Yingkun Fu","doi":"10.2118/219749-pa","DOIUrl":"https://doi.org/10.2118/219749-pa","url":null,"abstract":"\u0000 This study analyzes the production behaviors of six deep coalbed-methane (CBM) wells (>1980 m) completed in the Ordos Basin and presents a machine-learning method to predict gas production for six target wells. The production behaviors of target wells are characterized with several months of rapidly declining pressure, following by several years of stabilized gas rate and pressure. Production data analysis suggests a relatively large amount of free gas (but limited free water) in coal seams under in-situ condition. The production mechanisms generally transit from free-gas expansion and fracture/cleat closure at early stage to gas desorption at later stage. We treated the target wells’ production data as time-series data and applied the Long Short-Term Memory (LSTM) model on the target wells for gas-rate predictions. We also employed a Bayesian-probabilistic method to optimize the LSTM model (BO-LSTM). Our results demonstrate the BO-LSTM model’s robustness in gas-rate predictions for target wells. Also, treating casing pressure and liquid level as inputs is sufficient for the BO-LSTM model to reach a reliable production forecast. This study provides a promising tool to forecast the gas production of deep-CBM wells using surface rates and pressure data. The findings of this study may guide the reservoir management and development-strategy optimizations of deep-CBM reservoirs.","PeriodicalId":22252,"journal":{"name":"SPE Journal","volume":null,"pages":null},"PeriodicalIF":3.6,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140778991","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Hong Pang, Duo-lin Wang, Tong Wu, Rui Wang, Xu Dai, Meng Lu, Zhejun Pan
Relative permeability models are essential in describing the multiphase fluid flow in reservoir rocks. Literature work has shown that the existing theoretical models of relative permeability cannot perfectly describe the two-phase flow experimental data in fractures because those models are mostly developed for porous media (such as sandstone) or proposed without fully taking the specific characteristics of two-phase flow into consideration. In this paper, we propose a theoretical two-phase flow relative permeability model based on the tortuous flow channels, considering the structural characteristics of two-phase flow in the fractures. This model considers that the gas and liquid flow through different channels of different shapes and sizes at the same time. The formula for two-phase relative permeability was derived from cubic law in fracture and Darcy’s law, with the influence of the slip effect of the gas phase also considered. The results from different models were compared using several series of experimental data. The model proposed in this paper has a better fit than the others for the raw experimental data. This study demonstrates that it is crucial to take the flow paths and distribution of the two phases into consideration to model the two-phase flow in fracture accurately. This work also found that the tortuosity of the gas channel at the irreducible liquid saturation has a negative effect on gas relative permeability but positive to liquid relative permeability. Moreover, the model demonstrates that the decrease in aperture leads to an increase in the gas relative permeability due to gas slippage, while the impact of gas slippage reduces under high pressure.
{"title":"An Analytical Relative Permeability Model Considering Flow Path Structural Characteristics for Gas-Liquid Two-Phase Flow in Shale Fracture","authors":"Hong Pang, Duo-lin Wang, Tong Wu, Rui Wang, Xu Dai, Meng Lu, Zhejun Pan","doi":"10.2118/219748-pa","DOIUrl":"https://doi.org/10.2118/219748-pa","url":null,"abstract":"\u0000 Relative permeability models are essential in describing the multiphase fluid flow in reservoir rocks. Literature work has shown that the existing theoretical models of relative permeability cannot perfectly describe the two-phase flow experimental data in fractures because those models are mostly developed for porous media (such as sandstone) or proposed without fully taking the specific characteristics of two-phase flow into consideration. In this paper, we propose a theoretical two-phase flow relative permeability model based on the tortuous flow channels, considering the structural characteristics of two-phase flow in the fractures. This model considers that the gas and liquid flow through different channels of different shapes and sizes at the same time. The formula for two-phase relative permeability was derived from cubic law in fracture and Darcy’s law, with the influence of the slip effect of the gas phase also considered. The results from different models were compared using several series of experimental data. The model proposed in this paper has a better fit than the others for the raw experimental data. This study demonstrates that it is crucial to take the flow paths and distribution of the two phases into consideration to model the two-phase flow in fracture accurately. This work also found that the tortuosity of the gas channel at the irreducible liquid saturation has a negative effect on gas relative permeability but positive to liquid relative permeability. Moreover, the model demonstrates that the decrease in aperture leads to an increase in the gas relative permeability due to gas slippage, while the impact of gas slippage reduces under high pressure.","PeriodicalId":22252,"journal":{"name":"SPE Journal","volume":null,"pages":null},"PeriodicalIF":3.6,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140773836","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Statistically, oil and gas production can generate up to 20 times the oil equivalent of produced water. The composition of produced water samples reflects its source, its interactions with reservoir rocks, and downhole (DH) facilities, which are critical for basin evolution, water source determination, and the monitoring, management, and optimization of oil and gas production. For example, scale and corrosion, two of the most severe flow assurance issues accompanied by produced water, can lead to billions of dollars lost every year. However, few studies have developed a standard protocol to extract such valuable information from produced water compositions due to a lack of data and professional models. Using produced water geochemical data from the Appalachian Basin, one of the largest natural gas producers in the US, from the United States Geological Survey (USGS) Produced Waters Geochemical Database (PWGD), we developed a standard protocol to investigate the produced water source, evolution history, and scale and corrosion risks under both DH and surface conditions by means of incorporating the professional models for water-rock interaction and corrosion. The results show that the produced water from the Appalachian Basin possibly evolves from seawater evaporation following a typical evolution pattern of ion concentration and water isotopes, while a group of time-elapsed samples indicates that such an evolution pattern can also be due to the mixture of the injected water and reservoir water. In addition, most produced water samples show obvious risks of mineral scaling (e.g., calcite, barite, and siderite) and CO2 corrosion with corresponding mitigation strategies recommended. This study not only developed a reliable data processing and analysis protocol but also showed the valuable information a systematic analysis of produced water samples can provide for actual oil and gas production.
{"title":"Evaluating Source, Scale Risk, and Corrosion Risk of the Produced Water Samples from the Appalachian Basin Based on a Geochemical Database","authors":"Zhaoyi Dai, Jiahe Zhang, Huiying Yuan, Huanyu Liu, Kui Zhang, Shucheng Xie","doi":"10.2118/219757-pa","DOIUrl":"https://doi.org/10.2118/219757-pa","url":null,"abstract":"\u0000 Statistically, oil and gas production can generate up to 20 times the oil equivalent of produced water. The composition of produced water samples reflects its source, its interactions with reservoir rocks, and downhole (DH) facilities, which are critical for basin evolution, water source determination, and the monitoring, management, and optimization of oil and gas production. For example, scale and corrosion, two of the most severe flow assurance issues accompanied by produced water, can lead to billions of dollars lost every year. However, few studies have developed a standard protocol to extract such valuable information from produced water compositions due to a lack of data and professional models. Using produced water geochemical data from the Appalachian Basin, one of the largest natural gas producers in the US, from the United States Geological Survey (USGS) Produced Waters Geochemical Database (PWGD), we developed a standard protocol to investigate the produced water source, evolution history, and scale and corrosion risks under both DH and surface conditions by means of incorporating the professional models for water-rock interaction and corrosion. The results show that the produced water from the Appalachian Basin possibly evolves from seawater evaporation following a typical evolution pattern of ion concentration and water isotopes, while a group of time-elapsed samples indicates that such an evolution pattern can also be due to the mixture of the injected water and reservoir water. In addition, most produced water samples show obvious risks of mineral scaling (e.g., calcite, barite, and siderite) and CO2 corrosion with corresponding mitigation strategies recommended. This study not only developed a reliable data processing and analysis protocol but also showed the valuable information a systematic analysis of produced water samples can provide for actual oil and gas production.","PeriodicalId":22252,"journal":{"name":"SPE Journal","volume":null,"pages":null},"PeriodicalIF":3.6,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140772929","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In unconventional shale and tight reservoirs, the concept of stimulated reservoir volume (SRV) is used to correlate the volume of total injected proppant with well performance. The SRV configuration consists of primary fractures connected to the wellbore and secondary fractures intersecting primary fractures. SRV productivity is determined by fracture conductivity, fracture dimensions, and network complexity, which also vary with time. This work presents an extension of the unified-fracture-design (UFD) approach to account for not only the pseudosteady state (PSS) but also transient flow regimes and ultimately optimize SRV for maximizing well performance. A generalized productivity index (PI) for both the transient and PSS regimes is presented to improve well performance by searching for the maximum PI over time. In addition, a surrogate model is developed to accelerate the optimization. This study demonstrates that the UFD enables the determination of the optimal fracture network conductivity and complexity that contribute to the maximum PI with a given proppant volume. The optimal SRV design is time-dependent until the PSS is reached. The surrogate model not only improves the computational efficiency but also delivers high precision, which means far less computational burden than the traditional parametric-sensitivity analysis.
{"title":"Optimization Method for Fracture-Network Design under Transient and Pseudosteady Conditions Using Unified-Fracture-Design and Deep-Learning Approaches","authors":"Junlei Wang, Yunsheng Wei, Yuewei Pan, Wei Yu","doi":"10.2118/219745-pa","DOIUrl":"https://doi.org/10.2118/219745-pa","url":null,"abstract":"\u0000 In unconventional shale and tight reservoirs, the concept of stimulated reservoir volume (SRV) is used to correlate the volume of total injected proppant with well performance. The SRV configuration consists of primary fractures connected to the wellbore and secondary fractures intersecting primary fractures. SRV productivity is determined by fracture conductivity, fracture dimensions, and network complexity, which also vary with time. This work presents an extension of the unified-fracture-design (UFD) approach to account for not only the pseudosteady state (PSS) but also transient flow regimes and ultimately optimize SRV for maximizing well performance. A generalized productivity index (PI) for both the transient and PSS regimes is presented to improve well performance by searching for the maximum PI over time. In addition, a surrogate model is developed to accelerate the optimization. This study demonstrates that the UFD enables the determination of the optimal fracture network conductivity and complexity that contribute to the maximum PI with a given proppant volume. The optimal SRV design is time-dependent until the PSS is reached. The surrogate model not only improves the computational efficiency but also delivers high precision, which means far less computational burden than the traditional parametric-sensitivity analysis.","PeriodicalId":22252,"journal":{"name":"SPE Journal","volume":null,"pages":null},"PeriodicalIF":3.6,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140788570","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
T.P. Mello, M. N. Borges Filho, Rodrigo F. O. Borges, Rodrigo S. C. Ferraz, A. T. Waldmann, C. Scheid, L. A. C. Meleiro, L. Calçada
Among all the systems that make up a drilling operation, the production and correction of drilling fluid can be considered the heart of the process. Among the main objectives of the drilling fluid are to cool the drill bit and maintain the pressure gradient inside the drilling well, which is done by controlling its density. Another important function is transporting the cuttings from the bottom to the surface and keeping them in suspension in case of stoppage, which directly depends on the viscosity of the drilling fluid. Density and viscosity must be constantly maintained within an operational window, and failures can lead to serious accidents, even the loss of the well. Currently, this control is done manually: An operator collects samples of the fluid and takes them for analysis in the laboratory and subsequently makes the necessary corrections by manually adding products to the fluid. To reduce process dead time, keep personnel on board, and increase operation safety, a control and monitoring system is necessary. Fuzzy logic was chosen because it can be combined with classical methods, is cheap to develop and implement, and can be customized in terms of natural language, capturing the knowledge acquired by operators from equipment operation, bench tests, etc. This work aimed to develop a novel real-time monitoring and fuzzy-based system for simultaneous control of the apparent viscosity and density of non-Newtonian fluids, dealing with the inevitable interactions between them in a pilot experimental unit. A pilot plant was built to evaluate the fuzzy system approach for modeling and controlling of density and apparent viscosity of drilling fluids. The pilot flow loop comprises a mixing tank, solids vibrating feeders, and a water-dosing pump. The unit was instrumented with online sensors to measure fluid density, temperature, flow rate, differential pressure, and viscosity. The apparent viscosity and density of the non-Newtonian fluid were controlled by manipulating the dosage of carboxymethylcellulose (CMC), barite, and water. The proposed methodology was compared to a classical proportional-integral-derivative (PID) controller in servo and regulatory scenarios for apparent viscosity and density. The results showed that the fuzzy controller dealt adequately with the effect of variable interactions, keeping both variables within their setpoint ranges, demonstrating the ability to control them individually despite their interactions. These results also showed that the fuzzy-based controller could easily be integrated into a diagnostic-predictive monitoring system to control fluid properties, accomplishing setpoint changes and rejecting undesirable disturbances presenting a maximum overshoot of 7.5% for apparent viscosity and 0.3% for density.
{"title":"Fuzzy-Based Control System of Drilling Fluids Density and Apparent Viscosity Simultaneously: An Alternative Strategy to Support Autonomous Drilling Operations","authors":"T.P. Mello, M. N. Borges Filho, Rodrigo F. O. Borges, Rodrigo S. C. Ferraz, A. T. Waldmann, C. Scheid, L. A. C. Meleiro, L. Calçada","doi":"10.2118/219492-pa","DOIUrl":"https://doi.org/10.2118/219492-pa","url":null,"abstract":"\u0000 Among all the systems that make up a drilling operation, the production and correction of drilling fluid can be considered the heart of the process. Among the main objectives of the drilling fluid are to cool the drill bit and maintain the pressure gradient inside the drilling well, which is done by controlling its density. Another important function is transporting the cuttings from the bottom to the surface and keeping them in suspension in case of stoppage, which directly depends on the viscosity of the drilling fluid. Density and viscosity must be constantly maintained within an operational window, and failures can lead to serious accidents, even the loss of the well. Currently, this control is done manually: An operator collects samples of the fluid and takes them for analysis in the laboratory and subsequently makes the necessary corrections by manually adding products to the fluid. To reduce process dead time, keep personnel on board, and increase operation safety, a control and monitoring system is necessary. Fuzzy logic was chosen because it can be combined with classical methods, is cheap to develop and implement, and can be customized in terms of natural language, capturing the knowledge acquired by operators from equipment operation, bench tests, etc. This work aimed to develop a novel real-time monitoring and fuzzy-based system for simultaneous control of the apparent viscosity and density of non-Newtonian fluids, dealing with the inevitable interactions between them in a pilot experimental unit. A pilot plant was built to evaluate the fuzzy system approach for modeling and controlling of density and apparent viscosity of drilling fluids. The pilot flow loop comprises a mixing tank, solids vibrating feeders, and a water-dosing pump. The unit was instrumented with online sensors to measure fluid density, temperature, flow rate, differential pressure, and viscosity. The apparent viscosity and density of the non-Newtonian fluid were controlled by manipulating the dosage of carboxymethylcellulose (CMC), barite, and water. The proposed methodology was compared to a classical proportional-integral-derivative (PID) controller in servo and regulatory scenarios for apparent viscosity and density. The results showed that the fuzzy controller dealt adequately with the effect of variable interactions, keeping both variables within their setpoint ranges, demonstrating the ability to control them individually despite their interactions. These results also showed that the fuzzy-based controller could easily be integrated into a diagnostic-predictive monitoring system to control fluid properties, accomplishing setpoint changes and rejecting undesirable disturbances presenting a maximum overshoot of 7.5% for apparent viscosity and 0.3% for density.","PeriodicalId":22252,"journal":{"name":"SPE Journal","volume":null,"pages":null},"PeriodicalIF":3.6,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140769945","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Guoqiang An, Hai Sun, Xiangdong Ye, Aifen Li, Wanjian Guo, Shuaishi Fu, Shiqi Liu, Yongchun Zhu, Zhuocheng Hu
Thermal recovery techniques serve as the primary approach for developing heavy oil due to its high viscosity and poor flowability. In this study, we established a high-temperature and high-pressure 3D physical experimental and numerical model based on the unique reservoir characteristics of the sand-mud interlayer in the Long Lake oil sands of Canada, using similarity criteria. Physical and numerical experiments employing steam-assisted gravity drainage (SAGD) were conducted to investigate the impact of sand-mud interlayer properties on the expansion limit of steam chambers during SAGD development. The results indicate that the expansion mode and limit of the steam chamber play a decisive role in heavy oil mobilization. Notably, heat loss during steam chamber expansion and the flow resistance caused by the interlayer are critical factors influencing the SAGD process. The presence of the interlayer extends the mobilization range in the lower portion of the reservoir, but it also limits the upward expansion of the steam chamber, resulting in a reduced mobilization range above the interlayer. Moreover, the steam chamber above the interlayer exhibits a distinct expansion pattern, featuring concave sides and a convex middle, resembling a “positive triangle.” Furthermore, the properties of the sand-mud interlayer and production parameters significantly affect the expansion limit of the steam chamber. Permeability and position exert a substantial impact on recovery, whereas thickness has a minor influence. Specifically, at an injection rate of 20 mL·min–1, steam quality of approximately 0.7, and a production/injection ratio of approximately 1.0, the steam chamber can successfully penetrate interlayers with a thickness of either 3.5 m and a permeability of 100×10−3 μm2 or 4.5 m and a permeability of 200×10−3 μm2.
{"title":"Research on the Influence of Sand-Mud Interlayer Properties on the Expansion of SAGD Steam Chamber","authors":"Guoqiang An, Hai Sun, Xiangdong Ye, Aifen Li, Wanjian Guo, Shuaishi Fu, Shiqi Liu, Yongchun Zhu, Zhuocheng Hu","doi":"10.2118/219738-pa","DOIUrl":"https://doi.org/10.2118/219738-pa","url":null,"abstract":"\u0000 Thermal recovery techniques serve as the primary approach for developing heavy oil due to its high viscosity and poor flowability. In this study, we established a high-temperature and high-pressure 3D physical experimental and numerical model based on the unique reservoir characteristics of the sand-mud interlayer in the Long Lake oil sands of Canada, using similarity criteria. Physical and numerical experiments employing steam-assisted gravity drainage (SAGD) were conducted to investigate the impact of sand-mud interlayer properties on the expansion limit of steam chambers during SAGD development. The results indicate that the expansion mode and limit of the steam chamber play a decisive role in heavy oil mobilization. Notably, heat loss during steam chamber expansion and the flow resistance caused by the interlayer are critical factors influencing the SAGD process. The presence of the interlayer extends the mobilization range in the lower portion of the reservoir, but it also limits the upward expansion of the steam chamber, resulting in a reduced mobilization range above the interlayer. Moreover, the steam chamber above the interlayer exhibits a distinct expansion pattern, featuring concave sides and a convex middle, resembling a “positive triangle.” Furthermore, the properties of the sand-mud interlayer and production parameters significantly affect the expansion limit of the steam chamber. Permeability and position exert a substantial impact on recovery, whereas thickness has a minor influence. Specifically, at an injection rate of 20 mL·min–1, steam quality of approximately 0.7, and a production/injection ratio of approximately 1.0, the steam chamber can successfully penetrate interlayers with a thickness of either 3.5 m and a permeability of 100×10−3 μm2 or 4.5 m and a permeability of 200×10−3 μm2.","PeriodicalId":22252,"journal":{"name":"SPE Journal","volume":null,"pages":null},"PeriodicalIF":3.6,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140757555","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
C. Urdaneta, Cheolkyun Jeong, Xuqing Wu, Jiefu Chen
The urgent global need to reduce CO2 emissions necessitates the development of sustainable power generation sources. Geothermal power emerges as a renewable and dependable energy option, harnessing the Earth’s natural heat sources for electricity generation. Unlike other renewables, geothermal energy offers uninterrupted power, immune to weather conditions. However, its efficiency hinges on technological innovation, particularly in the challenging realm of geothermal drilling. Rate of penetration (ROP) is a crucial drilling performance metric, and this study explores how deep learning models, particularly transformers, can optimize ROP prediction. Leveraging data from Utah Frontier Observatory for Research in Geothermal Energy (FORGE), we analyze the relationship between drilling parameters and ROP. Traditional drilling optimization methods face limitations, as drilling dysfunctions can disrupt the linear relationship between ROP and weight on bit (WOB). We propose a dynamic approach that allows adapting drilling parameters in real time to optimize ROP. Our experiments investigate optimal sampling intervals and forecast horizons for ROP prediction. We find that a 60-second sampling interval maximizes the transformer model’s forecasting accuracy. Additionally, we explore retraining to fine-tune models for specific wells, improving forecasting performance. Our transformer-based ROP forecaster outperforms deep learning models, achieving a low overall 5.22% symmetrical mean average percentage error (SMAPE) over a forecast horizon of 10 minutes. This model offers opportunities for cost-effective drilling optimization, with real-time accuracy, speed, and scalability. Future work will focus on larger data sets and integration with drilling automation systems to further enhance the model’s practicality and effectiveness in the field.
{"title":"Deep Learning Method for Improving Rate of Penetration Prediction in Drilling","authors":"C. Urdaneta, Cheolkyun Jeong, Xuqing Wu, Jiefu Chen","doi":"10.2118/219746-pa","DOIUrl":"https://doi.org/10.2118/219746-pa","url":null,"abstract":"\u0000 The urgent global need to reduce CO2 emissions necessitates the development of sustainable power generation sources. Geothermal power emerges as a renewable and dependable energy option, harnessing the Earth’s natural heat sources for electricity generation. Unlike other renewables, geothermal energy offers uninterrupted power, immune to weather conditions. However, its efficiency hinges on technological innovation, particularly in the challenging realm of geothermal drilling. Rate of penetration (ROP) is a crucial drilling performance metric, and this study explores how deep learning models, particularly transformers, can optimize ROP prediction. Leveraging data from Utah Frontier Observatory for Research in Geothermal Energy (FORGE), we analyze the relationship between drilling parameters and ROP. Traditional drilling optimization methods face limitations, as drilling dysfunctions can disrupt the linear relationship between ROP and weight on bit (WOB). We propose a dynamic approach that allows adapting drilling parameters in real time to optimize ROP. Our experiments investigate optimal sampling intervals and forecast horizons for ROP prediction. We find that a 60-second sampling interval maximizes the transformer model’s forecasting accuracy. Additionally, we explore retraining to fine-tune models for specific wells, improving forecasting performance. Our transformer-based ROP forecaster outperforms deep learning models, achieving a low overall 5.22% symmetrical mean average percentage error (SMAPE) over a forecast horizon of 10 minutes. This model offers opportunities for cost-effective drilling optimization, with real-time accuracy, speed, and scalability. Future work will focus on larger data sets and integration with drilling automation systems to further enhance the model’s practicality and effectiveness in the field.","PeriodicalId":22252,"journal":{"name":"SPE Journal","volume":null,"pages":null},"PeriodicalIF":3.6,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140792275","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
With the vigorous exploitation of shale gas, the cost of drilling and production of shale gas wells, which can reduce the cost, has also received attention. Equal-diameter solid expandable tubular (SET) technology is one of the best choices at present. For this paper, we carried out a series of expansion experiments for 20G pipe, and the experimental results show that the pipe breaks and fails at 30% expansion ratio. The cracked pipe is analyzed by scanning electron microscopy (SEM), and the method to solve the failure of cracked pipe is proposed. In addition, a 3D dynamic model is established to study the relationship between the inner diameter, wall thickness, expansion ratio, and ultimate expansion ratio of the pipeline. The study results show that (1) SET made of 20G expanded successfully at 25% expansion ratio and failed at 30% expansion ratio, the fracture surface presents 45°, with typical shear failure characteristics; (2) SEM results showed that the pit characteristics were normal, the pipe was cracked under high stress, and the 20G pipe could not meet the expansion ratio of 30%; and (3) the maximum stress of 20G pipe during expansion is proportional to the expansion ratio. It is recommended that the SET expansion rate of 20G material should not exceed 26%. The research results will provide ideas and methods for the design of SET.
随着页岩气的大力开采，能够降低页岩气井钻采成本的技术也受到了关注。等直径固体可膨胀管（SET）技术是目前最好的选择之一。本文对 20G 管材进行了一系列膨胀实验，实验结果表明，管材在 30% 的膨胀率下会发生断裂和失效。通过扫描电子显微镜（SEM）对开裂的管道进行了分析，并提出了解决开裂管道失效的方法。此外，还建立了三维动态模型来研究管道内径、壁厚、膨胀比和极限膨胀比之间的关系。研究结果表明：（1）20G 材质的 SET 在 25% 的膨胀率下膨胀成功，在 30% 的膨胀率下失效，断裂面呈 45°，具有典型的剪切失效特征；（2）SEM 结果表明，凹坑特征正常，管道在高应力下开裂，20G 管道无法满足 30% 的膨胀率；（3）20G 管道在膨胀过程中的最大应力与膨胀率成正比。建议 20G 材料的 SET 伸缩率不应超过 26%。这些研究成果将为 SET 的设计提供思路和方法。
{"title":"Failure Analysis and Ultimate Expansion Mechanical Behavior Analysis of Thin-Walled Solid Expandable Tubular","authors":"Xiaohua Zhu, Feilong Cheng, C. Shi","doi":"10.2118/219743-pa","DOIUrl":"https://doi.org/10.2118/219743-pa","url":null,"abstract":"\u0000 With the vigorous exploitation of shale gas, the cost of drilling and production of shale gas wells, which can reduce the cost, has also received attention. Equal-diameter solid expandable tubular (SET) technology is one of the best choices at present. For this paper, we carried out a series of expansion experiments for 20G pipe, and the experimental results show that the pipe breaks and fails at 30% expansion ratio. The cracked pipe is analyzed by scanning electron microscopy (SEM), and the method to solve the failure of cracked pipe is proposed. In addition, a 3D dynamic model is established to study the relationship between the inner diameter, wall thickness, expansion ratio, and ultimate expansion ratio of the pipeline. The study results show that (1) SET made of 20G expanded successfully at 25% expansion ratio and failed at 30% expansion ratio, the fracture surface presents 45°, with typical shear failure characteristics; (2) SEM results showed that the pit characteristics were normal, the pipe was cracked under high stress, and the 20G pipe could not meet the expansion ratio of 30%; and (3) the maximum stress of 20G pipe during expansion is proportional to the expansion ratio. It is recommended that the SET expansion rate of 20G material should not exceed 26%. The research results will provide ideas and methods for the design of SET.","PeriodicalId":22252,"journal":{"name":"SPE Journal","volume":null,"pages":null},"PeriodicalIF":3.6,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140764577","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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