This study discusses the benefits and challenges of well monitoring for Gulong shale oil production.It examines the Unified Transient Analysis(UTA)method,which integrates rate and pressure data to monitor changes in f...This study discusses the benefits and challenges of well monitoring for Gulong shale oil production.It examines the Unified Transient Analysis(UTA)method,which integrates rate and pressure data to monitor changes in fracture surface area and production efficiency in real-time.The UTA method allows for early detection of production impairments and provides feedback to optimize drawdown pressure,enhancing production without damaging fracture conductivity.Analysis of production data from Well A in the Daqing Oilfield demonstrates the method's efficacy,particularly in managing choke size adjustments and identifying fracture conductivity degradation.Despite its benefits,challenges such as data quality,manual data analysis,and the need for automated choke management are highlighted.The study underscores the necessity of integrating intelligent monitoring technologies and automating workflows to optimize Gulong shale oil production.展开更多
Anthropogenic emissions reached 37.4 Gt/a in 2023,intensifying the need for effective carbon storage in subsurface formations to mitigate global warming.Carbon Capture and Storage(CCS)has emerged as a viable solution,...Anthropogenic emissions reached 37.4 Gt/a in 2023,intensifying the need for effective carbon storage in subsurface formations to mitigate global warming.Carbon Capture and Storage(CCS)has emerged as a viable solution,with over 43 operational sites worldwide and projections for more than 840 projects by 2040,potentially storing 2225 Mt CO_(2) annually.This review provides a comprehensive analysis of CCS technologies,focusing on the integrity,safety,and economic viability of storage sites,which are crucial for long-term success.It identifies knowledge gaps in existing research,revealing that most studies address specific aspects of CCS but lack integrated approaches combining data,technologies,risks,and economic assessments.Some studies emphasize numerical modeling and fault reactivation risks but overlook issues such as cement degradation and casing corrosion,which are critical to preventing wellbore leakage.Others explore CO_(2)-rock interactions without considering cement integrity or focus on cement degradation without accounting for other field-scale risks.This review bridges these gaps by examining failures across wellbores,reservoirs,and caprocks,including cement integrity,casing corrosion,uplifting,fault activation,and seismicity due to injection.It also covers numerical modeling,experimental work,and monitoring techniques to ensure CCS integrity.Additionally,this review assesses economic risks to build confidence in CCS deployment,offering a comprehensive framework to ensure secure and long-term CO_(2) storage in subsurface formations.展开更多
The characterization of kerogen nanopores is crucial for predicting the geostorage capacity and recoverability of natural gas in unconventional gas shale reservoirs.Towards this end,a powerful technique is presented w...The characterization of kerogen nanopores is crucial for predicting the geostorage capacity and recoverability of natural gas in unconventional gas shale reservoirs.Towards this end,a powerful technique is presented which integrates 2D NMR T_(1)-T_(2) relaxation measurements with molecular dynamics(MD)simulations of hydrocarbons confined in the nanopores of kerogen.The integrated NMR-MD technique is demonstrated using T_(1)-T_(2) measurements of kerogen isolates and organic-rich chalks saturated with heptane,together with MD simulations of heptane completely dissolved in a realistic kerogen model.The NMR-MD results are used to extract the swelling ratio and nanopore size distribution of kerogen as a function of depth in the reservoir.The effects of organic nanoconfinement on the T_(1) relaxation dispersion and T_(2) residual dipolar coupling of heptane are investigated,as well as the effect of downhole effective stress on the kerogen nanopore size as a function of depth and compaction.Potential applications in partially depleted gas shale reservoirs are discussed,including CO_(2) utilization/geostorage,geostorage of green H_(2),and integration of the NMR-MD technique with thermodynamic models for predicting the competitive sorption of gas mixtures in kerogen.展开更多
Characterization and optimization of physical and chemical properties of drilling fluids are critical for the efficiency and success of drilling operations.In particular,maintaining the optimal levels of solids conten...Characterization and optimization of physical and chemical properties of drilling fluids are critical for the efficiency and success of drilling operations.In particular,maintaining the optimal levels of solids content is essential for achieving the most effective fluid performance.Proper management of solids content also reduces the risk of tool failures.Traditional solids content analysis methods,such as retort analysis,require substantial human intervention and time,which can lead to inaccuracies,time-management issues,and increased operational risks.In contrast to human-intensive methods,machine learning may offer a viable alternative for solids content estimation due to its pattern-recognition capability.In this study,a large set of laboratory reports of drilling-fluid analyses from 130 oil wells around the world were compiled to construct a comprehensive data set.The relationships among various rheological parameters were analyzed using statistical methods and machine learning algorithms.Several machine learning algorithms of diverse classes,namely linear(linear regression,ridge regression,and ElasticNet regression),kernel-based(support vector machine)and ensemble tree-based(gradient boosting,XGBoost,and random forests)algorithms,were trained and tuned to estimate solids content from other readily available drilling fluid properties.Input variables were kept consistent across all models for interpretation and comparison purposes.In the final stage,different evaluation metrics were employed to evaluate and compare the performance of different classes of machine learning models.Among all algorithms tested,random forests algorithm was found to be the best predictive model resulting in consistently high accuracy.Further optimization of the random forests model resulted in a mean absolute percentage error(MAPE)of 3.9%and 9.6%and R^(2) of 0.99 and 0.93 for the training and testing sets,respectively.Analysis of residuals,their histograms and Q-Q normality plots showed Gaussian distributions with residuals that are scattered around a mean of zero within error ranges of±1%and±4%,for training and testing,respectively.The selected model was further validated by applying the rheological measurements from mud samples taken from an offshore well from the Gulf of Mexico.The model was able to estimate total solids content in those four mud samples with an average absolute error of 1.08% of total solids content.The model was then used to develop a web-based graphical-user-interface(GUI)application,which can be practically used at the rig site by engineers to optimize drilling fluid programs.The proposed model can complement automation workflows that are designed to measure fundamental rheological properties in real time during drilling operations.While a standard retort test can take approximately 2 h at the rig site,such kind of real-time estimations can help the rig personnel to timely optimize drilling fluids,with a potential of saving 2920 man-hours in a given year for a single drilling rig.展开更多
Polymer-based EOR methods in low-permeability reservoirs face injectivity issues and increased fracturing due to near wellbore plugging,as well as high-pressure gradients in these reservoirs.Polymer may cause pore blo...Polymer-based EOR methods in low-permeability reservoirs face injectivity issues and increased fracturing due to near wellbore plugging,as well as high-pressure gradients in these reservoirs.Polymer may cause pore blockage and undergo shear degradation and even oxidative degradation at high temperatures in the presence of very hard brine.Low-tension gas(LTG) flooding has the potential to be applied successfully for low-permeability carbonate reservoirs even in the presence of high formation brine salinity.In LTG flooding,the interfacial tension between oil and water is reduced to ultra-low values(10^-3 dyne/cm) by injecting an optimized surfactant formulation to maximize mobilization of residual oil post-waterflood.Gas(nitrogen,hydrocarbon gases or C02) is co-injected along with the surfactant slug to generate in situ foam which reduces the mobility ratio between the displaced(oil) and displacing phases,thus improving the displacement efficiency of the oil.In this work,the mechanism governing LTG flooding in low-permeability,high-salinity reservoirs was studied at a microscopic level using microemulsion properties and on a macroscopic scale by laboratory-scale coreflooding experiments.The main injection parameters studied were injected slug salinity and the interrelation between surfactant concentration and injected foam quality,and how they influence oil mobilization and displacement efficiency.Qualitative assessment of the results was performed by studying oil recovery,oil fractional flow,oil bank breakthrough and effluent salinity and pressure drop characteristics.展开更多
This work mainly studies the effect of fluid phase momentum transfer mechanisms on the acidizing results,including the retardation effect of the porous structure and the interaction between the fluid phase,such as vis...This work mainly studies the effect of fluid phase momentum transfer mechanisms on the acidizing results,including the retardation effect of the porous structure and the interaction between the fluid phase,such as viscous dissipation and inertial effect.The results show that the acid fluid momentum transfer is influenced by the complex porous structure and fluid viscous dissipation.Eventually,the Stokes-Darcy equation is recommended to be adopted to describe the fluid phase momentum transfer in the following numerical simulation studies of the carbonate acidizing process.Based on this model,a parametric research is carried out to investigate the impact of acid on rock physical characteristics in the stimulation process.Increasing the acid concentration appears to minimize the quantity of acid consumed for the breakthrough.The acid surface reaction rate has a considerable impact on the pore volume to breakthrough and the optimum acid injection rate.The influence of permeability on the acidizing results basically shows a negative correlation with the injection rate.The difference between the acidizing curves of different permeability gradually becomes insignificant with the decrease in injection rate.The existence of isolated fracture and vug significantly reduces acid consumption for the breakthrough.展开更多
This study extends an integrated field characterization in Eagle Ford by optimizing the numerical reservoir simulation of highly representative complex fractured systems through embedded discrete fracture modeling(EDF...This study extends an integrated field characterization in Eagle Ford by optimizing the numerical reservoir simulation of highly representative complex fractured systems through embedded discrete fracture modeling(EDFM). The bottom-hole flowing pressure was history-matched and the field production was forecasted after screening complex fracture scenarios with more than 100 000 fracture planes based on their propped-type. This work provided a greater understanding of the impact of complex-fractures proppant efficiency on the production. After compaction tables were included for each propped-type fracture group, the estimated pressure depletion showed that the effective drainage area can be smaller than the complex fracture network if modeled and screened by the EDFM method rather than unstructured gridding technique. The essential novel value of this work is the capability to couple EDFM with third-party fracture propagation simulation automatically, considering proppant intensity variation along the complex fractured systems. Thus, this work is pioneer to model complex fracture propagation and well interference accurately from fracture diagnostics and pseudo 3 D fracture propagation outcomes for multiple full wellbores to capture well completion effectiveness after myriads of sharper field simulation cases with EDFM.展开更多
To better understand the roles natural fractures play in porous media, an embedded discrete fracture model and streamline modeling method were combined to model natural fractures and compute the flow trajectory and ti...To better understand the roles natural fractures play in porous media, an embedded discrete fracture model and streamline modeling method were combined to model natural fractures and compute the flow trajectory and time of fluid in matrix and fractures systems. The effects of fracture conductivity, number of fractures and fracture locations on fluid flow trajectory and time were examined through analyzing the differences in water breakthrough time and sweeping volume of reservoirs with different fracture networks. When other conditions are the same, compared with homogeneous reservoir without fractures, the fractured reservoir has water breakthrough time 30% sooner and swept volume 10% smaller. Although increase of single fracture can lead to faster water breakthrough and smaller swept volume, adding more fractures wouldn't necessarily reach the same effect. The effect of water flooding is also related to the strike and position of fractures. Fractures in different strikes and positions can result in 20% discrepancy in water breakthrough time and 9% gap in swept volume. The shorter the fracture, the less its effect on fluid flow trajectory and time will be. The position of fracture has a strong influence on sweeping efficiency, and the change of one fracture position could bring about 1% variation in swept volume.展开更多
Molecular dynamics(MD)has served as a powerful tool for designing materials with reduced reliance on laboratory testing.However,the use of MD directly to treat the deformation and failure of materials at the mesoscale...Molecular dynamics(MD)has served as a powerful tool for designing materials with reduced reliance on laboratory testing.However,the use of MD directly to treat the deformation and failure of materials at the mesoscale is still largely beyond reach.In this work,we propose a learning framework to extract a peridynamics model as a mesoscale continuum surrogate from MD simulated material fracture data sets.Firstly,we develop a novel coarse-graining method,to automatically handle the material fracture and its corresponding discontinuities in the MD displacement data sets.Inspired by the weighted essentially non-oscillatory(WENO)scheme,the key idea lies at an adaptive procedure to automatically choose the locally smoothest stencil,then reconstruct the coarse-grained material displacement field as the piecewise smooth solutions containing discontinuities.Then,based on the coarse-grained MD data,a two-phase optimizationbased learning approach is proposed to infer the optimal peridynamics model with damage criterion.In the first phase,we identify the optimal nonlocal kernel function from the data sets without material damage to capture the material stiffness properties.Then,in the second phase,the material damage criterion is learnt as a smoothed step function from the data with fractures.As a result,a peridynamics surrogate is obtained.As a continuum model,our peridynamics surrogate model can be employed in further prediction tasks with different grid resolutions from training,and hence allows for substantial reductions in computational cost compared with MD.We illustrate the efficacy of the proposed approach with several numerical tests for the dynamic crack propagation problem in a single-layer graphene.Our tests show that the proposed data-driven model is robust and generalizable,in the sense that it is capable of modeling the initialization and growth of fractures under discretization and loading settings that are different from the ones used during training.展开更多
Increasing the production and utilization of shale gas is of great significance for building a clean and low-carbon energy system.Sharp decline of gas production has been widely observed in shale gas reservoirs.How to...Increasing the production and utilization of shale gas is of great significance for building a clean and low-carbon energy system.Sharp decline of gas production has been widely observed in shale gas reservoirs.How to forecast shale gas production is still challenging due to complex fracture networks,dynamic fracture properties,frac hits,complicated multiphase flow,and multi-scale flow as well as data quality and uncertainty.This work develops an integrated framework for evaluating shale gas well production based on data-driven models.Firstly,a comprehensive dominated-factor system has been established,including geological,drilling,fracturing,and production factors.Data processing and visualization are required to ensure data quality and determine final data set.A shale gas production evaluation model is developed to evaluate shale gas production levels.Finally,the random forest algorithm is used to forecast shale gas production.The prediction accuracy of shale gas production level is higher than 95%based on the shale gas reservoirs in China.Forty-one wells are randomly selected to predict cumulative gas production using the optimal regression model.The proposed shale gas production evaluation frame-work overcomes too many assumptions of analytical or semi-analytical models and avoids huge computation cost and poor generalization for numerical modelling.展开更多
Two-phase pipe flow occurs frequently in oil&gas industry,nuclear power plants,and CCUS.Reliable calculations of gas void fraction(or liquid holdup)play a central role in two-phase pipe flow models.In this paper w...Two-phase pipe flow occurs frequently in oil&gas industry,nuclear power plants,and CCUS.Reliable calculations of gas void fraction(or liquid holdup)play a central role in two-phase pipe flow models.In this paper we apply the fractional flow theory to multiphase flow in pipes and present a unified modeling framework for predicting the fluid phase volume fractions over a broad range of pipe flow conditions.Compared to existing methods and correlations,this new framework provides a simple,approximate,and efficient way to estimate the phase volume fraction in two-phase pipe flow without invoking flow patterns.Notably,existing correlations for estimating phase volume fraction can be transformed and expressed under this modeling framework.Different fractional flow models are applicable to different flow conditions,and they demonstrate good agreement against experimental data within 5%errors when compared with an experimental database comprising of 2754 data groups from 14literature sources,covering various pipe geometries,flow patterns,fluid properties and flow inclinations.The gas void fraction predicted by the framework developed in this work can be used as inputs to reliably model the hydraulic and thermal behaviors of two-phase pipe flows.展开更多
Supercritical CO2 fracturing is considered to be a new method for efficient exploitation of unconventional reservoirs,such as shale gas,coal bed methane,and tight sand stone gas.Supercritical CO2 has many special prop...Supercritical CO2 fracturing is considered to be a new method for efficient exploitation of unconventional reservoirs,such as shale gas,coal bed methane,and tight sand stone gas.Supercritical CO2 has many special properties including low viscosity,high diffusion coefficient,and lack of surface tension,which brings about great advantages for fracturing.However,these properties also cause several problems,such as difficulty in proppant transportation,high friction loss,and high pump displacement.In this paper,the above problems were analyzed by combining field test with laboratory study and specific solutions to these problems are given.The high frictionloss in the pipeline could be reduced by developing a new drag reducing agent and selecting large-size casing.Besides,for the problem of poor capacity in proppant carrying and sand plug,the methods of adding tackifier into supercritical CO2,increasing pump displacement and selecting ultralow density proppants are proposed.Moreover,for the problem of fast leak-off and high requirement for pump displacement,the displacement can be increased or the pad fluid can be injected into the reservoir.After solving the above three problems,the field test of supercritical CO2 fracturing can be conducted.The research results can promote the industrialization process of supercritical CO2 fracturing.展开更多
Gas transport mechanisms can be categorized into viscous flow and mass diffusion,both of which may coexist in a porous media with multiscale pore sizes.To determine the dominant transport mechanism and its contributio...Gas transport mechanisms can be categorized into viscous flow and mass diffusion,both of which may coexist in a porous media with multiscale pore sizes.To determine the dominant transport mechanism and its contribution to gas transport capacity,the gas viscous flow and mass diffusion processes are analyzed in single nanoscale pores via a theoretical method,and are simulated in 3D nanoporous media via pore-scale lattice Boltzmann methods.The apparent permeability from the viscous flow and apparent diffusivity from the mass diffusion are estimated.A dimensionless parameter,i.e.,the diffusion-flow ratio,is proposed to evaluate the dominant transport mechanism,which is a function of the apparent permeability,apparent diffusivity,bulk dynamic viscosity,and working pressure.The results show that the apparent permeability increases by approximately two orders of magnitude when the average Knudsen number(Kn_(avg))of the nanoporous media or Knudsen number(Kn)of single nanoscale pores increases from 0.1 to 10.Under the same conditions,the increment in the apparent diffusivity is only approximately one order of magnitude.When Kn<0.01,the apparent permeability has a lower bound(i.e.,absolute permeability).When Kn>10,the apparent diffusivity has an upper bound(i.e.,Knudsen diffusivity).The dominant transport mechanism in single nanoscale pores is the viscous flow for 0.01<Kn<100,where the maximum diffusion-flow ratio is less than one.In nanoporous media,the dominant transport relies heavily on Kn_(avg) and the structural parameters.For nanoporous media with the pore throat diameter of 3 nm,Kn_(avg)=0.2 is the critical point,above which the mass diffusion is dominant;otherwise,the viscous flow is dominant.As Kn_(avg) increases to 3.4,the mass diffusion is overwhelming,with the maximum diffusion-flow ratio reaching ~4.展开更多
The successful commercial development of high-quality middle-shallow and middle-deep shale gas in the Sichuan Basin marks a significant achievement. With the escalating energy demand, attention has shifted toward expl...The successful commercial development of high-quality middle-shallow and middle-deep shale gas in the Sichuan Basin marks a significant achievement. With the escalating energy demand, attention has shifted toward exploring and exploiting deep-buried, low-quality middle-shallow, and middle-deep shale gas reservoirs in China. This shift necessitates advancements in geological evaluation and engineering design. Here, the key issues related to sweet spot identification in shale gas reservoirs are introduced, and three correlated parameters (gas-in-place, microstructure, and permeability) are concisely overviewed. Numerous efforts and advances have been dedicated to characterizing these parameters in recent years, attempting to reveal the underlying mechanisms and identify the appropriate evaluation methods. However, challenges persist, and potential improvement opportunities are outlined here to provide insights for researchers.展开更多
Chemical enhanced oil recovery(CEOR)is well known for its success in recovering the trapped oil in reservoirs after waterflooding operations.In CEOR,synthetic chemicals are utilized to increase the capillary number or...Chemical enhanced oil recovery(CEOR)is well known for its success in recovering the trapped oil in reservoirs after waterflooding operations.In CEOR,synthetic chemicals are utilized to increase the capillary number or modify the mobility ratio of reservoirs;however,they are expensive and are associated with environmental concerns.Hence,the rise in environmental awareness paved the way for environmentally friendly and cheaper alternatives,such as green products,to replace synthetic chemicals.This paper comprehensively reviews recent studies on applying green products in CEOR.It also includes comparisons between the performance of several green products and their synthetic counterparts in CEOR.Moreover,limitations,cost,and environmental footprints are analyzed.Finally,the displacement efficiency of green chemicals and pertinent challenges in the field are highlighted.While the utilization of some natural materials in EOR still has an environmental impact,they constitute a safer option than synthetic chemicals.Furthermore,green materials are more affordable than synthetic chemicals that are commonly utilized,making them a financially viable option for EOR.An up-to-date overview is urgently needed due to the growth of natural chemical utilization in oil and gas applications.Promoting sustainable alternatives is essential to addressing the rise in global environmental concerns.展开更多
文摘This study discusses the benefits and challenges of well monitoring for Gulong shale oil production.It examines the Unified Transient Analysis(UTA)method,which integrates rate and pressure data to monitor changes in fracture surface area and production efficiency in real-time.The UTA method allows for early detection of production impairments and provides feedback to optimize drawdown pressure,enhancing production without damaging fracture conductivity.Analysis of production data from Well A in the Daqing Oilfield demonstrates the method's efficacy,particularly in managing choke size adjustments and identifying fracture conductivity degradation.Despite its benefits,challenges such as data quality,manual data analysis,and the need for automated choke management are highlighted.The study underscores the necessity of integrating intelligent monitoring technologies and automating workflows to optimize Gulong shale oil production.
文摘Anthropogenic emissions reached 37.4 Gt/a in 2023,intensifying the need for effective carbon storage in subsurface formations to mitigate global warming.Carbon Capture and Storage(CCS)has emerged as a viable solution,with over 43 operational sites worldwide and projections for more than 840 projects by 2040,potentially storing 2225 Mt CO_(2) annually.This review provides a comprehensive analysis of CCS technologies,focusing on the integrity,safety,and economic viability of storage sites,which are crucial for long-term success.It identifies knowledge gaps in existing research,revealing that most studies address specific aspects of CCS but lack integrated approaches combining data,technologies,risks,and economic assessments.Some studies emphasize numerical modeling and fault reactivation risks but overlook issues such as cement degradation and casing corrosion,which are critical to preventing wellbore leakage.Others explore CO_(2)-rock interactions without considering cement integrity or focus on cement degradation without accounting for other field-scale risks.This review bridges these gaps by examining failures across wellbores,reservoirs,and caprocks,including cement integrity,casing corrosion,uplifting,fault activation,and seismicity due to injection.It also covers numerical modeling,experimental work,and monitoring techniques to ensure CCS integrity.Additionally,this review assesses economic risks to build confidence in CCS deployment,offering a comprehensive framework to ensure secure and long-term CO_(2) storage in subsurface formations.
基金Vinegar Technologies LLC,Chevron Energy Technology Company,Rice University Consortium for Processes in Porous Media,and the American Chemical Society Petroleum Research Fund(No.ACS PRF 58859-ND6)for their financial support。
文摘The characterization of kerogen nanopores is crucial for predicting the geostorage capacity and recoverability of natural gas in unconventional gas shale reservoirs.Towards this end,a powerful technique is presented which integrates 2D NMR T_(1)-T_(2) relaxation measurements with molecular dynamics(MD)simulations of hydrocarbons confined in the nanopores of kerogen.The integrated NMR-MD technique is demonstrated using T_(1)-T_(2) measurements of kerogen isolates and organic-rich chalks saturated with heptane,together with MD simulations of heptane completely dissolved in a realistic kerogen model.The NMR-MD results are used to extract the swelling ratio and nanopore size distribution of kerogen as a function of depth in the reservoir.The effects of organic nanoconfinement on the T_(1) relaxation dispersion and T_(2) residual dipolar coupling of heptane are investigated,as well as the effect of downhole effective stress on the kerogen nanopore size as a function of depth and compaction.Potential applications in partially depleted gas shale reservoirs are discussed,including CO_(2) utilization/geostorage,geostorage of green H_(2),and integration of the NMR-MD technique with thermodynamic models for predicting the competitive sorption of gas mixtures in kerogen.
文摘Characterization and optimization of physical and chemical properties of drilling fluids are critical for the efficiency and success of drilling operations.In particular,maintaining the optimal levels of solids content is essential for achieving the most effective fluid performance.Proper management of solids content also reduces the risk of tool failures.Traditional solids content analysis methods,such as retort analysis,require substantial human intervention and time,which can lead to inaccuracies,time-management issues,and increased operational risks.In contrast to human-intensive methods,machine learning may offer a viable alternative for solids content estimation due to its pattern-recognition capability.In this study,a large set of laboratory reports of drilling-fluid analyses from 130 oil wells around the world were compiled to construct a comprehensive data set.The relationships among various rheological parameters were analyzed using statistical methods and machine learning algorithms.Several machine learning algorithms of diverse classes,namely linear(linear regression,ridge regression,and ElasticNet regression),kernel-based(support vector machine)and ensemble tree-based(gradient boosting,XGBoost,and random forests)algorithms,were trained and tuned to estimate solids content from other readily available drilling fluid properties.Input variables were kept consistent across all models for interpretation and comparison purposes.In the final stage,different evaluation metrics were employed to evaluate and compare the performance of different classes of machine learning models.Among all algorithms tested,random forests algorithm was found to be the best predictive model resulting in consistently high accuracy.Further optimization of the random forests model resulted in a mean absolute percentage error(MAPE)of 3.9%and 9.6%and R^(2) of 0.99 and 0.93 for the training and testing sets,respectively.Analysis of residuals,their histograms and Q-Q normality plots showed Gaussian distributions with residuals that are scattered around a mean of zero within error ranges of±1%and±4%,for training and testing,respectively.The selected model was further validated by applying the rheological measurements from mud samples taken from an offshore well from the Gulf of Mexico.The model was able to estimate total solids content in those four mud samples with an average absolute error of 1.08% of total solids content.The model was then used to develop a web-based graphical-user-interface(GUI)application,which can be practically used at the rig site by engineers to optimize drilling fluid programs.The proposed model can complement automation workflows that are designed to measure fundamental rheological properties in real time during drilling operations.While a standard retort test can take approximately 2 h at the rig site,such kind of real-time estimations can help the rig personnel to timely optimize drilling fluids,with a potential of saving 2920 man-hours in a given year for a single drilling rig.
基金supported by Petroleum Development Oman and Shell Global Solutions International。
文摘Polymer-based EOR methods in low-permeability reservoirs face injectivity issues and increased fracturing due to near wellbore plugging,as well as high-pressure gradients in these reservoirs.Polymer may cause pore blockage and undergo shear degradation and even oxidative degradation at high temperatures in the presence of very hard brine.Low-tension gas(LTG) flooding has the potential to be applied successfully for low-permeability carbonate reservoirs even in the presence of high formation brine salinity.In LTG flooding,the interfacial tension between oil and water is reduced to ultra-low values(10^-3 dyne/cm) by injecting an optimized surfactant formulation to maximize mobilization of residual oil post-waterflood.Gas(nitrogen,hydrocarbon gases or C02) is co-injected along with the surfactant slug to generate in situ foam which reduces the mobility ratio between the displaced(oil) and displacing phases,thus improving the displacement efficiency of the oil.In this work,the mechanism governing LTG flooding in low-permeability,high-salinity reservoirs was studied at a microscopic level using microemulsion properties and on a macroscopic scale by laboratory-scale coreflooding experiments.The main injection parameters studied were injected slug salinity and the interrelation between surfactant concentration and injected foam quality,and how they influence oil mobilization and displacement efficiency.Qualitative assessment of the results was performed by studying oil recovery,oil fractional flow,oil bank breakthrough and effluent salinity and pressure drop characteristics.
基金financial support from the Key Project of the National Natural Science Foundation of China(No.52034010)the China Scholarship Council(201906450038)
文摘This work mainly studies the effect of fluid phase momentum transfer mechanisms on the acidizing results,including the retardation effect of the porous structure and the interaction between the fluid phase,such as viscous dissipation and inertial effect.The results show that the acid fluid momentum transfer is influenced by the complex porous structure and fluid viscous dissipation.Eventually,the Stokes-Darcy equation is recommended to be adopted to describe the fluid phase momentum transfer in the following numerical simulation studies of the carbonate acidizing process.Based on this model,a parametric research is carried out to investigate the impact of acid on rock physical characteristics in the stimulation process.Increasing the acid concentration appears to minimize the quantity of acid consumed for the breakthrough.The acid surface reaction rate has a considerable impact on the pore volume to breakthrough and the optimum acid injection rate.The influence of permeability on the acidizing results basically shows a negative correlation with the injection rate.The difference between the acidizing curves of different permeability gradually becomes insignificant with the decrease in injection rate.The existence of isolated fracture and vug significantly reduces acid consumption for the breakthrough.
文摘This study extends an integrated field characterization in Eagle Ford by optimizing the numerical reservoir simulation of highly representative complex fractured systems through embedded discrete fracture modeling(EDFM). The bottom-hole flowing pressure was history-matched and the field production was forecasted after screening complex fracture scenarios with more than 100 000 fracture planes based on their propped-type. This work provided a greater understanding of the impact of complex-fractures proppant efficiency on the production. After compaction tables were included for each propped-type fracture group, the estimated pressure depletion showed that the effective drainage area can be smaller than the complex fracture network if modeled and screened by the EDFM method rather than unstructured gridding technique. The essential novel value of this work is the capability to couple EDFM with third-party fracture propagation simulation automatically, considering proppant intensity variation along the complex fractured systems. Thus, this work is pioneer to model complex fracture propagation and well interference accurately from fracture diagnostics and pseudo 3 D fracture propagation outcomes for multiple full wellbores to capture well completion effectiveness after myriads of sharper field simulation cases with EDFM.
文摘To better understand the roles natural fractures play in porous media, an embedded discrete fracture model and streamline modeling method were combined to model natural fractures and compute the flow trajectory and time of fluid in matrix and fractures systems. The effects of fracture conductivity, number of fractures and fracture locations on fluid flow trajectory and time were examined through analyzing the differences in water breakthrough time and sweeping volume of reservoirs with different fracture networks. When other conditions are the same, compared with homogeneous reservoir without fractures, the fractured reservoir has water breakthrough time 30% sooner and swept volume 10% smaller. Although increase of single fracture can lead to faster water breakthrough and smaller swept volume, adding more fractures wouldn't necessarily reach the same effect. The effect of water flooding is also related to the strike and position of fractures. Fractures in different strikes and positions can result in 20% discrepancy in water breakthrough time and 9% gap in swept volume. The shorter the fracture, the less its effect on fluid flow trajectory and time will be. The position of fracture has a strong influence on sweeping efficiency, and the change of one fracture position could bring about 1% variation in swept volume.
基金the projects support by the National Science Foundation(No.DMS-1753031)the Air Force Office of Scientific Research(No.FA9550-22-1-0197)+3 种基金partially supported by the National Science Foundation(No.2019035)the support of the Sandia National Laboratories(SNL)Laboratory-directed Research and Development Programthe U.S.Department of Energy(DOE)Office of Advanced Scientific Computing Research(ASCR)under the Collaboratory on Mathematics and Physics-Informed Learning Machines for Multiscale and Multiphysics Problems(PhILMs)project。
文摘Molecular dynamics(MD)has served as a powerful tool for designing materials with reduced reliance on laboratory testing.However,the use of MD directly to treat the deformation and failure of materials at the mesoscale is still largely beyond reach.In this work,we propose a learning framework to extract a peridynamics model as a mesoscale continuum surrogate from MD simulated material fracture data sets.Firstly,we develop a novel coarse-graining method,to automatically handle the material fracture and its corresponding discontinuities in the MD displacement data sets.Inspired by the weighted essentially non-oscillatory(WENO)scheme,the key idea lies at an adaptive procedure to automatically choose the locally smoothest stencil,then reconstruct the coarse-grained material displacement field as the piecewise smooth solutions containing discontinuities.Then,based on the coarse-grained MD data,a two-phase optimizationbased learning approach is proposed to infer the optimal peridynamics model with damage criterion.In the first phase,we identify the optimal nonlocal kernel function from the data sets without material damage to capture the material stiffness properties.Then,in the second phase,the material damage criterion is learnt as a smoothed step function from the data with fractures.As a result,a peridynamics surrogate is obtained.As a continuum model,our peridynamics surrogate model can be employed in further prediction tasks with different grid resolutions from training,and hence allows for substantial reductions in computational cost compared with MD.We illustrate the efficacy of the proposed approach with several numerical tests for the dynamic crack propagation problem in a single-layer graphene.Our tests show that the proposed data-driven model is robust and generalizable,in the sense that it is capable of modeling the initialization and growth of fractures under discretization and loading settings that are different from the ones used during training.
基金funded by National Natural Science Foundation of China(52004238)China Postdoctoral Science Foundation(2019M663561).
文摘Increasing the production and utilization of shale gas is of great significance for building a clean and low-carbon energy system.Sharp decline of gas production has been widely observed in shale gas reservoirs.How to forecast shale gas production is still challenging due to complex fracture networks,dynamic fracture properties,frac hits,complicated multiphase flow,and multi-scale flow as well as data quality and uncertainty.This work develops an integrated framework for evaluating shale gas well production based on data-driven models.Firstly,a comprehensive dominated-factor system has been established,including geological,drilling,fracturing,and production factors.Data processing and visualization are required to ensure data quality and determine final data set.A shale gas production evaluation model is developed to evaluate shale gas production levels.Finally,the random forest algorithm is used to forecast shale gas production.The prediction accuracy of shale gas production level is higher than 95%based on the shale gas reservoirs in China.Forty-one wells are randomly selected to predict cumulative gas production using the optimal regression model.The proposed shale gas production evaluation frame-work overcomes too many assumptions of analytical or semi-analytical models and avoids huge computation cost and poor generalization for numerical modelling.
基金financial support from the Energize Program between the University of Texas at Austin and Southwest Research InstituteHydraulic Fracturing and Sand Control Industrial Affiliates Program at the University of Texas at Austin for financially supporting this research。
文摘Two-phase pipe flow occurs frequently in oil&gas industry,nuclear power plants,and CCUS.Reliable calculations of gas void fraction(or liquid holdup)play a central role in two-phase pipe flow models.In this paper we apply the fractional flow theory to multiphase flow in pipes and present a unified modeling framework for predicting the fluid phase volume fractions over a broad range of pipe flow conditions.Compared to existing methods and correlations,this new framework provides a simple,approximate,and efficient way to estimate the phase volume fraction in two-phase pipe flow without invoking flow patterns.Notably,existing correlations for estimating phase volume fraction can be transformed and expressed under this modeling framework.Different fractional flow models are applicable to different flow conditions,and they demonstrate good agreement against experimental data within 5%errors when compared with an experimental database comprising of 2754 data groups from 14literature sources,covering various pipe geometries,flow patterns,fluid properties and flow inclinations.The gas void fraction predicted by the framework developed in this work can be used as inputs to reliably model the hydraulic and thermal behaviors of two-phase pipe flows.
基金the National Natural Science Foundation of China(Grant Nos.51221003,51874318)the National Science and Technology Major Project of the Ministry of Science and Technology of China(Grant No.2017ZX05039-003).
文摘Supercritical CO2 fracturing is considered to be a new method for efficient exploitation of unconventional reservoirs,such as shale gas,coal bed methane,and tight sand stone gas.Supercritical CO2 has many special properties including low viscosity,high diffusion coefficient,and lack of surface tension,which brings about great advantages for fracturing.However,these properties also cause several problems,such as difficulty in proppant transportation,high friction loss,and high pump displacement.In this paper,the above problems were analyzed by combining field test with laboratory study and specific solutions to these problems are given.The high frictionloss in the pipeline could be reduced by developing a new drag reducing agent and selecting large-size casing.Besides,for the problem of poor capacity in proppant carrying and sand plug,the methods of adding tackifier into supercritical CO2,increasing pump displacement and selecting ultralow density proppants are proposed.Moreover,for the problem of fast leak-off and high requirement for pump displacement,the displacement can be increased or the pad fluid can be injected into the reservoir.After solving the above three problems,the field test of supercritical CO2 fracturing can be conducted.The research results can promote the industrialization process of supercritical CO2 fracturing.
基金supported by the National Science Foundation for Distinguished Young Scholars(52025065)the China Scholarship Council(201906280349)for its financial support during her study at The University of Texas at Austin.
文摘Gas transport mechanisms can be categorized into viscous flow and mass diffusion,both of which may coexist in a porous media with multiscale pore sizes.To determine the dominant transport mechanism and its contribution to gas transport capacity,the gas viscous flow and mass diffusion processes are analyzed in single nanoscale pores via a theoretical method,and are simulated in 3D nanoporous media via pore-scale lattice Boltzmann methods.The apparent permeability from the viscous flow and apparent diffusivity from the mass diffusion are estimated.A dimensionless parameter,i.e.,the diffusion-flow ratio,is proposed to evaluate the dominant transport mechanism,which is a function of the apparent permeability,apparent diffusivity,bulk dynamic viscosity,and working pressure.The results show that the apparent permeability increases by approximately two orders of magnitude when the average Knudsen number(Kn_(avg))of the nanoporous media or Knudsen number(Kn)of single nanoscale pores increases from 0.1 to 10.Under the same conditions,the increment in the apparent diffusivity is only approximately one order of magnitude.When Kn<0.01,the apparent permeability has a lower bound(i.e.,absolute permeability).When Kn>10,the apparent diffusivity has an upper bound(i.e.,Knudsen diffusivity).The dominant transport mechanism in single nanoscale pores is the viscous flow for 0.01<Kn<100,where the maximum diffusion-flow ratio is less than one.In nanoporous media,the dominant transport relies heavily on Kn_(avg) and the structural parameters.For nanoporous media with the pore throat diameter of 3 nm,Kn_(avg)=0.2 is the critical point,above which the mass diffusion is dominant;otherwise,the viscous flow is dominant.As Kn_(avg) increases to 3.4,the mass diffusion is overwhelming,with the maximum diffusion-flow ratio reaching ~4.
基金supported by the National Natural Science Foundation of China(No.42172159).
文摘The successful commercial development of high-quality middle-shallow and middle-deep shale gas in the Sichuan Basin marks a significant achievement. With the escalating energy demand, attention has shifted toward exploring and exploiting deep-buried, low-quality middle-shallow, and middle-deep shale gas reservoirs in China. This shift necessitates advancements in geological evaluation and engineering design. Here, the key issues related to sweet spot identification in shale gas reservoirs are introduced, and three correlated parameters (gas-in-place, microstructure, and permeability) are concisely overviewed. Numerous efforts and advances have been dedicated to characterizing these parameters in recent years, attempting to reveal the underlying mechanisms and identify the appropriate evaluation methods. However, challenges persist, and potential improvement opportunities are outlined here to provide insights for researchers.
文摘Chemical enhanced oil recovery(CEOR)is well known for its success in recovering the trapped oil in reservoirs after waterflooding operations.In CEOR,synthetic chemicals are utilized to increase the capillary number or modify the mobility ratio of reservoirs;however,they are expensive and are associated with environmental concerns.Hence,the rise in environmental awareness paved the way for environmentally friendly and cheaper alternatives,such as green products,to replace synthetic chemicals.This paper comprehensively reviews recent studies on applying green products in CEOR.It also includes comparisons between the performance of several green products and their synthetic counterparts in CEOR.Moreover,limitations,cost,and environmental footprints are analyzed.Finally,the displacement efficiency of green chemicals and pertinent challenges in the field are highlighted.While the utilization of some natural materials in EOR still has an environmental impact,they constitute a safer option than synthetic chemicals.Furthermore,green materials are more affordable than synthetic chemicals that are commonly utilized,making them a financially viable option for EOR.An up-to-date overview is urgently needed due to the growth of natural chemical utilization in oil and gas applications.Promoting sustainable alternatives is essential to addressing the rise in global environmental concerns.
