Determining the orientation of in-situ stresses is crucial for various geoscience and engineering appli-cations.Conventional methods for estimating these stress orientations often depend on focal mechanism solutions(F...Determining the orientation of in-situ stresses is crucial for various geoscience and engineering appli-cations.Conventional methods for estimating these stress orientations often depend on focal mechanism solutions(FMSs)derived from earthquake data and formation micro-imager(FMI)data from well logs.However,these techniques can be costly,depth-inaccurate,and may lack spatial coverage.To address this issue,we introduce the use of three-dimensional(3D)seismic data(active sources)as a lateral constraint to approximate the 3D stress orientation field.Recognizing that both stress and fracture patterns are closely related to seismic velocity anisotropy,we derive the orientation of azimuthal anisotropy from multi-azimuth 3D seismic data to compensate for the lack of spatial stress orientation information.We apply our proposed workflow to a case study in the Weiyuan area of the Sichuan Basin,China,a region targeted for shale gas production.By integrating diverse datasets,including 3D seismic,earthquakes,and well logs,we develop a comprehensive 3D model of in-situ stress(orientations and magnitudes).Our results demonstrate that the estimated anisotropy orientations from 3D seismic data are consistent with the direction of maximum horizontal principal stress(SHmax)obtained from FMIs.We analyzed 12 earthquakes(magnitude>3)recorded between 2016 and 2020 for their FMSs and compressional axis(P-axis)orientations.The derived SHmax direction from our 3D stress model is 110°ES(East-South),which shows excellent agreement with the FMSs(within 3.96°).This close alignment validates the reliability and precision of our integrated method for predicting 3D SHmax orientations.展开更多
Distributed acoustic sensing(DAS)is increasingly used in seismic exploration owing to its wide frequency range,dense sampling and real-time monitoring.DAS radiation patterns help to understand angle response of DAS re...Distributed acoustic sensing(DAS)is increasingly used in seismic exploration owing to its wide frequency range,dense sampling and real-time monitoring.DAS radiation patterns help to understand angle response of DAS records and improve the quality of inversion and imaging.In this paper,we solve the 3D vertical transverse isotropic(VTI)Christoffel equation and obtain the analytical,frst-order,and zero-order Taylor expansion solutions that represent P-,SV-,and SH-wave phase velocities and polarization vectors.These analytical and approximated solutions are used to build the P/S plane-wave expression identical to the far-feld term of seismic wave,from which the strain rate expressions are derived and DAS radiation patterns are thus extracted for anisotropic P/S waves.We observe that the gauge length and phase angle terms control the radiating intensity of DAS records.Additionally,the Bond transformation is adopted to derive the DAS radiation patterns in title transverse isotropic(TTI)media,which exhibits higher complexity than that of VTI media.Several synthetic examples demonstrate the feasibility and effectiveness of our theory.展开更多
Desulfurization technology is rather difficult and urgently needed for carbon dioxide(CO_(2))utilization in industry.A new Cu(I)-based adsorbent was synthesized and examined for the capacity of removing carbonyl sulfi...Desulfurization technology is rather difficult and urgently needed for carbon dioxide(CO_(2))utilization in industry.A new Cu(I)-based adsorbent was synthesized and examined for the capacity of removing carbonyl sulfide(COS)from a CO_(2)stream in an effort to solve the competitive adsorption between CO_(2)and COS and to seek opportunity to advance adsorption capacity.A wide range of character-ization techniques were used to investigate the physicochemical properties of the synthesized Cu(I)adsorbent featuringπ-complexation and their correlations with the adsorption performance.Meanwhile,the first principal calculation software CP2K was used to develop an understanding of the adsorption mechanism,which can offer useful guidance for the adsorbent regeneration.The synthesized Cu(I)adsorbent,prepared by using copper citrate and citric acid on the ZSM-5(SiO_(2)/Al_(2)O_(3)=25)carrier,outperformed other adsorbents with varying formulations and carriers in adsorption capacities.Through optimization of the preparation and adsorption conditions for various adsorbents,the breakthrough adsorption capacity(Qb)for COS was further enhanced from 2.19 mg/g to 15.36 mg/g.The formed stableπ-complex bonds between COS and Cu(I),as confirmed by density func-tional theory calculations,were verified by the significant improvement in the adsorption capacity after regeneration at 600°C.The above advantages render the novel synthesized Cu(I)adsorbent a promising candidate featuring cost-effectiveness,high efficacy and good regenerability for desulfurization from a CO_(2)stream.展开更多
In order to investigate the problem of long-term strength retrogression in oil well cement systems exposed to high pressure and high temperature(HPHT)curing conditions,various influencing factors,including cement sour...In order to investigate the problem of long-term strength retrogression in oil well cement systems exposed to high pressure and high temperature(HPHT)curing conditions,various influencing factors,including cement sources,particle sizes of silica flour,and additions of silica fume,alumina,colloidal iron oxide and nano-graphene,were investigated.To simulate the environment of cementing geothermal wells and deep wells,cement slurries were directly cured at 50 MPa and 200?C.Mineral compositions(as determined by X-ray diffraction Rietveld refinement),water permeability,compressive strength and Young’s modulus were used to evaluate the qualities of the set cement.Short-term curing(2e30 d)test results indicated that the adoption of 6 m m ultrafine crystalline silica played the most important role in stabilizing the mechanical properties of oil well cement systems,while the addition of silica fume had a detrimental effect on strength stability.Long-term curing(2e180 d)test results indicated that nano-graphene could stabilize the Young’s modulus of oil well cement systems.However,none of the ad-mixtures studied here can completely prevent the strength retrogression phenomenon due to their inability to stop the conversion of amorphous to crystalline phases.展开更多
Source-rock permeability is a key parameter that controls the gas production rate from unconventional reservoirs. Measured source-rock permeability in the laboratory, however, is not an intrinsic property of a rock sa...Source-rock permeability is a key parameter that controls the gas production rate from unconventional reservoirs. Measured source-rock permeability in the laboratory, however, is not an intrinsic property of a rock sample, but depends on pore pressure and temperature as a result of the relative importance of slip flow and diffusion in gas flow in lowpermeability media. To estimate the intrinsic permeability which is required to determine effective permeability values for the reservoir conditions, this study presents a simple approach to correct the laboratory permeability measurements based on the theory of gas flow in a micro/nano-tube that includes effects of viscous flow, slip flow and Knudsen diffusion under different pore pressure and temperature conditions. The approach has been verified using published shale laboratory data.The ＇＇corrected＇＇（or intrinsic） permeability is considerably smaller than the measured permeability. A larger measured permeability generally corresponds to a smaller relative difference between measured and corrected permeability values. A plot based on our approach is presented to describe the relationships between measured and corrected permeability for typical Gas Research Institute permeability test conditions. The developed approach also allows estimating the effective permeability in reservoir conditions from a laboratory permeability measurement.展开更多
This study uses a three-dimensional crack model to theoretically derive the HoekeBrown rock failure criterion based on the linear elastic fracture theory. Specifically, we argue that a failure characteristic factor ne...This study uses a three-dimensional crack model to theoretically derive the HoekeBrown rock failure criterion based on the linear elastic fracture theory. Specifically, we argue that a failure characteristic factor needs to exceed a critical value when macro-failure occurs. This factor is a product of the micro-failure orientation angle （characterizing the density and orientation of damaged micro-cracks） and the changing rate of the angle with respect to the major principal stress （characterizing the microscopic stability of damaged cracks）. We further demonstrate that the factor mathematically leads to the empirical HoekeBrown rock failure criterion. Thus, the proposed factor is able to successfully relate the evolution of microscopic damaged crack characteristics to macro-failure. Based on this theoretical development, we also propose a quantitative relationship between the brittleeductile transition point and confining pressure, which is consistent with experimental observations.展开更多
Reverse Time Migration(RTM)Surface Ofset Gathers(SOGs)are demonstrated to deliver more superior residual dip information than ray-based approaches.It appears more powerful in complex geological settings,such as salt a...Reverse Time Migration(RTM)Surface Ofset Gathers(SOGs)are demonstrated to deliver more superior residual dip information than ray-based approaches.It appears more powerful in complex geological settings,such as salt areas.Still,the computational cost of constructing RTM SOGs is a big challenge in applying it to 3D feld data.To tackle this challenge,we propose a novel method using dips of local events as a guide for RTM gather interpolation.The residual-dip information of the SOGs is created by connecting local events from depth-domain to time-domain via ray tracing.The proposed method is validated by a synthetic experiment and a feld example.It mitigates the computational cost by an order of magnitude while producing comparable results as fully computed RTM SOGs.展开更多
Common-image gathers are extensively used in amplitude versus angle(AVA)and migration velocity analysis(MVA).The current state of methods for anisotropic angle gathers extraction use slant-stack,local Fourier transfor...Common-image gathers are extensively used in amplitude versus angle(AVA)and migration velocity analysis(MVA).The current state of methods for anisotropic angle gathers extraction use slant-stack,local Fourier transform or low-rank approximation,which requires much computation.Based on an anisotropic-Helmholtz P/S wave-mode decomposition method,we propose a novel and efficient approach to produce angle-domain common-image gathers(ADCIGs)in the elastic reverse time migration(ERTM)of VTI media.To start with,we derive an anisotropic-Helmholtz decomposition operator from the Christoffel equation in VTI media,and use this operator to derive the decomposed formulations for anisotropic P/S waves.Second,we employ the first-order Taylor expansion to calculate the normalized term of decomposed formulations and obtain the anisotropic-Helmholtz decomposition method,which generates the separated P/S wavefields with correct amplitudes and phases.Third,we develop a novel way that uses the anisotropic-Helmholtz decomposition operator to define the polari-zation angles for anisotropic P/S waves and substitute these angles to decomposing formulations.The polarization angles are then calculated directly from the separated vector P-and S-wavefields and converted to the phase angles.The ADCIGs are thusly produced by applying the phase angles to VTI ERTM.In addition,we develop a concise approximate expression of residual moveout(RMO)for PP-reflections of flat reflectors in VTI media,which avoids the complex transformations between the group angles and the phase angles.The approximate RMO curves show a good agreement with the exact solution and can be used as a tool to assess the migration velocity errors.As demonstrated by two selected examples,our ADCIGs not only produce the correct kinematic responses with regards to different velocity pertubatation,but also generate the reliable amplitude responses versus different angle.The final stacking images of ADCIGs data exhibit the identical imaging effect as that of VTI ERTM.展开更多
Seismic migration and inversion are closely related techniques to portray subsurface images and identify hydrocarbon reservoirs.Seismic migration aims at obtaining structural images of subsurface geologic discontinuit...Seismic migration and inversion are closely related techniques to portray subsurface images and identify hydrocarbon reservoirs.Seismic migration aims at obtaining structural images of subsurface geologic discontinuities.More specifically,seismic migration estimates the reflectivity function(stacked average reflectivity or pre-stack angle-dependent reflectivity)from seismic reflection data.On the other hand,seismic inversion quantitatively estimates the intrinsic rock properties of subsurface formulations.Such seismic inversion methods are applicable to detect hydrocarbon reservoirs that may exhibit lateral variations in the inverted parameters.Although there exist many differences,pre-stack seismic migration is similar with the first iteration of the general linearized seismic inversion.Usually,seismic migration and inversion techniques assume an acoustic or isotropic elastic medium.Unconventional reservoirs such as shale and tight sand formation have notable anisotropic property.We present a linearized waveform inversion(LWI)scheme for weakly anisotropic elastic media with vertical transversely isotropic(VTI)symmetry.It is based on two-way anisotropic elastic wave equation and simultaneously inverts for the localized perturbations(ΔVp_(0)/Vp_(0)/Vs_(0)/Vs_(0)/,Δ∈,Δδ)from the long-wavelength reference model.Our proposed VTI-elastic LWI is an iterative method that requires a forward and an adjoint operator acting on vectors in each iteration.We derive the forward Born approximation operator by perturbation theory and adjoint operator via adjoint-state method.The inversion has improved the quality of the images and reduces the multi-parameter crosstalk comparing with the adjoint-based images.We have observed that the multi-parameter crosstalk problem is more prominent in the inversion images for Thomsen anisotropy parameters.Especially,the Thomsen parameter is the most difficult to resolve.We also analyze the multi-parameter crosstalk using scattering radiation patterns.The linearized waveform inversion for VTI-elastic media presented in this article provides quantitative information of the rock properties that has the potential to help identify hydrocarbon reservoirs.展开更多
The oil and gas industry strives to improve environmental stewardship and reduce its carbon footprint,but lacks comprehensive global operational data for accurate environmental assessment and decision-making.This chal...The oil and gas industry strives to improve environmental stewardship and reduce its carbon footprint,but lacks comprehensive global operational data for accurate environmental assessment and decision-making.This challenge is compounded by dispersed information sources and the high costs of accessing proprietary databases.This paper presents an innovative framework using Large Language Models(LLMs)–specifically GPT-4 and GPT-4o–to extract critical oil and gas asset information from diverse literature sources.Our framework employs iterative comparisons between GPT-4’s output and a dataset of 129 ground truth documents labeled by domain experts.Through 11 training and testing iterations,we fine-tuned prompts to optimize information extraction.The evaluation process assessed performance using true positive rate,precision,and F1 score metrics.The framework achieved strong results,with a true positive rate of 83.74%and an F1 score of 78.16%on the testing dataset.The system demonstrated remarkable efficiency,processing 32 documents in 61.41 min with GPT-4o,averaging 7.09 s per extraction-a substantial improvement over the manual method.Cost-effectiveness was also achieved,with GPT-4o reducing extraction costs by a factor of 10 compared to GPT-4.This research has significant implications for the oil and gas industry.By creating an organized,transparent,and accessible database,we aim to democratize access to critical information.The framework supports more accurate climate modeling efforts,enhances decision-making processes for operations and investments,and contributes to the sector’s ability to meet environmental commitments.These improvements particularly impact emissions reduction and energy transition strategies,potentially transforming how data is extracted and utilized in this field and beyond.展开更多
Relative permeability is an indispensable property for characterizing the unsaturated flow and induced deformation in soils. The widely used Mualem model is inadequate for deformable soils because of its assumption of...Relative permeability is an indispensable property for characterizing the unsaturated flow and induced deformation in soils. The widely used Mualem model is inadequate for deformable soils because of its assumption of a rigid pore structure and the resultant unique dependence of the tortuosity factor on the volumetric water content. In this study, a unified relationship between the relative permeability and the effective degree of saturation was proposed for deformable soils by incorporating our newly developed water retention curve model into the original Mualem model, in which a new tortuosity factor was defined using the fractal dimension of flow paths and the mean radius of water-filled pores for representing the effect of pore structure variation. The modified deformation-dependent relative permeability model was verified using test data on five types of soils; the verification revealed a much better performance of the proposed model than the original model, which commonly overestimates the relative permeability of deformable soils. Finally, the proposed model was implemented in a coupled numerical model for examining the unsaturated flow and elastoplastic deformation processes in a soil slope induced by rain infiltration. The numerical results showed that the deformation-dependent nature of relative permeability has a remarkable effect on the elastoplastic deformation in the slope and that neglect of the deformation-dependent behavior of relative permeability causes overestimation of the depth of failure.展开更多
The lattice Boltzmann method(LBM)is implemented in the Particle Flow Code(PFC)as a pore-scale CFD module and coupled with the particulate discrete element assemblage in PFC using an immersed boundary scheme.The implem...The lattice Boltzmann method(LBM)is implemented in the Particle Flow Code(PFC)as a pore-scale CFD module and coupled with the particulate discrete element assemblage in PFC using an immersed boundary scheme.The implementation of LBM and LBM-PFC coupling is validated with the analytical solutions in a couple of hydrodynamics and fluid-particle interaction problems,i.e.,the accuracy of LBM as a CFD solver is verified by solving channel flow driven by a pressure gradient for which the closed-form solution is also derived;the accuracy of LBM-PFC coupling is validated by solving flow across a cylinder,Taylor-Couette flow,Karman vortex street,and fluid flow through a cylinder array.To demonstrate potential applications of this coupling code,a perforation cavity subjected to axial fluid flush is then tested,showing that the collapse and reconstruction of sand arch in the perforation cavity can be reproduced in this coupling system.The developed system is ready for exploring more complicated physical issues involved in sand production.展开更多
Chemical flooding has been widely used in the oil industry since the 1980s for enhanced oil recovery(EOR)process.Previous studies have shown that the effectiveness of calcium carbonate scale inhibitors is affected by ...Chemical flooding has been widely used in the oil industry since the 1980s for enhanced oil recovery(EOR)process.Previous studies have shown that the effectiveness of calcium carbonate scale inhibitors is affected by many factors,such as water composition,system pressure,temperature,production rates,pH etc.The breakthrough of the EOR chemicals in the production well could also affect scale formation process and interfere with the scale treatment program as well.However,the studies on the impacts of injected EOR chemicals to scale inhibitor performances are very limited.This paper presents the comprehensive laboratory study on the impacts of the EOR chemicals on CaCO3 scale formation and prevention using static bottle and dynamic tube blocking methods.The EOR chemicals used in this study are a combination of surfactants and polymers.Three different types of inhibitors were evaluated:triphosphonate,penta-phosphonate,and polyacrylate based chemicals.Inhibition(%)from the bottle test and minimum effective dose(MED)based on the tube blocking method were determined for each inhibitor at 160F.Scale precipitates from the bottle tests were also characterized for morphology and polymorphs using environmental scanning electron(ESEM)and X-ray diffraction(XRD)techniques.Results suggest that the performance of scale inhibitors could be substantially affected by the EOR chemicals.In dynamic tube blocking tests,the MED values of inhibitors were increased roughly 10 times with the EOR chemicals.The static bottle tests showed considerable changes under the test conditions.The impact of EOR chemicals were also demonstrated by the remarkable ranges of crystal morphologies,changing from simple aragonite columns to nanorod,distorted spheroid,and flower-like superstructure in the presence of EOR chemicals and inhibitors.展开更多
Estimation of good velocity models under complex near-surface conditions remains a topic of ongoing research.We propose to predict near-surface velocity profiles from surface-waves transformed to phase velocity-freque...Estimation of good velocity models under complex near-surface conditions remains a topic of ongoing research.We propose to predict near-surface velocity profiles from surface-waves transformed to phase velocity-frequency panels in a data-driven manner using deep neural networks.This is a different approach from many recent works that attempt to estimate velocity from directly reflected body waves or guided waves.A secondary objective is to analyze the influence on the prediction accuracy of various commonly employed deep learning practices,such as transfer learning and data augmentations.Through numerical experiments on synthetic data as well as a real geophysical example,we demonstrate that transfer learning as well as data augmentations are helpful when using deep learning for velocity estimation.A third and final objective is to study lack of generalization of deep learning models for out-of-distribution(OOD)data in the context of our problem,and present a novel approach to tackle it.We propose a domain adaptation network for training deep learning models that uses a priori knowledge on the range of velocity values in order to constrain mapping of the output.The final comparison on field data,which was not part of the training data,show the deep neural network predictions compare favorably with a conventional velocity model estimation obtained with a dispersion curve inversion workflow.展开更多
Machine learning provides a powerful alternative data-driven approach to accomplish many petrophysical tasks from subsurface data.It can assimilate information from large and rich data bases and infer relations,rules,...Machine learning provides a powerful alternative data-driven approach to accomplish many petrophysical tasks from subsurface data.It can assimilate information from large and rich data bases and infer relations,rules,and knowledge hidden in the data.When the physics behind data becomes extremely complex,inexplicit,or even unclear/unknown,machine learning approaches have the advantage of being more flexible with wider applicability over conventional physics-based interpretation models.Moreover,machine learning can be utilized to assist many labor-intensive human interpretation tasks such as bad data identification,facies classification,and geo-features segmentation out of imagery data.However,the validity of the outcome from machine learning largely depends on the quantity,quality,representativeness,and relevance of the feeding data including accurate labels.To achieve the best performance,it requires significant effort in data preparation,feature engineering,algorithm selection,architecture design hyperparameter tuning,and regularization.In addition,it needs to overcome technical issues such as imbalanced population,overfitting,and underfitting.In this paper,advantages,limitations,and conditions of using machine learning to solve petrophysics challenges are discussed.The capability of machine learning algorithms in accomplishing different challenging tasks can only be achieved by overcoming its own limitations.Machine learning,if properly utilized,can become a powerful disruptive tool for assisting a series of critical petrophysics tasks.展开更多
基金supported by the National Key R&D Program of China(Grant No.2020YFA0710604)NSFC(Grant No.42374064).
文摘Determining the orientation of in-situ stresses is crucial for various geoscience and engineering appli-cations.Conventional methods for estimating these stress orientations often depend on focal mechanism solutions(FMSs)derived from earthquake data and formation micro-imager(FMI)data from well logs.However,these techniques can be costly,depth-inaccurate,and may lack spatial coverage.To address this issue,we introduce the use of three-dimensional(3D)seismic data(active sources)as a lateral constraint to approximate the 3D stress orientation field.Recognizing that both stress and fracture patterns are closely related to seismic velocity anisotropy,we derive the orientation of azimuthal anisotropy from multi-azimuth 3D seismic data to compensate for the lack of spatial stress orientation information.We apply our proposed workflow to a case study in the Weiyuan area of the Sichuan Basin,China,a region targeted for shale gas production.By integrating diverse datasets,including 3D seismic,earthquakes,and well logs,we develop a comprehensive 3D model of in-situ stress(orientations and magnitudes).Our results demonstrate that the estimated anisotropy orientations from 3D seismic data are consistent with the direction of maximum horizontal principal stress(SHmax)obtained from FMIs.We analyzed 12 earthquakes(magnitude>3)recorded between 2016 and 2020 for their FMSs and compressional axis(P-axis)orientations.The derived SHmax direction from our 3D stress model is 110°ES(East-South),which shows excellent agreement with the FMSs(within 3.96°).This close alignment validates the reliability and precision of our integrated method for predicting 3D SHmax orientations.
基金supported by the National Key R&D Program of China under grant No.2021YFA0716800。
文摘Distributed acoustic sensing(DAS)is increasingly used in seismic exploration owing to its wide frequency range,dense sampling and real-time monitoring.DAS radiation patterns help to understand angle response of DAS records and improve the quality of inversion and imaging.In this paper,we solve the 3D vertical transverse isotropic(VTI)Christoffel equation and obtain the analytical,frst-order,and zero-order Taylor expansion solutions that represent P-,SV-,and SH-wave phase velocities and polarization vectors.These analytical and approximated solutions are used to build the P/S plane-wave expression identical to the far-feld term of seismic wave,from which the strain rate expressions are derived and DAS radiation patterns are thus extracted for anisotropic P/S waves.We observe that the gauge length and phase angle terms control the radiating intensity of DAS records.Additionally,the Bond transformation is adopted to derive the DAS radiation patterns in title transverse isotropic(TTI)media,which exhibits higher complexity than that of VTI media.Several synthetic examples demonstrate the feasibility and effectiveness of our theory.
基金supported by the National Key Research and Development Program of China(2022YFA1504402)National Energy R&D Center of Petroleum Refining Technology(RIPP,SINOPEC)+2 种基金the National Natural Science Foundation of China(22472016 and U23B20169)Key R&D Program of Ningbo(No.2023Z144)the Fundamental Research Funds for the Central Universities(DUT22LAB601).
文摘Desulfurization technology is rather difficult and urgently needed for carbon dioxide(CO_(2))utilization in industry.A new Cu(I)-based adsorbent was synthesized and examined for the capacity of removing carbonyl sulfide(COS)from a CO_(2)stream in an effort to solve the competitive adsorption between CO_(2)and COS and to seek opportunity to advance adsorption capacity.A wide range of character-ization techniques were used to investigate the physicochemical properties of the synthesized Cu(I)adsorbent featuringπ-complexation and their correlations with the adsorption performance.Meanwhile,the first principal calculation software CP2K was used to develop an understanding of the adsorption mechanism,which can offer useful guidance for the adsorbent regeneration.The synthesized Cu(I)adsorbent,prepared by using copper citrate and citric acid on the ZSM-5(SiO_(2)/Al_(2)O_(3)=25)carrier,outperformed other adsorbents with varying formulations and carriers in adsorption capacities.Through optimization of the preparation and adsorption conditions for various adsorbents,the breakthrough adsorption capacity(Qb)for COS was further enhanced from 2.19 mg/g to 15.36 mg/g.The formed stableπ-complex bonds between COS and Cu(I),as confirmed by density func-tional theory calculations,were verified by the significant improvement in the adsorption capacity after regeneration at 600°C.The above advantages render the novel synthesized Cu(I)adsorbent a promising candidate featuring cost-effectiveness,high efficacy and good regenerability for desulfurization from a CO_(2)stream.
基金Financial support comes from China National Natural Science Foundation(Grant No.51974352)as well as from China University of Petroleum(East China)(Grant Nos.2018000025 and 2019000011)。
文摘In order to investigate the problem of long-term strength retrogression in oil well cement systems exposed to high pressure and high temperature(HPHT)curing conditions,various influencing factors,including cement sources,particle sizes of silica flour,and additions of silica fume,alumina,colloidal iron oxide and nano-graphene,were investigated.To simulate the environment of cementing geothermal wells and deep wells,cement slurries were directly cured at 50 MPa and 200?C.Mineral compositions(as determined by X-ray diffraction Rietveld refinement),water permeability,compressive strength and Young’s modulus were used to evaluate the qualities of the set cement.Short-term curing(2e30 d)test results indicated that the adoption of 6 m m ultrafine crystalline silica played the most important role in stabilizing the mechanical properties of oil well cement systems,while the addition of silica fume had a detrimental effect on strength stability.Long-term curing(2e180 d)test results indicated that nano-graphene could stabilize the Young’s modulus of oil well cement systems.However,none of the ad-mixtures studied here can completely prevent the strength retrogression phenomenon due to their inability to stop the conversion of amorphous to crystalline phases.
文摘Source-rock permeability is a key parameter that controls the gas production rate from unconventional reservoirs. Measured source-rock permeability in the laboratory, however, is not an intrinsic property of a rock sample, but depends on pore pressure and temperature as a result of the relative importance of slip flow and diffusion in gas flow in lowpermeability media. To estimate the intrinsic permeability which is required to determine effective permeability values for the reservoir conditions, this study presents a simple approach to correct the laboratory permeability measurements based on the theory of gas flow in a micro/nano-tube that includes effects of viscous flow, slip flow and Knudsen diffusion under different pore pressure and temperature conditions. The approach has been verified using published shale laboratory data.The ＇＇corrected＇＇（or intrinsic） permeability is considerably smaller than the measured permeability. A larger measured permeability generally corresponds to a smaller relative difference between measured and corrected permeability values. A plot based on our approach is presented to describe the relationships between measured and corrected permeability for typical Gas Research Institute permeability test conditions. The developed approach also allows estimating the effective permeability in reservoir conditions from a laboratory permeability measurement.
基金supported by the National Natural Science Foundation of China (No. 51374215)Fok Ying Tung Education Foundation (No. 142018)+1 种基金Beijing Major Scientific and Technological Achievements into Ground Cultivation Projectthe 111 Project (No. B14006)
文摘This study uses a three-dimensional crack model to theoretically derive the HoekeBrown rock failure criterion based on the linear elastic fracture theory. Specifically, we argue that a failure characteristic factor needs to exceed a critical value when macro-failure occurs. This factor is a product of the micro-failure orientation angle （characterizing the density and orientation of damaged micro-cracks） and the changing rate of the angle with respect to the major principal stress （characterizing the microscopic stability of damaged cracks）. We further demonstrate that the factor mathematically leads to the empirical HoekeBrown rock failure criterion. Thus, the proposed factor is able to successfully relate the evolution of microscopic damaged crack characteristics to macro-failure. Based on this theoretical development, we also propose a quantitative relationship between the brittleeductile transition point and confining pressure, which is consistent with experimental observations.
基金This study is jointly supported by the National Key R&D Program of China(2017YFC1500303 and 2020YFA0710604)the Science Foundation of China University of Petroleum,Beijing(2462019YJRC007 and 2462020YXZZ047)the Strategic Cooperation Technology Projects of CNPC and CUPB(ZLZX2020-05).
文摘Reverse Time Migration(RTM)Surface Ofset Gathers(SOGs)are demonstrated to deliver more superior residual dip information than ray-based approaches.It appears more powerful in complex geological settings,such as salt areas.Still,the computational cost of constructing RTM SOGs is a big challenge in applying it to 3D feld data.To tackle this challenge,we propose a novel method using dips of local events as a guide for RTM gather interpolation.The residual-dip information of the SOGs is created by connecting local events from depth-domain to time-domain via ray tracing.The proposed method is validated by a synthetic experiment and a feld example.It mitigates the computational cost by an order of magnitude while producing comparable results as fully computed RTM SOGs.
基金supported by the National Key R&D Program of China(2020YFA0710604 and 2017YFC1500303)the Science Foundation of the China University of Petroleum,Beijing(2462019YJRC007 and 2462020YXZZ047)the Strategic Cooperation Technology Projects of CNPC and CUPB(ZLZX2020-05).
文摘Common-image gathers are extensively used in amplitude versus angle(AVA)and migration velocity analysis(MVA).The current state of methods for anisotropic angle gathers extraction use slant-stack,local Fourier transform or low-rank approximation,which requires much computation.Based on an anisotropic-Helmholtz P/S wave-mode decomposition method,we propose a novel and efficient approach to produce angle-domain common-image gathers(ADCIGs)in the elastic reverse time migration(ERTM)of VTI media.To start with,we derive an anisotropic-Helmholtz decomposition operator from the Christoffel equation in VTI media,and use this operator to derive the decomposed formulations for anisotropic P/S waves.Second,we employ the first-order Taylor expansion to calculate the normalized term of decomposed formulations and obtain the anisotropic-Helmholtz decomposition method,which generates the separated P/S wavefields with correct amplitudes and phases.Third,we develop a novel way that uses the anisotropic-Helmholtz decomposition operator to define the polari-zation angles for anisotropic P/S waves and substitute these angles to decomposing formulations.The polarization angles are then calculated directly from the separated vector P-and S-wavefields and converted to the phase angles.The ADCIGs are thusly produced by applying the phase angles to VTI ERTM.In addition,we develop a concise approximate expression of residual moveout(RMO)for PP-reflections of flat reflectors in VTI media,which avoids the complex transformations between the group angles and the phase angles.The approximate RMO curves show a good agreement with the exact solution and can be used as a tool to assess the migration velocity errors.As demonstrated by two selected examples,our ADCIGs not only produce the correct kinematic responses with regards to different velocity pertubatation,but also generate the reliable amplitude responses versus different angle.The final stacking images of ADCIGs data exhibit the identical imaging effect as that of VTI ERTM.
文摘Seismic migration and inversion are closely related techniques to portray subsurface images and identify hydrocarbon reservoirs.Seismic migration aims at obtaining structural images of subsurface geologic discontinuities.More specifically,seismic migration estimates the reflectivity function(stacked average reflectivity or pre-stack angle-dependent reflectivity)from seismic reflection data.On the other hand,seismic inversion quantitatively estimates the intrinsic rock properties of subsurface formulations.Such seismic inversion methods are applicable to detect hydrocarbon reservoirs that may exhibit lateral variations in the inverted parameters.Although there exist many differences,pre-stack seismic migration is similar with the first iteration of the general linearized seismic inversion.Usually,seismic migration and inversion techniques assume an acoustic or isotropic elastic medium.Unconventional reservoirs such as shale and tight sand formation have notable anisotropic property.We present a linearized waveform inversion(LWI)scheme for weakly anisotropic elastic media with vertical transversely isotropic(VTI)symmetry.It is based on two-way anisotropic elastic wave equation and simultaneously inverts for the localized perturbations(ΔVp_(0)/Vp_(0)/Vs_(0)/Vs_(0)/,Δ∈,Δδ)from the long-wavelength reference model.Our proposed VTI-elastic LWI is an iterative method that requires a forward and an adjoint operator acting on vectors in each iteration.We derive the forward Born approximation operator by perturbation theory and adjoint operator via adjoint-state method.The inversion has improved the quality of the images and reduces the multi-parameter crosstalk comparing with the adjoint-based images.We have observed that the multi-parameter crosstalk problem is more prominent in the inversion images for Thomsen anisotropy parameters.Especially,the Thomsen parameter is the most difficult to resolve.We also analyze the multi-parameter crosstalk using scattering radiation patterns.The linearized waveform inversion for VTI-elastic media presented in this article provides quantitative information of the rock properties that has the potential to help identify hydrocarbon reservoirs.
基金the Aramco Services Company and Natural Gas Initiatives at Stanford University。
文摘The oil and gas industry strives to improve environmental stewardship and reduce its carbon footprint,but lacks comprehensive global operational data for accurate environmental assessment and decision-making.This challenge is compounded by dispersed information sources and the high costs of accessing proprietary databases.This paper presents an innovative framework using Large Language Models(LLMs)–specifically GPT-4 and GPT-4o–to extract critical oil and gas asset information from diverse literature sources.Our framework employs iterative comparisons between GPT-4’s output and a dataset of 129 ground truth documents labeled by domain experts.Through 11 training and testing iterations,we fine-tuned prompts to optimize information extraction.The evaluation process assessed performance using true positive rate,precision,and F1 score metrics.The framework achieved strong results,with a true positive rate of 83.74%and an F1 score of 78.16%on the testing dataset.The system demonstrated remarkable efficiency,processing 32 documents in 61.41 min with GPT-4o,averaging 7.09 s per extraction-a substantial improvement over the manual method.Cost-effectiveness was also achieved,with GPT-4o reducing extraction costs by a factor of 10 compared to GPT-4.This research has significant implications for the oil and gas industry.By creating an organized,transparent,and accessible database,we aim to democratize access to critical information.The framework supports more accurate climate modeling efforts,enhances decision-making processes for operations and investments,and contributes to the sector’s ability to meet environmental commitments.These improvements particularly impact emissions reduction and energy transition strategies,potentially transforming how data is extracted and utilized in this field and beyond.
基金supported by the CRSRI Open Research Program(Grant No.CKWV2015209/KY)the National Natural Science Foundation of China(Grant Nos.51409198,51179136&51222903)
文摘Relative permeability is an indispensable property for characterizing the unsaturated flow and induced deformation in soils. The widely used Mualem model is inadequate for deformable soils because of its assumption of a rigid pore structure and the resultant unique dependence of the tortuosity factor on the volumetric water content. In this study, a unified relationship between the relative permeability and the effective degree of saturation was proposed for deformable soils by incorporating our newly developed water retention curve model into the original Mualem model, in which a new tortuosity factor was defined using the fractal dimension of flow paths and the mean radius of water-filled pores for representing the effect of pore structure variation. The modified deformation-dependent relative permeability model was verified using test data on five types of soils; the verification revealed a much better performance of the proposed model than the original model, which commonly overestimates the relative permeability of deformable soils. Finally, the proposed model was implemented in a coupled numerical model for examining the unsaturated flow and elastoplastic deformation processes in a soil slope induced by rain infiltration. The numerical results showed that the deformation-dependent nature of relative permeability has a remarkable effect on the elastoplastic deformation in the slope and that neglect of the deformation-dependent behavior of relative permeability causes overestimation of the depth of failure.
基金The lattice Boltzmann method was implemented in Particle Flow Code when YH was working for Itasca Consulting Group,Inc.
文摘The lattice Boltzmann method(LBM)is implemented in the Particle Flow Code(PFC)as a pore-scale CFD module and coupled with the particulate discrete element assemblage in PFC using an immersed boundary scheme.The implementation of LBM and LBM-PFC coupling is validated with the analytical solutions in a couple of hydrodynamics and fluid-particle interaction problems,i.e.,the accuracy of LBM as a CFD solver is verified by solving channel flow driven by a pressure gradient for which the closed-form solution is also derived;the accuracy of LBM-PFC coupling is validated by solving flow across a cylinder,Taylor-Couette flow,Karman vortex street,and fluid flow through a cylinder array.To demonstrate potential applications of this coupling code,a perforation cavity subjected to axial fluid flush is then tested,showing that the collapse and reconstruction of sand arch in the perforation cavity can be reproduced in this coupling system.The developed system is ready for exploring more complicated physical issues involved in sand production.
文摘Chemical flooding has been widely used in the oil industry since the 1980s for enhanced oil recovery(EOR)process.Previous studies have shown that the effectiveness of calcium carbonate scale inhibitors is affected by many factors,such as water composition,system pressure,temperature,production rates,pH etc.The breakthrough of the EOR chemicals in the production well could also affect scale formation process and interfere with the scale treatment program as well.However,the studies on the impacts of injected EOR chemicals to scale inhibitor performances are very limited.This paper presents the comprehensive laboratory study on the impacts of the EOR chemicals on CaCO3 scale formation and prevention using static bottle and dynamic tube blocking methods.The EOR chemicals used in this study are a combination of surfactants and polymers.Three different types of inhibitors were evaluated:triphosphonate,penta-phosphonate,and polyacrylate based chemicals.Inhibition(%)from the bottle test and minimum effective dose(MED)based on the tube blocking method were determined for each inhibitor at 160F.Scale precipitates from the bottle tests were also characterized for morphology and polymorphs using environmental scanning electron(ESEM)and X-ray diffraction(XRD)techniques.Results suggest that the performance of scale inhibitors could be substantially affected by the EOR chemicals.In dynamic tube blocking tests,the MED values of inhibitors were increased roughly 10 times with the EOR chemicals.The static bottle tests showed considerable changes under the test conditions.The impact of EOR chemicals were also demonstrated by the remarkable ranges of crystal morphologies,changing from simple aragonite columns to nanorod,distorted spheroid,and flower-like superstructure in the presence of EOR chemicals and inhibitors.
文摘Estimation of good velocity models under complex near-surface conditions remains a topic of ongoing research.We propose to predict near-surface velocity profiles from surface-waves transformed to phase velocity-frequency panels in a data-driven manner using deep neural networks.This is a different approach from many recent works that attempt to estimate velocity from directly reflected body waves or guided waves.A secondary objective is to analyze the influence on the prediction accuracy of various commonly employed deep learning practices,such as transfer learning and data augmentations.Through numerical experiments on synthetic data as well as a real geophysical example,we demonstrate that transfer learning as well as data augmentations are helpful when using deep learning for velocity estimation.A third and final objective is to study lack of generalization of deep learning models for out-of-distribution(OOD)data in the context of our problem,and present a novel approach to tackle it.We propose a domain adaptation network for training deep learning models that uses a priori knowledge on the range of velocity values in order to constrain mapping of the output.The final comparison on field data,which was not part of the training data,show the deep neural network predictions compare favorably with a conventional velocity model estimation obtained with a dispersion curve inversion workflow.
文摘Machine learning provides a powerful alternative data-driven approach to accomplish many petrophysical tasks from subsurface data.It can assimilate information from large and rich data bases and infer relations,rules,and knowledge hidden in the data.When the physics behind data becomes extremely complex,inexplicit,or even unclear/unknown,machine learning approaches have the advantage of being more flexible with wider applicability over conventional physics-based interpretation models.Moreover,machine learning can be utilized to assist many labor-intensive human interpretation tasks such as bad data identification,facies classification,and geo-features segmentation out of imagery data.However,the validity of the outcome from machine learning largely depends on the quantity,quality,representativeness,and relevance of the feeding data including accurate labels.To achieve the best performance,it requires significant effort in data preparation,feature engineering,algorithm selection,architecture design hyperparameter tuning,and regularization.In addition,it needs to overcome technical issues such as imbalanced population,overfitting,and underfitting.In this paper,advantages,limitations,and conditions of using machine learning to solve petrophysics challenges are discussed.The capability of machine learning algorithms in accomplishing different challenging tasks can only be achieved by overcoming its own limitations.Machine learning,if properly utilized,can become a powerful disruptive tool for assisting a series of critical petrophysics tasks.
