查看更多>>摘要：The pore structure of ultra-low permeability sandstone(0.1 mD<K<1 mD)is complex and has high heterogeneity,which leads to great challenges in reservoir characterization and effective evaluation.To study the effect of the heterogeneity of ultra-low permeability sandstone on permeability,a digital core model was established using X-ray computer tomography(CT)technology.Then a three-dimensional pore network model(PNM)in core samples was created using the"maximum ball method"algorithm.Finally,the geometric topology features of ultra-low permeability reservoirs were quantitatively characterized.According to the physical properties and test results of samples,the porosity distribution of targeted area ranged between 5.92% and 10.08%,and the permeability distribution range was 0.145 mD-0.75 mD,which was typical for an ultra-low permeability reservoir.The distribution of pore throat radii ranged from 0.27 μm to 1.29 μm,the shape factor was 0.04-0.06,the disconnected pores of the four samples made up between 16.89% and 58.71% of all pores,and the fractal dimension fluctuated between 1.05 and 1.5.Plane porosity also showed certain fractal characteristics.Correlation analysis showed that the disconnected isolated pores and the micron-scale pore throat radii of the reservoir sandstone were the main factors resulting in ultra-low permeability.The above-mentioned quantitative characterization parameters can be subsequently used to conduct microscopic seepage simulation studies of such reservoirs.
查看更多>>摘要：Oil viscosity is used in any fluid transport calculation in both subsurface and surface conditions.It is possible to determine oil viscosity from laboratory measurements or empirical correlations.However,laboratory measurements are not always available;and empirical correlations suffer from low accuracy.This work implements data mining algorithms to suggest a new correlation for oil viscosity calculation in a wide pressure range from subsurface to surface conditions.First,a scatter plot matrix is applied to analyze 1950 PVT experimental data points from Iranian oil reservoirs.Therefore,the most correlated parameters for predicting oil viscosity are determined.Next,75% of data points are randomly selected to train the models.The remaining data,i.e.,25% of data points,are utilized to investigate the accuracy of the developed correlation.Then,a symbolic regression analysis is performed in all pressure ranges,i.e.,dead oil viscosity,bubble point oil viscosity,below and above the bubble point pressure.Finally,a new oil viscosity correlation is proposed.The statistical and graphical evaluations reveal that the new correlation outperformed the previously proposed correlations by lowering average absolute errors.It can be concluded that the presented correlation improves the prediction accuracy in all pressure ranges.Consequently,it is inferred from the results that machine learning could provide a highly accurate prediction for oil viscosity in all pressure regions.Overall,the proposed correlation could be used to calculate oil viscosity in all pressure ranges with reasonable accuracy.
查看更多>>摘要：Determining the properties of hydrocarbons,especially density,is one of the most important measures in the oil and gas industry.In this study,robust artificial intelligence techniques have been investigated to predict the density of pure and binary mixtures of normal alkanes(between C1 and C_(44)).Since there are various conditions in oil and gas reservoirs,it has been tried to study the properties of different hydrocarbons in a wide range of temperature(up to 522 K)and pressure(up to 275 MPa).An extensive databank,including 2143 and 985 data points for pure and binary mixtures of normal alkanes,respectively,was extracted from the literature.The crow search algorithm(CSA),firefly algorithm(FFA),grey wolf optimization(GWO),and wind-driven optimization(WDO)algorithms were utilized to improve the learning process of least square support vector machine(LSSVM)and radial basis function neural network(RBFNN)models,which were developed to predict the density of hydrocarbons.Also,gene expression programming(GEP)correlations were presented using complex mathematical calculations to estimate the density of hydrocarbons.The results obtained from the models were also compared with seven equations of state(EOSs).The obtained results showed that the predictions of the proposed techniques are in a great match with the experimental data.By performing a comparison on the models'outcomes,LSSVM-GWO and RBFNN-CSA were found to be the most accurate models for pure and binary mixtures of normal alkanes with overall average absolute percent relative error(AAPRE)values of 0.0622% and 0.0098%,respectively.It is noteworthy that the GEP correlations with the AAPRE values of 0.1955% and 0.3525% for pure and binary mixtures of normal alkanes,respectively,have a high accuracy compared to the equations of state and are suitable practical correlations for estimating the density of hydrocarbons.
查看更多>>摘要：Shale is a highly vertical heterogeneous formation due to the complex sedimentary environment.Unfortunately,available models to predict the well production rely on the over-simplified assumption that ignores the effect of vertical heterogeneity and cross-flow on well production.This work aims to propose a simple-yet-rigorous oil flow model considering the vertical heterogeneity in shale formation.The stimulated reservoir volume(SRV)near well is characterized by a Vertical Heterogeneous Cross-flow Model(VHCM).The drainage volume is divided into several layers,and the diffusivity equation of each segment is derived separately.Thus,three dimensions of flow are considered simultaneously.The VHCM is analytically solved in Laplace domain and inversed to real domain numerically.Then the proposed model is verified against the fine-grid numerical results.Based on the VHCM,the flow characteristics in shale formation considering the effects of vertical heterogeneity and cross-flow are systemically investigated.The result shows that the adoption of a vertical homogeneous model will lead to the overestimation of reservoir properties and using the Vertical Heterogeneous No-cross-flow Model(VHNM)will lead to the underestimation of reservoir properties in shale formation.In addition,thin interbedded structures and stratified sandstone in shale are beneficial for well production.Compared with the traditional vertical homogeneous model,the VHCM captures the variation of reservoir and fracture properties in shale reservoirs,and the results better match the field data.
查看更多>>摘要：The investigation of tight oil reservoirs has become a significant area of interest in unconventional oil development.CO2 flooding is considered an effective oil recovery method for tight oil reservoirs as it can significantly increase oil recovery when it reaches supercritical condition and becomes miscible with oil.Although extensive research has been conducted on CO2 flooding,the oil recovery from pore of different sizes in tight sandstone reservoirs at different pressures has not been thoroughly investigated.In this study,we analyzed the petrology features and the pore structure of a reservoir using casting section and scanning electron microscope(SEM)images.Subsequently,diree cores with different permeability from the reservoir were subjected to CO2 flooding experiments at different pressures.A nuclear magnetic resonance(NMR)spectrometer was used to quantify the oil recovery.Amott-Harvey index was measured to study the effect of CO2 flooding on core wettability.Results indicate that the total oil recovery and the oil recovery of smaller pores increase as the pressure increasing.The oil recovery of the larger pores does not increase continuously.The oil recovery of the smaller pores is more dependent on pressure than that of the larger pores,and the total oil recovery is related to the oil recovery of smaller pores.Meanwhile,the supercritical and miscible CO2 has a positive effect on oil recovery.After CO2 becoming supercritical and miscible,the cores still have potential to produce more oil with the pressure increasing.As the pore structure is playing a significant role in oil recovery,the core with a higher proportion of the volume of larger pores is relatively easy to produce more oil at low pressure.Amott-Harvey index shows CO2 flooding can significantly reduce the hydrophilicity of cores.This study reveals the mechanism of pressure effect on oil recovery during CO2 flooding in tight sandstone reservoirs.The results can be used to improve the efficiency of reservoir development.
查看更多>>摘要：Digital cores are of great significance for reservoir structure simulation,oil and gas exploration and development.Most existing digital core reconstruction methods only generate binary cores with complicated implementation processes,among other problems.To address these problems,this study proposed a combination of core pore parameters and conditional generative adversarial network(CGAN)to realize the 2D reconstruction of core grayscale images from only pore parameters(namely,text-to-image synthesis).The current text-to-image synthesis approaches still have many difficulties in generating fine images,but the technologies of image-to-image generation have improved drastically in recent years.Therefore,the proposed method involves two stages to avoid the difficulty of directly generating core grayscale images from pore parameters.In stage I,we preprocessed core sample images to obtain binary-grayscale image pairs,and then used the CGAN to learn the mapping from core binary images to real sample images.At the same time,the pores in the binary images were segmented and extracted to construct the pore component library.In stage II,on the basis of the given pore parameters,the corresponding pores were randomly extracted from the pore component library to generate binary images,and then the generated binary images were used as input for the trained CGAN model to produce core grayscale images.The experimental results showed that the core grayscale images reconstructed by the proposed method meet the pore conditions and reflect the basic characteristics of real cores.
查看更多>>摘要：The migration and interaction of water and gas in coal plays an important role in achieving high-performance recovery of coalbed methane(CBM).While a significant amount of fracturing fluid is injected into the reservoir to enhance the production of CBM,the effect of the imbibed liquid on the gas transport process remains poorly understood.To better understand the impact on well productivity after fracturing fluid invasion,we carried out experimental investigations on dynamic imbibition of water,and resulting matrix permeability changes,using core plug samples of coal from the Qinshui,Ordos and Junggar basins in China.The imbibition process is divided into a quick stage followed by a slow stage:the former occurs in seepage pores with a higher imbibition rate and larger imbibition time-exponent than the latter,which occurs in adsorption pores.Capillary and frictional resistance forces control the spontaneous imbibition of coals.Water movement during gas flooding has a similar imbibition rate and imbibition resistance to the slow stage of spontaneous imbibition,suggesting that the water migration process moves from larger seepage pores to smaller adsorption pores,and this is the main reason for a change in gas permeability.Gas permeability can seemingly be reduced because of two combined mechanisms:1)occupation of the gas flow path by water in seepage pores;and 2)matrix swelling induced by water adsorption in adsorption pores.In contrast,the changing gas slippage factor can lead to an improvement in gas permeability.Coupling these three factors,we propose a modified permeability model that can be used to evaluate the influence of water on gas permeability and then to estimate the change in gas permeability during hydro-fracturing of a CBM reservoir.
查看更多>>摘要：A novel sphingan WL was mixed with an anionic polyacrylamide(APAM)and a nonionic surfactant(Brij 35).The viscosity and rheological properties of the two mixtures were systematically investigated.An obvious increase in viscosity was observed for the mixed solution containing WL and APAM in a ratio of 9:1.The two inflection points on the surface tension curve indicated intermolecular interactions between WL and Brij 35.The combination of WL and the APAM or WL and Brij 35 resulted in the formation of networks in the solution through electrostatic interactions and hydrogen bonding interactions.Moreover,the rheological properties of WL-APAM were observed to be maintained under high temperature and high salinity conditions,and the WL-Brij 35 could tolerate high temperature,too.The mixtures of WL-APAM and WL-Brij 35 with only 0.035 wt% WL could enhance the oil displacement efficiencies by 21.31% and 22.17%,respectively.Therefore,the synergistic effects between exopolysaccharides and polymers/surfactants were demonstrated to improve oil recovery.
查看更多>>摘要：Spontaneous imbibition(SI)is the principal production mechanism in naturally fractured reservoirs produced by waterflooding and is essential for fluid flow characterization to predict their future performance.As an alter-native to the expensive,time-consuming laboratory measurements,2D images render a different prospect to obtain SI capillary pressure curves,especially for tight reservoirs.This paper introduces a unique approach to infer SI capillary pressure curves from 2D images through integrating image analysis and fractal theory.Using pore-related information obtained from image analysis,we properly represent the pore structure as bundles of tortuous square and triangular tubes with sinusoidally varying radii to imitate cross-sectional variation between pore bodies and throats.Moreover,we simulate the piston-like and snap-off displacement mechanisms to derive an innovative fractal SI capillary pressure model.The developed model considers the contact angle hysteresis caused by surface roughness and heterogeneity of reservoir rocks.The Mayer-Stowe-Princen(MSP)approach is implemented to compute the entry capillary pressure of piston-like displacement.The laboratory-measured porosity and permeability are utilized to determine the model's 3D-related parameters that cannot be inferred from 2D images.The model reliability is verified with the good accuracy of the predicted capillary pressure curves versus laboratory-measured data of five samples from the Liushagang and Huangliu in the South China Sea.Finally,the fundamental parameters influencing the developed SI capillary pressure model are investigated with sensitivity analysis.
查看更多>>摘要：The ultra-deep dolomite reservoir of the Permian Qixia Formation in northwest Sichuan is important for hydrocarbon reservoirs,but the mechanism of dolomite genesis is complex and has long been controversial,thus requiring further elucidation.By studying the dolomite with different types in the Permian Qixia Formation,northwest Sichuan Basin,this paper,based on outcrop sections observation and core description,seeks to find out the dolomitizing fluids'source and the dolomite's genetic mechanism by analyzing the dolomite's rock-mineral and geochemical characteristics.Various technologies are applied,including rock thin section observation,cathode luminescence,carbon and oxygen isotope analyses,laser ablation-inductively coupled plasma-mass spectrometry(LA-ICP-MS),and inclusion homogenization temperature and salinity.Results show that the dolomite is mainly classified into silty-fine dolomite(Mdl),fine-medium dolomite(Md2),medium-coarse dolomite(Md3),and saddle dolomite(SD)filled in the pores.Mdl is formed in the early shallow-burial stage;the dolomitizing fluids are mainly derived from the early seawater sealed in carbonate sediments;and the penesaline seawater is formed by the seepage reflux under a moderate evaporitic environment.Md2 and Md3 are formed in the middle and late shallow-burial stages.Of these two types,Md2 is formed earlier,and the dolomitizing fluids are primarily derived from the seawater sealed in the early stage and partially derived from the residual evaporated seawater and hydrothermal fluids.In contrast,Md3 is formed later,and the dolomitizing fluids are the mixture of the seawater sealed in the early stage and the hydrothermal fluids formed in the late stage.In addition,Md3 was affected by the hydrothermal process more significantly during the formation.SD is deposited and formed when the saturated hydrotherm upwells along with the fracture system in the late stage.This study provides a significant reference for understanding the source and action mechanism of multi-stage dolomitizing fluids and expands the exploration field of the deep dolomite reservoir.
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