查看更多>>摘要：Accurate prediction of formation pore pressure is essential to predict fluid flow and manage hydrocarbon production in petroleum engineering.Recent deep learning technique has been receiving more interest due to the great potential to deal with pore pressure prediction.However,most of the traditional deep learning models are less efficient to address generalization problems.To fill this technical gap,in this work,we developed a new adaptive physics-informed deep learning model with high generalization capability to predict pore pressure values directly from seismic data.Specifically,the new model,named CGP-NN,consists of a novel parametric features extraction approach(1DCPP),a stacked multilayer gated recurrent model(multilayer GRU),and an adaptive physics-informed loss function.Through machine training,the developed model can automatically select the optimal physical model to constrain the re-sults for each pore pressure prediction.The CGP-NN model has the best generalization when the physics-related metric λ=0.5.A hybrid approach combining Eaton and Bowers methods is also proposed to build machine-learnable labels for solving the problem of few labels.To validate the developed model and methodology,a case study on a complex reservoir in Tarim Basin was further performed to demonstrate the high accuracy on the pore pressure prediction of new wells along with the strong generalization ability.The adaptive physics-informed deep learning approach presented here has potential application in the prediction of pore pressures coupled with multiple genesis mechanisms using seismic data.
查看更多>>摘要：Picking velocities from semblances manually is laborious and necessitates experience.Although various methods for automatic velocity picking have been developed,there remains a challenge in efficiently incorporating information from nearby gathers to ensure picked velocity aligns with seismic horizons while also improving picking accuracy.The conventional method of velocity picking from a semblance volume is computationally demanding,highlighting a need for a more efficient strategy.In this study,we introduce a novel method for automatic velocity picking based on multi-object tracking.This dynamic tracking process across different semblance panels can integrate information from nearby gathers effectively while maintaining computational efficiency.First,we employ accelerated density clustering on the velocity spectrum to discern cluster centers without the requirement for prior knowledge regarding the number of clusters.These cluster centers embody the maximum likelihood velocities of the main subsurface structures.Second,our proposed method tracks key points within the semblance vol-ume.Kalman filter is adopted to adjust the tracking process,followed by interpolation on these tracked points to construct the final velocity model.Our synthetic data example demonstrates that our proposed algorithm can effectively rectify the picking errors of the clustering algorithm.We further compare the performances of the clustering method(CM),the proposed tracking method(TM),and the variational method(VM)on a field dataset from the Gulf of Mexico.The results attest that our method offers su-perior accuracy than CM,achieves comparable accuracy with VM,and benefits from a reduced computational cost.
Fábio Júnior Damasceno FernandesLeonardo TeixeiraAntonio Fernando Menezes FreireWagner Moreira Lupinacci...
918-935页
查看更多>>摘要：We apply stochastic seismic inversion and Bayesian facies classification for porosity modeling and igneous rock identification in the presalt interval of the Santos Basin.This integration of seismic and well-derived information enhances reservoir characterization.Stochastic inversion and Bayesian classi-fication are powerful tools because they permit addressing the uncertainties in the model.We used the ES-MDA algorithm to achieve the realizations equivalent to the percentiles P10,P50,and P90 of acoustic impedance,a novel method for acoustic inversion in presalt.The facies were divided into five:reservoir 1,reservoir 2,tight carbonates,clayey rocks,and igneous rocks.To deal with the overlaps in acoustic impedance values of facies,we included geological information using a priori probability,indicating that structural highs are reservoir-dominated.To illustrate our approach,we conducted porosity modeling using facies-related rock-physics models for rock-physics inversion in an area with a well drilled in a coquina bank and evaluated the thickness and extension of an igneous intrusion near the carbonate-salt interface.The modeled porosity and the classified seismic facies are in good agreement with the ones observed in the wells.Notably,the coquinas bank presents an improvement in the porosity towards the top.The a priori probability model was crucial for limiting the clayey rocks to the structural lows.In Well B,the hit rate of the igneous rock in the three scenarios is higher than 60％,showing an excellent thickness-prediction capability.
查看更多>>摘要：Emulsification is one of the important mechanisms of surfactant flooding.To improve oil recovery for low permeability reservoirs,a highly efficient emulsification oil flooding system consisting of anionic sur-factant sodium alkyl glucosyl hydroxypropyl sulfonate(APGSHS)and zwitterionic surfactant octadecyl betaine(BS-18)is proposed.The performance of APGSHS/BS-18 mixed surfactant system was evaluated in terms of interfacial tension,emulsification capability,emulsion size and distribution,wettability alteration,temperature-resistance and salt-resistance.The emulsification speed was used to evaluate the emulsification ability of surfactant systems,and the results show that mixed surfactant systems can completely emulsify the crude oil into emulsions droplets even under low energy conditions.Meanwhile,the system exhibits good temperature and salt resistance.Finally,the best oil recovery of 25.45％is achieved for low permeability core by the mixed surfactant system with a total concentration of 0.3 wt％while the molar ratio of APGSHS:BS-18 is 4∶6.The current study indicates that the anionic/zwitterionic mixed surfactant system can improve the oil flooding efficiency and is potential candidate for application in low permeability reservoirs.
查看更多>>摘要：This paper aims to investigate the tragacanth gum potential as a natural polymer combined with natural clay mineral(montmorillonite,kaolinite,and illite)nanoparticles(NPs)to form NP-polymer suspension for enhanced oil recovery(EOR)in carbonate reservoirs.Thermal gravimetric analysis(TGA)tests were conducted initially in order to evaluate the properties of tragacanth gum.Subsequently,scanning elec-tron microscopy(SEM)and energy-dispersive X-ray(EDX)tests were used to detect the structure of clay particles.In various scenarios,the effects of natural NPs and polymer on the wettability alteration,interfacial tension(IFT)reduction,viscosity improvement,and oil recovery were investigated through contact angle system,ring method,AntonPaar viscometer,and core flooding tests,respectively.The entire experiment was conducted at 25,50,and 75 ℃,respectively.According to the experimental re-sults,the clay minerals alone did not have a significant effect on viscosity,but the addition of minerals to the polymer solution leads to the viscosity enhancement remarkably,resulting mobility ratio improve-ment.Among clay NPs,the combination of natural polymer and kaolinite results in increased viscosity at all temperatures.Considerable wettability alteration was also observed in the case of natural polymer and illite NPs.Illite in combination with natural polymer showed an ability in reducing IFT.Finally,the results of displacement experiments revealed that the combination of natural polymer and kaolinite could be the best option for EOR due to its substantial ability to improve the recovery factor.
查看更多>>摘要：Deformable gel particles(DGPs)possess the capability of deep profile control and flooding.However,the deep migration behavior and plugging mechanism along their path remain unclear.Breakage,an inev-itable phenomenon during particle migration,significantly impacts the deep plugging effect.Due to the complexity of the process,few studies have been conducted on this subject.In this paper,we conducted DGP flow experiments using a physical model of a multi-point sandpack under various injection rates and particle sizes.Particle size and concentration tests were performed at each measurement point to investigate the transportation behavior of particles in the deep part of the reservoir.The residual resistance coefficient and concentration changes along the porous media were combined to analyze the plugging performance of DGPs.Furthermore,the particle breakage along their path was revealed by analyzing the changes in particle size along the way.A mathematical model of breakage and concen-tration changes along the path was established.The results showed that the passage after breakage is a significant migration behavior of particles in porous media.The particles were reduced to less than half of their initial size at the front of the porous media.Breakage is an essential reason for the continuous decreases in particle concentration,size,and residual resistance coefficient.However,the particles can remain in porous media after breakage and play a significant role in deep plugging.Higher injection rates or larger particle sizes resulted in faster breakage along the injection direction,higher degrees of breakage,and faster decreases in residual resistance coefficient along the path.These conditions also led to a weaker deep plugging ability.Smaller particles were more evenly retained along the path,but more particles flowed out of the porous media,resulting in a poor deep plugging effect.The particle size is a function of particle size before injection,transport distance,and different injection parameters(injection rate or the diameter ratio of DGP to throat).Likewise,the particle concentration is a function of initial concentration,transport distance,and different injection parameters.These models can be utilized to optimize particle injection parameters,thereby achieving the goal of fine-tuning oil displacement.
查看更多>>摘要：CO2 emulsions used for EOR have received a lot of interest because of its good performance on CO2 mobility reduction.However,most of them have been focusing on the high quality CO2 emulsion(high CO2 fraction),while CO2 emulsion with high water cut has been rarely researched.In this paper,we carried out a comprehensive experimental study of using high water cut CO2/H2O emulsion for enhancing oil recovery.Firstly,a nonionic surfactant,alkyl glycosides(APG),was selected to stabilize CO2/H2O emulsion,and the corresponding morphology and stability were evaluated with a transparent PVT cell.Subsequently,plugging capacity and apparent viscosity of CO2/H2O emulsion were measured sys-tematically by a sand pack displacement apparatus connected with a 1.95-m long capillary tube.Furthermore,a high water cut(40 vol％)CO2/H2O emulsion was selected for flooding experiments in a long sand pack and a core sample,and the oil recovery,the rate of oil recovery,and the pressure gra-dients were analyzed.The results indicated that APG had a good performance on emulsifying and sta-bilizing CO2 emulsion.An inversion from H2O/CO2 emulsion to CO2/H2O emulsion with the increase in water cut was confirmed.CO2/H2O emulsions with lower water cuts presented higher apparent viscosity,while the optimal plugging capacity of CO2/H2O emulsion occurred at a certain water cut.Eventually,the displacement using CO2/H2O emulsion provided 18.98％and 13.36％additional oil recovery than that using pure CO2 in long sand pack and core tests,respectively.This work may provide guidelines for EOR using CO2 emulsions with high water cut.
查看更多>>摘要：Gravity assistance is a critical factor influencing CO2-oil mixing and miscible flow during EOR and CO2 geological storage.Based on the Navier-Stokes equation,component mass conservation equation,and fluid property-composition relationship,a mathematical model for pore-scale CO2 injection in oil-saturated porous media was developed in this study.The model can reflect the effects of gravity assis-tance,component diffusion,fluid density variation,and velocity change on EOR and CO2 storage.For non-homogeneous porous media,the gravity influence and large density difference help to minimize the velocity difference between the main flow path and the surrounding area,thus improving the oil re-covery and CO2 storage.Large CO2 injection angles and oil-CO2 density differences can increase the oil recovery by 22.6％and 4.2％,respectively,and increase CO2 storage by 37.9％and 4.7％,respectively.Component diffusion facilitates the transportation of the oil components from the low-velocity region to the main flow path,thereby reducing the oil/CO2 concentration difference within the porous media.Component diffusion can increase oil recovery and CO2 storage by 5.7％and 6.9％,respectively.In addi-tion,combined with the component diffusion,a low CO2 injection rate creates a more uniform spatial distribution of the oil/CO2 component,resulting in increases of 9.5％oil recovery and 15.7％CO2 storage,respectively.This study provides theoretical support for improving the geological CO2 storage and EOR processes.
查看更多>>摘要：Spontaneous imbibition(SI)is an important mechanism for enhancing oil recovery in low-permeability reservoirs.Due to the strong heterogeneity,and the non-Darcy flow,the construction of SI model for low-permeability reservoirs is extremely challenging.Commonly,traditional SI models based on single or averaged capillary tortuosity ignore the influence of heterogeneity of pore seepage channels and the threshold pressure(TP)on imbibition.Therefore,in this work,based on capillary model and fractal theory,a mathematical model of characterizing SI considering heterogeneity of pore seepage channels is established.On this basis,the threshold pressure was introduced to determine the pore radius at which the wetted phase can displace oil.The proposed new SI model was verified by imbibition experimental data.The study shows that for weakly heterogeneous cores with permeability of 0-1 mD,the traditional SI model can characterize the imbibition process relatively accurately,and the new imbibition model can increase the coefficient of determination by 1.05 times.However,traditional model has serious de-viations in predicting the imbibition recovery for cores with permeability of 10-50 mD.The new SI model coupling with heterogeneity of pore seepage channels and threshold pressure effectively solves this problem,and the determination coefficient is increased from 0.344 to 0.922,which is increased by 2.68 times.For low-permeability reservoirs,the production of the oil in transitional pores(0.01-0.1 μm)and mesopores(0.1-1 μm)significantly affects the imbibition recovery,as the research shows that when the heterogeneity of pore seepage channels is ignored,the oil recovery in transitional pores and mes-opores decreases by 7.54％and 4.26％,respectively.Sensitivity analysis shows that increasing interfacial tension,decreasing contact angle,oil-water viscosity ratio and threshold pressure will increase imbi-bition recovery.In addition,there are critical values for the influence of these factors on the imbibition recovery,which provides theoretical support for surfactant optimization.
查看更多>>摘要：The oil production of the multi-fractured horizontal wells(MFHWs)declines quickly in unconventional oil reservoirs due to the fast depletion of natural energy.Gas injection has been acknowledged as an effective method to improve oil recovery factor from unconventional oil reservoirs.Hydrocarbon gas huff-n-puff becomes preferable when the CO2 source is limited.However,the impact of complex fracture networks and well interference on the EOR performance of multiple MFHWs is still unclear.The optimal gas huff-n-puff parameters are significant for enhancing oil recovery.This work aims to optimize the hydrocarbon gas injection and production parameters for multiple MFHWs with complex fracture net-works in unconventional oil reservoirs.Firstly,the numerical model based on unstructured grids is developed to characterize the complex fracture networks and capture the dynamic fracture features.Secondly,the PVT phase behavior simulation was carried out to provide the fluid model for numerical simulation.Thirdly,the optimal parameters for hydrocarbon gas huff-n-puff were obtained.Finally,the dominant factors of hydrocarbon gas huff-n-puff under complex fracture networks are obtained by fuzzy mathematical method.Results reveal that the current pressure of hydrocarbon gas injection can achieve miscible displacement.The optimal injection and production parameters are obtained by single-factor analysis to analyze the effect of individual parameter.Gas injection time is the dominant factor of hy-drocarbon gas huff-n-puff in unconventional oil reservoirs with complex fracture networks.This work can offer engineers guidance for hydrocarbon gas huff-n-puff of multiple MFHWs considering the complex fracture networks.
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