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Journal of Petroleum Science & Engineering
Elsevier Science B.V.
Journal of Petroleum Science & Engineering

Elsevier Science B.V.

0920-4105

Journal of Petroleum Science & Engineering/Journal Journal of Petroleum Science & Engineering
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收录年代

    Dynamic behaviors and mechanisms of fluid-fluid interaction in low salinity waterflooding of carbonate reservoirs

    Rukuan ChaiYuetian LiuYuting He
    15页
    查看更多>>摘要：Low salinity waterflooding of carbonate reservoirs has attracted wide attention and many mechanisms have been proposed.However,the dynamic behaviors and mechanisms of the fluid-fluid interaction in low salinity waterflooding have not yet been thoroughly classified.Regarding this,core flooding,contact angle & zeta po-tential,interfacial tension & interfacial dilatational rheology,total organic carbon,and cryogenic-scanning electron microscopy(cryo-SEM)experiments were combined in this study to investigate the role of the fluid-fluid interaction in low salinity waterflooding and reveal its in-depth mechanism.Core flooding & contact angle & zeta potential experiments results showed that the rock-fluid and fluid-fluid interactions act synergis-tically to enhance oil recovery.Thereof,as ionic strength decreases,the contribution of the fluid-fluid interaction for additional recovery first increases to the maximum 67.04 % in 20-times diluted formation waterflooding and then decreases to 29.99 % in 40-times diluted formation waterflooding.Moreover,Mg~(2+)and SO_4~(2-)as the po-tential determining ions both showed positive effects on the fluid-fluid interaction in low salinity waterflooding,As Mg~(2+)concentration increases,the contribution of the fluid-fluid interaction for additional recovery increases to 82.63 % and then decreases.As SO2-concentration increases,the contribution of the fluid-fluid interaction continuously increases and reaches 84.56 %.Interfacial tension and interfacial dilatational rheology results illustrated that the interfacial viscoelasticity enhancement is the important mechanism of the fluid-fluid interaction in low salinity waterflooding which could suppress the snap-off and stabilize the crude oil.Moreover,the ! total organic carbon and cryo-SEM results showed the oil-in-water emulsions with strong interfacial viscoelasticity are stably dispersed in low saline water,which could block the pores and throats and increase the sweep efficiency.In conclusion,the enhancement of interfacial viscoelasticity and the formation and existence of oil-in-water emulsion are the two important mechanisms of the fluid-fluid interaction in low salinity waterflooding,Herein,these two mechanisms both first enhance and then weaken as ionic strength decreases;enhance and then weaken as Mg~(2+)concentration increases,continuously enhance as SO_4~(2-)concentration increases.
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    Coupled optimization of carbon dioxide sequestration and CO2 enhanced oil recovery

    Shahrokh Bahrami KashkooliAsghar GandomkarMasoud Riazi
    12页
    查看更多>>摘要：GO2 injection into hydrocarbon reservoirs can simultaneously pave the path for two important processes,namely oil production increase,and CO2 storage.This combined optimization problem can be referred to as carbon capture and storage-enhanced oil recovery(CCS-EOR)problem.CCS-EOR is a challenging task with many opportunities which should be studied in a timely manner.Moreover,the attitude of the management team towards prioritizing CCS or EOR should be considered.Therefore,in the current study,CCS-EOR problem was addressed by utilizing the dynamic well flow settings(bottom-hole pressure and/or flow rate)as the optimization variables with a weighted objective function.This approach was tested on a case study.Its huge simulation time due to high dimensionality remained a serious challenge.One effective approach was to use the underlying applied knowledge of the system and extract that wisdom to reduce the simulation time in a rational manner.CO2 breakthrough time was such a knowledge.Therefore,the importance of CO2 breakthrough time was stressed,and the understanding of the response of the simulator to this event was used to considerably reduce the simulation time in a black box approach.Moreover,a concise sensitivity analysis was performed which helped to schedule the workflow based on the given priority to each process.The optimized case could improve the objective value and gas storage efficiency up to 2.86 % and 12.1 % respectively.The obtained results can be used to analyze a variety of operational matters such as the CO2 distribution map in the reservoir,and the well settings.
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    Mixed salt precipitation and water evaporation during smart water alternative CO2 injection in carbonate reservoirs

    Peyman AbbasiMohammad MadaniSaeed Abbasi
    13页
    查看更多>>摘要：The main objective in this study is to experimentally elucidate the challenges associated with smart water alternating CO2(smart WAG-CO2)with regard to permeability impairment that occurs due to interaction between injection water-formation water and injection gas-water.For this purpose,static tests including compatibility and zeta potential measurement,and dynamic tests including water,dry and wet CO2 coreflooding experiments are conducted.The findings illustrate that formation scales due to mixing formation water and injection water are mixed-salt with SrSO4 as the dominant scale type.Despite the fact that zeta potential outcomes point up that an increase in sulfate concentration in the injection water advantageously leads to proper potential oil recovery,the coreflooding tests reveal mat sulfate ion concentration is the main factor in controlling k/k;ratio;the more the sulfate concentration,the more the level of permeability impairment.During gas injection,evaporation phenomenon was observed,with the evaporation rate being function of core water saturation.In addition,as salinity increases,while evaporation rate is reduced,more salt precipitation occurs in the sample with higher salinity.The results exhibited that initial permeability is more effective than water salinity in changing gas effective permeability.The results of this study can aid the engineers working in upstream sections of petroleum industry to reduce the scale removal expenditures and enhance the smart WAG-CO2 technique.
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    Feature-based ensemble history matching in a fractured carbonate reservoir using time-lapse deep electromagnetic tomography

    Yanhui ZhangIbrahim HoteitKlemens Katterbauer
    14页
    查看更多>>摘要：Carbonate reservoirs typically exhibit very complex geological structures and are characterized by flow dynamics primarily occurring in fractures.The intricate network of fractures as well as their interconnectedness may lead to unexpected flow patterns and uneven sweep efficiency.Determining reservoir properties of both matrix and fracture channels is quintessential for accurately tracking the fluid front movement in the reservoir,optimizing sweep efficiency,and maximizing hydrocarbon production.In this study,we showcase the application of a feature-oriented ensemble-based history matching workflow to a complex fractured carbonate reservoir box model,focusing on the use of formation resistivity tomography data that are usually inferred from deep crosswell electromagnetic(EM)surveys.Compared with the production data that are commonly used in history matching,deep EM measurements provide additional information about the spatial distribution of subsurface reservoir properties in the interwell volumes by exploiting the strong resistivity contrast between water and hydrocarbons.A hybrid parameterization approach is used to represent the multiscale fracture distribution in which the spatial distribution of small-scale fractures is modelled by a truncated Gaussian simulation method.A large number(over one million)of uncertain model parameters including reservoir matrix and fracture properties as well as Archie's parameters are identified and updated by an iterative ensemble smoother.For an efficient integration of the high-dimensional and noisy EM tomography data,the boundary or contour information extracted from the I EM resistivity field is instead assimilated through a distance parameterization approach.A modified bootstrap-based localization is proposed to regularize the model updates adaptively during the iteration to reduce sampling errors.Especially,to improve the computational efficiency in dealing with the large dimensions of both data and model parameters,the localization is implemented in a projected low-dimensional data subspace.Experimental I results demonstrate the applicability and efficiency of the developed workflow for reservoir history matching in J more realistic model settings.The comparative case study also illustrates the significance of jointly incorporating multiple sources of data for better quantification of model uncertainty,and the great potential of deep EM data I for enhancing the characterization of complex fractured carbonate reservoirs.
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    A three-way convolutional network to compare 4D seismic data and reservoir simulation models in different domains

    Klaus RollmannAurea Soriano-VargasMarcos Cirne
    12页
    查看更多>>摘要：Four-dimensional seismic(4DS)contains spatial information that provides insights into the location,shape and movement of fluids(oil,gas,water).It helps engineers to adjust reservoir simulation models and increase their capability of providing reliable production forecasts.Recent probabilistic approaches consider hundreds of numerical simulation model scenarios,which require automated methods to evaluate this large number of numerical models based on observed 4D seismic data.Comparing spatial information of seismic and numerical simulation data is difficult as,usually,these data are converted to maps with different properties.We propose a novel approach to compare 4D seismic data and simulation models using a three-way deep neural network that is trained using a reference image(4D seismic data)with two simulation model candidates.It learns to find the simulation models that best characterize the reference.Our method is underpinned by more than a thousand pairs of simulation models and reference maps evaluated by human specialists for training.For testing,we compare the inter-rater agreement among different specialist groups and generate a reliable test set considering examples in which there was agreement among at least two specialists.We observed that the group with best-trained specialists agree more in their answers and have a considerably higher inter-rater agreement than the less trained groups.When we evaluate our method with the answers from this specialized group,we observe that the simulation model chosen by our method is the one agreed by the specialists in almost 90% of the cases.We also discuss the impact of different noise levels in the input and show mat our method outperforms other approaches in the literature if noise is present both in the training and test sets.
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    • NSTL

    Modeling transient flow behavior of eccentric horizontal well in bi-zonal formation

    Ren-Shi NieJing-Shun LiQi Deng
    15页
    查看更多>>摘要：In this study,an eccentric horizontal well in a bi-zonal formation and traversing the inner zone is first modeled,Three novel conceptual models are presented for three different well-placement situations:a horizontal well(in in an inner zone,(ii)traversing partially in an inner zone,and(iii)traversing fully in an inner zone.A point source model in a bi-zonal formation is established and solved using the Laplace transform,finite Fourier cosine transform and separation of variables.The pressure solutions for a point source in the inner and outer zones are obtained by integrating the point-source solution along a horizontal well.A series of type curves is simulated to reveal the transient flow behavior of a horizontal well in a bi-zonal formation.The main flow regimes are dis-cerned based on the type curves.Eight,six,and six flow regimes were discerned for the first,second,and third situations,respectively.The effect of different deviated distances on the type curves was analyzed.The type curves are compared among the three situations.Finally,the model is applied to a real case to validate it.This study can provide insights into the transient flow behavior controlled by an eccentric horizontal well in a bi-zonal formation.
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    • NSTL

    Application of deep learning on well-test interpretation for identifying pressure behavior and characterizing reservoirs

    Peng DongZhiming ChenXinwei Liao
    17页
    查看更多>>摘要：Pressure transient well test analysis is an important tool for identifying reservoir characteristics.However,the reliability of the results from well test analysis could be uncertain due to the analysts'lack of experience.This study aims to apply one-dimensional convolutional neural networks(ID CNN)and build an automatic interpretation model of well test data.The model can automatically identify not only the curve type but also the associated parameters.We integrate this automatic interpretation model with four classic well test models,with no model architecture adjustment and hyper-parameters.We validate the results that the curve classification accuracy reaches 97 %,and the median relative error of the curve parameter inversion is approximate 10 %.In addition,the performance of ID CNN is compared to the artificial neural network(ANN)and two-dimensional convolutional neural networks(2D CNN).Results show that the ID CNN has a faster training speed and has better accuracy in parameter inversion than ANN and 2D CNN.Finally,the automatic interpretation model is further validated with three field cases.
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    • NSTL

    Prediction of pressure gradient for oil-water flow:A comprehensive analysis on the performance of machine learning algorithms

    Md Ferdous WahidReza TafreshiZurwa Khan
    12页
    查看更多>>摘要：Pressure gradient(PG)in liquid-liquid flow is one of the key components to design an energy-efficient transportation system for wellbores.This study aims to develop five robust machine learning(ML)algorithms and their fusions for a wide range of flow patterns(FP)regimes.The MLs include Support Vector Machine(SVM),Gaussian Process(GP),Random Forest(RF),Artificial Neural Network(ANN),k-Nearest Neighbor(kNN),and fusions of these five MLs.A total of eleven hundred experimental data points for nine FPs(two stratified and seven dispersed patterns)in horizontal wellbores are used to develop the MLs.The MLs'performance is evaluated using the metrics including mean absolute percentage error(MAPE),median absolute percentage error(MdAPE),coefficient of variation of root mean squared error(CV-RMSE),and adjusted coefficient of determination.The evaluation metrics are cross-validated using a repeated train-test split strategy.Seven important predictor variables are identified using a supervised feature selection approach:oil and water velocities,FP,input diameter,oil and water density,and oil viscosity.The results show that the high PG prediction accuracy can be achieved using GP compared to other MLs except for the ML-fusions(p<0.05).A Friedman's test and Wilcoxon Sign-Rank post hoc analysis with Bonferroni correction show that PG prediction errors using GP are significantly lower than using the ANN model(p<0.05).The values are 18.44 % and 23.9 % for CV-RMSE,11.6 % and 10.06 % for MAPE,and 7.5 % and 6.75 % for MdAPE,using ANN and GP,respectively.While the previous studies mostly used ANN to demonstrate the capability of MLs to predict PG over the mechanistic or correlation-based models,the present research has shown that GP is even better than ANN using a wide range of FPs and a large data set.
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    A method of predicting oil and gas resource spatial distribution based on Bayesian network and its application

    Qiulin GuoHongjia RenJingdu Yu
    12页
    查看更多>>摘要：The spatial distribution prediction of hydrocarbon resource is essential to reduce exploration risks and improve investment returns.Determining the location of the spatial distribution of oil and gas resources is a complex and uncertain problem.This paper systematically analyzes oil and gas exploration risk assessment and resource spatial distribution prediction technology,and proposes a method of predicting hydrocarbon spatial distribution based on averaged one-dependence estimators(AODE).Firstly,the transformation process of petroleum geological problem to mathematical model is described.Then,the classification principle and decision rule of AODE model are expounded.Finally,a case study of Sangonghe Formation in the hinterland of Junggar Basin in China is given to further illustrate the proposed method and work flow.The case prediction results not only reveal that the accuracy of the AODE model can reach 85.2% on the data set of 203 exploratory wells,which is higher than state-of-the-art methods(such as tree augmented Bayesian network method and the Mahalanobis distance method),but also point out the areas witii high probability of remaining hydrocarbon resources in Sangonghe Formation,which provides decision-making basis for the next exploration.The application results show that the AODE model can effectively predict the spatial distribution of oil and gas and visualize the risk of geological exploration,thereby optimizing drilling strategy and increasing economic benefits.
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    • NSTL

    Influence of asphaltenes and resins on water/model oil interfacial tension and emulsion behavior:Comparison of extracted fractions from crude oils with different asphaltene stability

    Caiua Araujo AlvesJose Francisco Romero YanesFilipe Xavier Feitosa
    11页
    查看更多>>摘要：Asphaltenes and resins make a major contribution for the formation of stable water-in-oil emulsions during crude production,which could affect process operations and increase costs.The purpose of this investigation is to study the influence of these molecular substances from two different crude oil samples(regarding asphaltene stability)on the water-model oil interfacial tension,along with their effect on the emulsion stability.Asphaltene stability of these crude oils presented a marked difference when studied in our past work,with asphaltene precipitation onset that vary from 56 to 75 n-heptane wt %,despite their similar SARA composition.This difference on asphaltene stability was contrasted in this work with the chemical characterization,interfacial activity,and emulsion behavior of crude oil asphaltenes,resins,and their mixtures using toluene solutions.For each crude oil,resins and asphaltenes were extracted and characterized by XRD,SEM/EDS,FTIR,and elemental analysis,to better understand their molecular structure and surface-active species content.Then,it was prepared different model oil solutions in toluene,varying the content of asphaltenes and resins(500,1,000,and 2000 mg/L).Additionally,it was prepared 2000 mg/L asphaltene/resin mixtures with different ratios(75:25 wt%,50:50 wt%,and 25:75 wt%).Dynamic interfacial tension between the model oil and water was measured by intermediate of a Du Noiiy ring method.Afterward,each model system was emulsified by adding water(at the same volumetric ratio)in a bottle test and stability was analyzed.For the sample with lower stable asphaltenes,a rapid stabilization of the dynamic interfacial tension(IFT)was observed,together with a decrease of IFT from 26.8 to 24.2 mN/m at the limit of asphaltene content studied.On the contrary,for the high stable asphaltenes sample,a transient dynamic IFT behavior was observed,until reach 12.0 mN/m(the lower operational equipment limit).Similar results were obtained for resins model solutions for both crude oils tested.For asphaltene obtained from the sample with lower asphaltene stability,the emulsions presented high stability(for a 24 h test).Besides for the high asphaltene stability sample and resins model oils,all emulsions prepared were unstable.Useful insights are given by the oil fractions chemical characterization,suggesting that smaller sized molecules from high Jtable crude oils have a predominant effect on IFT reduction,while larger molecules from less stable oils are responsible for the emulsion stability.
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    • NSTL