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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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    Substituting petro-elastic model with a new proxy to assimilate time-lapse seismic data considering model errors

    Danaei, ShahramSilva Neto, Gilson M.Schiozer, Denis J.Davolio, Alessandra...
    18页
    查看更多>>摘要：Dynamic data from oil and gas reservoirs (such as well-production or 4D seismic data) have been used often to reduce uncertainty in reservoir simulation models. These data are assimilated in the simulation models separately or jointly. Assimilation of 4D seismic data conventionally involves with a petro-elastic model (PEM) to transform outputs from the simulation models to elastic properties. The PEM is a set of different equations with uncertain parameters and its inclusion in assimilation algorithms calls on multidisciplinary teams of geoscientists and engineers. Moreover, PEM requires extraction of different outputs from the simulation models for the seismic forward model calculations. The extraction process can be costly for large-scale simulation models of giant reservoirs. This research presents a new petro-elastic proxy model (named DAI-Proxy) with a novel formulation to substitute the PEM and integrate 4D seismic data. DAI-Proxy relates time-lapse acoustic impedance to a summation of saturation and pressure changes with two coefficients which are functions of porosity. As the proxy is an approximation of the PEM, its application is affected by model error. We introduce two approaches to account for the proxy model error: (1) considering uncertain coefficients for the DAI-Proxy and (2) using fixed coefficients in the proxy while estimating model errors statistics from the prior ensemble of models. We incorporate these two approaches with a data assimilation algorithm to assimilate simultaneously 4D seismic and well-production data. A benchmark case is used with different cases of data assimilation to compare the DAIProxy and the PEM applications. Results show that data match quality for 4D seismic and well-production have similar responses for the PEM and DAI-Proxy implementations. In terms of production forecast, using fixed coefficients in the proxy with its model error treatment create a data assimilation framework comparable to the PEM case. Our results indicate that the traditional PEM application to integrate jointly 4D seismic and wellproduction data can be replaced with our new DAI-Proxy application. Given the degree of uncertainty in the PEM, related to the rock and fluid models, our proxy provides similar results with fewer uncertain inputs. The proxy offers further advantage as it needs less outputs from the simulation models for seismic forward model calculations. In addition, it helps petroleum engineers to use a computationally less expensive model (light model) as a substitute for the PEM to assimilate 4D seismic data.
      原文链接:
    • NSTL
    • Elsevier

    A new predrilling reservoir permeability prediction model and its application

    Chen, GuosongMeng, YuanlinHuan, JinlaiWang, Youchun...
    14页
    查看更多>>摘要：The accurate prediction of sandstone permeability from variables such as porosity, composition, and texture is one of the major problems in petroleum geology. However, the application of geological variables related to diagenesis in permeability prediction models is relatively rare, especially the anomalous variations of clay content and type. This study investigates the differential control of sedimentation and diagenesis on permeability using a comprehensive analysis of cores, thin sections, routine core analysis, X-ray diffraction, and scanning electron microscopy from sandstone samples in the third member of the Weizhou Formation (Ew(3)), Weizhou 12-X oilfield, Weixinan Sag, Beibu Gulf Basin, China. An innovative sandstone reservoir permeability prediction model is proposed by introducing the clay factor beta confining the effect of clay minerals on permeability, predicting the spatial distribution of diagenetic index (I-D) using the Diagenetic Modeling System (DMS), and improving the Walderhaug permeability prediction model. The permeability of the well evaluated in the study was predicted with the relative and absolute errors changing from 0.01 mD to 192.65 mD and from 0.00 to 1.00, with an average values of 38.6 mD and 0.33, respectively, based on the sandstone reservoir permeability prediction model in Ew(3). The permeability predicted by the permeability prediction model matches well with the measured permeability in Ew(3). The results indicate that permeability is successfully predicted by the modified Walderhaug permeability prediction model for most sandstone reservoirs with strong diagenesis (such as anomalous changes in clay mineral types and content) under the background of a single distributary channel sedimentary microfacies. In general, anomalously high permeability zones are preferentially distributed in dominant sedimentary-diagenetic facies.
      原文链接:
    • NSTL
    • Elsevier

    A comparative study of dispersed and grafted nanofluids of graphene nanoplatelets with natural polymer in high salinity brine for enhanced oil recovery

    Hamdi, Sinan S.Al-Kayiem, Hussain H.Alsabah, Mohammed S.Muhsan, Ali S....
    17页
    查看更多>>摘要：Polymer flooding as one of conventional chemical enhanced oil recovery (C-EOR) techniques has high potential for declining the mobility ratio and improving oil recovery. The degradation, toxicity, and cost are inherent restrictions in polymer performance at high salinity and high temperature. Recently, incorporation of nanoparticles with a polymer to produce polymeric nanofluids has acquired a great interest as the newest trends of development in nanotechnology for EOR processes. In this study, a comparative evaluation of functionalized graphene nanoplatelets (GNPs) were prepared by two different methods of mixing and grafting with natural Polymer of Gum Arabic (GA). These methods aimed to improve the dispersion stability of the nano-additives in high salinity brines and high temperature conditions for promising alternative C-EOR agent. The physiochemical properties of the functionalized GNPs were characterized by Fourier transform-infrared spectroscopy, Raman spectroscopy, and transmission electron microscope. The zeta potential, dynamic light scattering, and optical absorbance were employed to evaluate the effective dispersion stability of the prepared nanofluids in high salinity concentration 3 wt% and temperature at 90 degrees C. The laboratory results indicated that the dispersion and rheological properties revealed a stable dispersibility of Polymer grafted GNPs (PG-GNPs) in high salinity brine even with high temperatures compared to Polymer dispersed GNPs (PD-GNPs) at low concentration 0.05 mg/mL. However, it was observed that the nature of functionalized GNPs with GA has a significant role in increment the capillary number via reducing the value of interfacial tension (IFT) and modification the wettability of pores surface inside the heterogenous micromodel. The core flooding findings of nanofluids injection in the mid permeable sandstone porous media showed that oil recovery enhanced by around 17% and 5% at 0.05 mg/mL of PG-GNPs and PD-GNPs, over the conventional water flooding. Consequently, the overall results of PG-GNPs exhibited better performance compared to PD-GNPs due to successful GNPs layers exfoliation which led to stable dispersion with the same concentration of 0.05 mg/mL at reservoir conditions.
      原文链接:
    • NSTL
    • Elsevier

    Accurate, cost-effective strategy for lean gas condensate sampling, characterization, and phase equilibria study

    Zahedizadeh, ParvizOsfouri, ShahriarAzin, Reza
    22页
    查看更多>>摘要：Accurate recognition of the fluid phase behaviour is the most important and first step for the preservation and hydrocarbon reservoir management. Among the various hydrocarbon fluids, the lean gas condensate fluids show complex and unique behaviour. Due to the nature of these fluids, errors in the laboratory constant volume depletion (CVD) experimental data are inevitable. In this study, the significance of using CVD data in the EoS tuning process is debated using six samples of lean gas condensate. According to the negative composition in the CVD data material balance of all samples, just data of the constant composition expansion (CCE) experiment, saturation pressure, and liquid density in the stock tank are used for tuning the equation of state (EoS) as fundamental experimental data. The results of this study demonstrate that without using any CVD experimental data in the EoS tuning process, this data can be generated accurately using tuned EoS with fundamental data. Therefore, there is no need to do CVD experiments for lean gas condensate fluids characterization, which leads to reduces not only the error in the simulation process but also the laboratory costs. Furthermore, the tuning strategy in this study demonstrates that molecular weight of plus fraction and the volume shift parameter of the heaviest pseudo-component are the effective parameters to adjust the EoS. The objective function has reduced from 0.7360 to 0.1538 (79.10% improvement) just by using these two parameters. A constrained tuning strategy was proposed to keep the critical properties and acentric factor expected trends versus carbon number. The results show uniform and swing trends in the case of constrained and unconstrained tuning strategies, respectively. Therefore, using a constrained tuning strategy is essential to obtain a fluid with an authentic thermodynamic background after the tuning process. The proposed analysis method of CVD experimental data suggests that gas compressibility factor and gas composition as the main sources of error, while the experimental parameters of retrograde liquid and cumulative gas production have ignorable errors.
      原文链接:
    • NSTL
    • Elsevier

    Study on recovery factor and interlayer interference mechanism of multilayer co-production in tight gas reservoir with high heterogeneity and multi-pressure systems

    Chai, XiaolongTian, LengDong, PengjuWang, Chunyao...
    14页
    查看更多>>摘要：The coupling effects of complex pore structure and poor reservoir properties generally lead to relatively low production of single layer in tight gas reservoir. The multilayer or multilayer co-production increasingly gain popularity in exploitation of tight gas reservoirs to achieve high recovery factor and economic profit. The multilayer co-production of tight gas reservoir with high heterogeneity or multi-pressure systems is more complex than that of the single-layer production. It is still not very clear about the mechanism of co-production. To fill this gap, a set of numerical simulations are intentionally designed and implemented in this paper to systematically understand production characteristics, interlayer interference, and recovery factor of multilayer co-production in tight gas reservoirs. Based on the established numerical gas reservoir simulation model, sensitivity analysis of influencing parameters of interlayer interference and recovery factor, including interlayer permeability contrast, interlayer pressure difference, thickness of gas layer, gas saturation, and producing rate, has been carried out. Subsequently, a type of machine-learning method, i.e., random forest method (RFM), is use to quantitatively characterize the main influencing parameters on interlayer interference and recovery factor. In the end, the predicted models of recovery factor and interference time are proposed by using the linear correlation and nonlinear correlation. The numerical experiment results reveal that the gas of high-pressure layer will flow back to the low-pressure layer in the multilayer co-production scenario and the influencing parameters have a great effect on daily gas production, recovery factor, backflow time, formation pressure and contribution rate of each layer. The thickness of gas layer and producing rate have the strongest and weakest influences on the gas recovery, respectively. However, the influence of interlayer pressure difference on interlayer interference is highest and the gas saturation has a lower effect on interference time than other parameters. The recovery factor and interference time of multilayer co-production is about 54.09%-63.82% and 55-565 days respectively. The correlation results of recovery factor and interference time have a good agreement with the results of numerical simulation, and the uncertainties are controlled within 10%. The research results of numerical simulation, RFM and predicted model are applied to a gas well of the tight gas and the validity and practicability of the results are verified, which can provide a solid foundation for the exploitation of tight gas reservoirs with high heterogeneity and multi-pressure systems.
      原文链接:
    • NSTL
    • Elsevier

    A fractal physics-based data-driven model for water-flooding reservoir (FlowNet-fractal)

    Xu, YunfengHu, YujieRao, XiangZhao, Hui...
    15页
    查看更多>>摘要：This paper proposed a fractal physics-based data-driven framework for reservoir simulation (name as FlowNetfractal) by integrating physics-based data-driven model with fractal theory. FlowNet-fractal enables fast history matching and production prediction of water flooding reservoirs by considering the fractal characteristics of reservoir permeability and porosity. Details of FlowNet-fractal calculation were given with an oil-water twophase flow example. In the FlowNet-fractal, transmissibility, control pore volumes (PVs), fractal mass dimension and fractal index were separately defined in each one-dimensional connection element to map reservoir properties, which more specifically reflected reservoir heterogeneity than the traditional FlowNet method. In this paper, an example of simple heterogeneous reservoir model and two actual water-flooding reservoir cases with different scales were given. The calculation results showed that the FlowNet-fractal method outperformed the FlowNet method in both the convergence speed and the accuracy of history matching. Moreover, the heterogeneity of the reservoir model was also defined by the inversed fractal mass dimension and the fractal index.
      原文链接:
    • NSTL
    • Elsevier

    A well rate prediction method based on LSTM algorithm considering manual operations

    Li, XianglingLi, XianbingYu, ChunyeFan, Dongyan...
    9页
    查看更多>>摘要：Manual operations such as changing the size of chokes as well as opening and closing of the well have a great impact on oil and gas production from the well. This scenario is not considered in most deep learning methods for predicting productivity. Therefore, a deep learning method based on a long short-term memory (LSTM) neural network model was established to predict well performance considering the manual operations. The input dataset was composed of data related to choke size, daily opening time series, and production; the first 90% of the dataset was used as the training set and the remaining 10% was used as the test set. The deep learning model was constructed using a LSTM module, regularization process, and dropout network. The formulated LSTM model was proficient compared with a model that did not consider the manual operation process, and showed better prediction accuracy. Through multiple experiments, the production-related time step was optimized at three, indicating that prediction for the subsequent step was most relevant to the initial three step inputs. Overall, the operation of opening and closing of wells, changing the size of chokes, and variations in daily production time can be considered in our LSTM deep learning model, which provides more reasonable results.
      原文链接:
    • NSTL
    • Elsevier

    A generalized machine learning workflow to visualize mechanical discontinuity

    Liu, RuiMisra, Siddharth
    14页
    查看更多>>摘要：Accurate detection and mapping of mechanical discontinuity in materials has widespread industrial and research applications. We developed a generalized machine-learning framework for visualizing single mechanical discontinuity embedded in material of any composition, velocity, density, porosity, and size with limited data. The proposed visualization of discontinuity requires accurate estimations of the length, location, and orientation of the embedded discontinuity by processing multipoint wave-transmission measurements. k-Wave simulator is used to create a large dataset of elastic waveforms recorded during multi-point wave-transmission measurements through materials containing single mechanical discontinuity. k-Wave simulator considers the wave attenuation, dispersion, and mode conversion in wave motion. Discrete wavelet transform (DWT) and statistical feature extraction are essential for data preprocessing prior to the data-driven model development. DWT also minimizes the effect of noise. Using hyper-parameter tuning and cross validation, gradient boosting regression can visualize the mechanical discontinuity with an accuracy of 0.85, in terms of coefficient of determination. A double-layered neural network-based regression has better performance with an accuracy of 0.95. Use of convolutional neural network converts the predictive task from a waveform processing to an image processing problem. Convolutional neural network achieved a generalization performance of 0.91. The proposed generalized workflow requires robust simulation of wave propagation, signal processing, feature engineering, and model evaluation. Sensors closest to the source and those located opposite the source are the most significant for the desired visualization. Notably, the sensors closest to the source capture the non-linear associations, whereas the sensor on the border opposite to the source capture the linear associations between the measured waveforms and the properties of the mechanical discontinuity.
      原文链接:
    • NSTL
    • Elsevier

    The synergistic effect of Fe2O3/SiO2 nanoparticles concentration on rheology, wettability, and brine-oil interfacial tension

    Hassan, Yarima MudassirGuan, Beh HoeChuan, Lee KeanHamza, Mohammed Falalu...
    9页
    查看更多>>摘要：Various nanoparticles (NPs) have been discovered as revolutionary agents of change in reservoir properties such as rheology, interfacial tension (IFT), and surface wettability that could lead to enhanced oil displacement. In recent years, Silicon dioxide (SiO2) and various metal oxide NPs have recorded successes in oil recovery, thus, understanding composites of NPs fluids is anticipated to provide unprecedented outcomes. The present study is aimed at evaluating the synergy impact of the NPs concentrations of Fe2O3/SiO2 on rheology, IFT, and rock surface wettability. The composite of Fe2O3/SiO2 was firstly synthesized and characterized to determine its physical and chemical properties. Subsequently, nanofluids of Fe2O3/SiO2 were prepared at different concentrations using brine as a fluid dispersant phase and investigated on the rheology, IFT, and wettability at 60 degrees C. The results have shown that the dispersion stability of the Fe2O3 NPs was found to have increased from -11 mV to -38 mV when SiO2 NPs were introduced and led to an increase in the viscosity of the composite fluids from 0.88 cP to 1.95 cP. The base case IFT (brine/oil system) was observed to be 17.39 mN/m, and upon introduction of the Fe2O3/SiO2 composite, the IFT significantly reduced to 0.21 mN/m as a result of the high attachment of the NPs at the oil/fluid interface. Furthermore, combining SiO2 with the Fe2O3 has facilitated the adsorption capacity of the NPs composite leading to the spreading of the nanocomposite fluids on the surface of sandstone which eventually alters the wettability from 140.65 degrees to 26.23 degrees. The study has shown the synergy effect of composite NPs which resulted in reducing the IFT and wettability by 98 and 81% respectively in advance of 50-60% reductions commonly observed when individual NPs have been used.
      原文链接:
    • NSTL
    • Elsevier

    Numerical investigations on rock breaking mechanism and parameter influence of torsional percussive drilling with a single PDC cutter

    Xi, YanWang, WeiZha, ChunqingLi, Jun...
    14页
    查看更多>>摘要：Torsional percussive drilling tool was designed to reduce the risk of stick-slip and improve drilling efficiency, but there are few studies on the influence of torsional impact parameters, including amplitude, frequency, waveform, on the rate of penetration (ROP) while drilling the hard rock. The design of the torsional percussive drilling tool was proposed, and the mathematical model of torsion hammer movement was developed, the Riedel-HiermaierThoma (RHT) rock dynamic material model was applied to analyze the rock-breaking process of the tool. A numerical model of hard rock cutting with a single polycrystalline diamond composite (PDC) bit cutter was established, the influences of amplitude, frequency, time parameters, and waveforms on the penetration depth of the PDC bit cutter were analyzed in the process of torsional percussive drilling. The results showed that the numerical simulation results were in good agreement with the indoor test results, which verified the correctness of the numerical simulation. Compared with conventional drilling, the penetration depth of torsional percussive drilling was increased by 20.0%, and the cutting debris particles were smaller, which was conducive to improving ROP and reducing stick-slip vibration of the bit. With the increase of the peak value of torsional percussive amplitude, the penetration depth of the cutter first increased and then decreased. When the ratio of torsional impact load to axial static load was 1.0, the penetration depth of the drilling cutter reached a maximum. When the torsional impact frequency was 40 Hz-100 Hz, the penetration depth decreased with the increase of the frequency, but the diameter of cuttings became smaller and smaller, which was conducive to cleaning the wellbore with drilling fluid. The latter has the highest rock-breaking efficiency compared with triangular, sine, and rectangular waves. Finally, suggestions are given on how to adjust these parameters by adjusting engineering parameters and tool structure parameters to optimize the efficiency of the torsional percussive drilling tool.
      原文链接:
    • NSTL
    • Elsevier