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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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    Effects of shale swelling and water-blocking on shale permeability

    Lyu, QiaoShi, JindongTan, JingqiangDick, Jeffrey M....
    12页
    查看更多>>摘要：In the process of producing shale gas by fracturing, a large amount of water enters shale due to shale imbibition, which affects the shale permeability because of the positive effect by cracks caused by shale swelling and the negative effect by water-blocking. However, there is still a lack of quantitative description of these two effects. In this paper, permeability tests were conducted on shale samples before and after deionized water/NaCl solution imbibition. The results show that, compared with deionized water imbibition, the decrease of shale permeability after NaCl solution imbibition is stronger and more complex because of the NaCl crystals. The permeability of shale after NaCl solution imbibition is only 0.06 times of that before imbibition, while imbibition of deionized water reduces the permeability to 0.15 times of the starting value. In deionized water imbibition, the shale swelling effect causes the increase of permeability by 2.78 times, while the water-blocking effect causes an average permeability loss as high as 99.0%. Shale swelling and water-blocking effects increase the sensitivity of shale permeability to pore pressure by 1.46 times and 1.05 times respectively. NaCl crystals can also increase the sensitivity of shale permeability to pore pressure. Except for the complex influence of NaCl solution and the influence of NaCl crystals on permeability, the relationship between permeability and true effective stress can be closely fitted with an exponential function. This study is helpful to understand the effects of water and saline solution on the permeability of shale gas reservoirs in the process of hydraulic fracturing.
      原文链接:
    • NSTL
    • Elsevier

    Effect of solvent on the adsorption behavior of asphaltene on silica surface: A molecular dynamic simulation study

    Lu, NingDong, XiaohuChen, ZhangxinLiu, Huiqing...
    17页
    查看更多>>摘要：In recent years, the hybrid thermal-solvent process has been widely applied to improve the recovery performance of steam injection processes in heavy oil reservoirs. In this paper, the method of Molecular Dynamics (MD) simulation is employed to illuminate the asphaltenes adsorption behavior in the thermal-solvent recovery process. Three different solvent molecules (CO2, C3H8, and nC(4)H(10)) and SARA (Saturates, Aromatics, Resins, Asphaltenes) simulated heavy oil model are constructed as the basic simulation model. A series of MD simulations at different temperature conditions are performed. Results show that for the SARA model, the asphaltene molecules can interact with the silica by a T-shape stacking, finally forming the asphaltene dense aggregates as a basic heavy oil occurrence state. The steric hindrance effect of other SARA components can also contribute to this configuration. Temperature significantly affects the adsorption configuration of asphaltenes by disassembling the dense core and loosening the structure of the aggregates. For the SARA model in three solvent atmospheres, the increasing temperature can benefit the extraction of light components. CO2 can only extract saturates, while nC(4)H(10) and C3H8 can simultaneously extract the saturates and aromatics. Besides, asphaltenes re-precipitation behavior can be observed in the 393 K CO2 atmosphere. Both nC(4)H(10) and C3H8 have mutual solubility with the heavy oil system. No apparent precipitation of asphaltenes occurs in the above two atmospheres. Comparing the performance of extraction capability and diffusion capability in all MD simulations, the nC(4)H(10) can both extract light oil components and control the asphaltenes precipitation. It further reveals that nC(4)H(10) can recover heavy oil more efficiently at a microcosm level. Among the three different solvents, nC(4)H(10) is the optimal solvent for hybrid thermal-solvent processes in heavy oil reservoirs.
      原文链接:
    • NSTL
    • Elsevier

    Petroleum viscosity modeling using least squares and ANN methods

    Stratiev, DichoNenov, SvetoslavSotirov, SotirShishkova, Ivelina...
    10页
    查看更多>>摘要：274 crude oils pertaining to the groups of extra light (gas condensates), light, medium, heavy, and extra heavy crude oils were characterized by true boiling point distillation, specific gravity and kinematic viscosity at 21.11 and 37.78 degrees C. Eight published regression empirical methods were examined for their capability of accurately predicting the crude oil viscosity. Among them the model of Kotzakoulakis and George was found to provide the lowest average absolute relative error (AARE) of 24.0% with AARE of 21.5% for the crude oils containing < 30 wt % vacuum residue (VR) and AARE of 37.2% for the crude oils having > 30 wt% VR. The model of Aboul-Seoud and Moharam exhibited the lowest AARE (16.3%) for the crude oils with < 30 wt% VR. A new nonlinear regression model was developed that predicted the viscosity of the 274 crude oils with AARE of 19.5%, with AARE of 14.9% for the crude oils containing < 30 wt% VR, and AARE of 42.0% for the crude oils having > 30 wt% VR. Another model based on the artificial neural network (ANN) technique was developed. The ANN model predicted the viscosity of the 274 crude oils with AARE of 44.3%, with AARE of 50.2% for the crude oils with < 30 wt% VR, and AARE of 13.9% for the crude oils containing > 30 wt% VR. The combination of predicting the viscosity of crude oils having < 30 wt% VR by the new nonlinear regression model with the predicting of viscosity of crude oils with > 30 wt% VR by the ANN model provides of AARE of 14.9% of viscosity prediction for the entire data base of 274 crude oils.
      原文链接:
    • NSTL
    • Elsevier

    Tar mitigation using insitu heat generation chemicals (part I): A comparative study

    Alade, Olalekan S.Mahmoud, M.Al Shehri, D. A.Patil, S....
    9页
    查看更多>>摘要：Tar is an extra-heavy oil with ultra-high viscosity. Accumulation of tar in a reservoir ultimately results in production decline. This study represents the first part of the series of investigation, which aim at developing an insitu heat generation scheme (through thermochemical reaction) for tar mitigation to improve oil production from tarmat-impacted reservoir. Comparative studies have been conducted through both coreflooding experiments and field scale numerical simulation for tar removal using injection of thermochemical fluids (TCF) at 90 degrees C and other fluids, including water (23 degrees C), hot water (90 degrees C), oil soluble organic solvent sludge (90 degrees C) and steam (210 degrees C). The results from coreflooding experiments revealed that TCF injection has comparable removal efficiency in terms of recovery factor (RF = 93%), with that of steam injection (RF = 94%). In comparison, the RF from water, hot water, and injection of an oil-soluble solvent sludge are 21, 53, and 85%, respectively. From the field scale simulation, the results affirmed greater efficiency of TCF injection over steam injection with higher tar recovery rate, recovery factor (RF), and Oil: Steam ratio (OSR). In addition, the simulation results revealed that cyclic injection of TCF outperformed continuous injection operation.
      原文链接:
    • NSTL
    • Elsevier

    Optimum geological storage depths for structural H(2 )geo-storage

    Iglauer, Stefan
    4页
    查看更多>>摘要：H(2 )geo-storage has been suggested as a key technology with which large quantities of H(2 )can be stored and withdrawn again rapidly. One option which is currently explored is H(2 )storage in sedimentary geologic for-mations which are geographically widespread and potentially provide large storage space. The mechanism which keeps the buoyant H(2 )in the subsurface is structural trapping where a caprock prevents the H(2 )from rising by capillary forces. It is therefore important to assess how much H(2 )can be stored via structural trapping under given geo-thermal conditions. This structural trapping capacity is thus assessed here, and it is demonstrated that an optimum storage depth for H(2 )exists at a depth of 1100 m, at which a maximum amount of H(2 )can be stored. This work therefore aids in the industrial-scale implementation of a hydrogen economy.
      原文链接:
    • NSTL
    • Elsevier

    Modeling carbonation and chloride ingress in well cements

    Liu, JinliangJing, YuxiangLi, Linfei
    11页
    查看更多>>摘要：The long-term durability of the wellbore system has become an important topic in recent decades. Specifically in a CO2 underground storage system, both the ingress of chloride and the leaking of carbon dioxide (CO2) can lead to severe degradation of the system, including corrosion of steel casing, and carbonation of the cement annulus. In this paper, a model was developed to consider the coupling effect of the carbonation reaction and chloride diffusion in well cement. The stoichiometric model was first applied to calculate the chemical compositions change of the well cement during the hydration process and the carbonation process. The chloride diffusion coefficient of carbonated well cement was calculated based on the general self-consistent (GSC) model and pore tortuosity. After that, the concentration of free chloride ions was predicted based on Fick's law, which takes into consideration released bonded chloride in the carbonated cement. The proposed model was validated based on available experimental data, and a comparison was made between the proposed model and other previously published models. The model has great significance for the safe and reliable geological storage of CO2. As described in this paper, the model can be used to predict the durability of a CO(2 )wellbore system and to inform the design of future systems.
      原文链接:
    • NSTL
    • Elsevier

    Underground hydrogen storage in a partially depleted gas condensate reservoir: Influence of cushion gas

    Zamehrian, MohammadSedaee, Behnam
    10页
    查看更多>>摘要：Hydrogen gas as a clean and renewable kind of energy can be considered to supply electricity demand during peak usage times. Actually, excess electricity cannot be stored in great quantities, but it can be converted to hydrogen, which can be stored and converted to electricity as a peak shaving. However, due to the very low hydrogen energy density in terms of volume, a huge capacity is needed for its storage. Therefore, underground hydrogen storage (UHS) can be evaluated as a solution. This study investigated the effect of cushion gas on underground hydrogen storage in a partially depleted gas condensate reservoir in a real case which is located in the Middle east. To the best of our knowledge, it is the first time the feasibility of underground hydrogen storage in a gas condensate reservoir has been investigated. The effect of some parameters such as cushion gas type, namely; methane, nitrogen, carbon dioxide, condensate existence, the implementation time of storage, hydrogen injection initialization stage, and hydrogen injection/production rate was investigated on hydrogen heating value and recovery during the underground hydrogen storage operation. The results of replacing alternative gases as part of cushion gas showed that the highest amount of hydrogen recovery and purity could be obtained by injecting the nitrogen. While carbon dioxide was the most effective alternative gas to improve condensate production but in terms of hydrogen recovery and purity was not. Also, implementing hydrogen storage in the gas condensate reservoir leads to higher hydrogen recovery than dry gas reservoirs due to the trapping of alternative gases in the condensate phase. However, most of the injected carbon dioxide was produced during hydrogen production, which is unfavorable. This study shows that 60% depletion of the gas condensate reservoir is the best condition to start underground hydrogen storage. Further, applying a hydrogen injection initialization stage indicated that the hydrogen recovery and heating value could be increased. However, it requires a detailed economic evaluation to consider the cost/benefit of initialized hydrogen loss and recovery.
      原文链接:
    • NSTL
    • Elsevier

    Evaluation of hydraulic fracturing effect on coalbed methane reservoir based on deep learning method considering physical constraints

    Du, ShuyiYang, JiaoshengZhao, YangYu, Mingxu...
    15页
    查看更多>>摘要：Data-driven deep learning algorithms have shown good performance in the field of petroleum industry. However, some research has begun to be keen to incorporate physical laws into machine learning algorithms, so as to establish a "data + physical laws " dual-drive model, which can more effectively guide deep learning. In this study, reservoir geology, hydraulic fracturing, and dynamic production data were considered to establish a fracturing effect evaluation model for coalbed methane reservoirs. The combined network is designed to fully excavate the characteristics of dynamic and static data and solve the problem that the network ignores static data due to excessive dimensions of dynamic data. Furthermore, a neural network considering physical constraints was developed to better evaluate the fracturing effect by incorporating the initial conditions and expert experiences into the loss function. The deep learning-based fracturing effect evaluation model not only fits data driven methods including reservoir geology, hydraulic fracturing and dynamic production data, but also adheres to the guidance of physical constraints. The experimental results show that compared with the conventional machine learning methods, the fracturing effect evaluation model has better performance on the prediction of crack half-length and permeability after fracturing due to combined network and physical constraints, with the overall RMSE of 6.11 m and 0.533mD respectively. In addition, through the analysis of influencing factors, it can be obtained that reservoir geology and hydraulic fracturing parameters can contribute more than 90% to the prediction of fracture half-length. Moreover, reservoir geology, hydraulic fracturing and dynamic data all play an important role in the permeability after fracturing, among which dynamic data has the highest contribution rate, with more than 40%.
      原文链接:
    • NSTL
    • Elsevier

    Preparation and characterization of super hydrophobic/oleophobic material and its application in releasing liquid locking in tight condensate gas reservoirs

    Tu, HongjunZhou, MingGu, YueGuo, Xiao...
    10页
    查看更多>>摘要：In this paper, a super hydrophobic/oleophobic material CS-1 with super hydrophobic/oleophobic properties was successfully prepared with nano silica as the main raw material and 1H, 1H, 2H, 2H-perfluorooctyl trichlorosilane as modifier. The structures of synthesized product were characterized by the infrared spectroscopy (FTIR). The contact angle of super hydrophobic/oleophobic material CS-1 was measured by contact angle measuring instrument, and its hydrophobic/oleophobic properties were analyzed systematically. The micro morphology of super hydrophobic/oleophobic material CS-1 was determined by scanning electron microscope. The results of wetting properties show that the maximum water phase contact angle of hydrophobic/ oleophobic material CS-1 is 159.58 degrees and the maximum oil phase contact angle is 135.63 degrees. Based on triple action of constructing micro-nanostructure on rock surface, reducing gas-water surface tension and oil-water interfacial tension, the optimized formula of the unlocking agent 1.5 wt% super hydrophobic/oleophobic material CS-1 + 0.06 wt% NFS surfactant +0.09 wt% C3 Gemini surfactant was screened by single factor method. Finally, the performance of unlocking agent is comprehensively evaluated by surface energy spectrometer, laser particle size analyzer, automatic contact angle tester and core unlocking equipment. The results show that the water phase contact angles of the core treated with the unlocking agent are greater than 150 degrees and the oil phase contact angles are greater than 130 degrees in acidic, alkaline and high temperature environments. The maximum recovery rate of water locking damage gas measurement permeability is 91.1%, and the maximum recovery rate of oil locking damage gas measurement permeability is 67.4%. It shows that the unlocking agent can effectively improve the gas logging permeability of the core and change the wettability of the core surface, so as to relieve the liquid locking of the condensate gas reservoir. It has a good application prospect in the middle and late stage of condensate gas reservoir development.
      原文链接:
    • NSTL
    • Elsevier

    X-ray mu Ct extracted pore attributes to predict and understand Sor using ensemble learning techniques in the Barra Velha Pre-salt carbonates, Santos Basin, Offshore Brazil

    Herlinger Jr, RonaldoVidal, Alexandre Campane
    16页
    查看更多>>摘要：The residual oil saturation (Sor) evaluation is relevant for developing oil fields, standing out as an input to flow simulation models for production forecasting. Also, Sor understanding is crucial to guide enhanced oil recovery techniques. Moreover, Sor laboratory measurement tends to be time-consuming and expensive. This work aims to understand and predict Sor from X-ray mu Ct and RCAL data employing Ensemble Learning techniques (AdaBoost, Gradient Boost, and XGBoost) in Pre-salt carbonates of the Barra Velha Formation, Santos Basin. Morphological attributes related to pore size, shape, and orientation were extracted from X-ray mu Ct scans. Hence, these attri-butes, together with routine core analysis (RCAL) data, were used to build machine learning (ML) models for the prediction of Sor. The results indicated strong faciological control in Sor, where the genesis of the rock implies different characteristics of the porous framework, impacting Sor and other petrophysical features. Rocks with larger pores usually lead to larger heterogeneity, which tends to trap more oil. Furthermore, the shape and orientation of the pores have substantial faciological control, given the textural organization of the different rock facies. These attributes showed weak control over Sor, impacting each type of facies differently, depending on the rock fabric. Even though the ML algorithms have similar results, the Gradient Boosting showed the best results. Furthermore, the inclusion of RCAL data does not increase the accuracy of the models. So, it is possible to predict the Sor only with morphological pore attributes reasonably. The most important features are mainly related to pore size and subordinately to orientation, confirming their impact on Sor. Finally, this methodology, in addition to predicting and bringing understanding to Sor in Pre-Salt rocks, can be adapted for use in other reservoirs.
      原文链接:
    • NSTL
    • Elsevier