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Frequencies of Lock Gate Structure Coupled with reservoir fluid

Sound & Vibration 2020年第3期54卷 179-200页

作者： Priyaranjan Pal Motilal Nehru National Institute of Technology Allahabad Prayagraj211004India

This study determines the natural frequencies of the lock gate structure,considering the coupled effect of reservoir fluid on one side using the finite element method(FEM).The gate is assumed to be a uniformly thick plate,and its material is isotropic,homogeneous,and *** reservoir fluid is assumed to be inviscid and incompressible in an irrotational flow *** length of the reservoir domain is truncated using the far boundary condition by adopting the Fourier series expansion *** different assumptions on the free surface,i.e.,undisturbed and linearized,are considered in the fluid domain *** computer code is written based on the developed finite element *** natural frequencies of the lock gate are computed when interacting with and without reservoir *** numerical problems are studied considering the effects of boundary conditions,aspect ratios,and varying dimensions of the gate and the fluid *** frequencies of gate reduce significantly due to the presence of *** frequencies increase when the fluid extends to either side of the *** frequencies reduce when the depth of the fluid domain above the top edge of the gate *** frequencies drop considerably when the free surface condition is taken into *** results of frequencies of lock gate structure may be useful to the designer if it is experienced in natural catastrophes.

关键词： Lock gate reservoir fluid fluid-structure interaction frequency HSDT FEM

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Calculation and application of partition coefficients of light hydrocarbons in oil-based mud system

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Petroleum Exploration and Development 2022年第4期49卷 906-918页

作者： BEN ABDALLAH Bacem Rabie AHMADI Riadh LYNEN Frederic REKHISS Farhat Laboratoire LR3E.Ecole Nationale d’Ingénieurs de Sfax Rte Soukra km 3SfaxTunisia Separation Science Group Department of Organic and Macromolecular ChemistryGhent UniversityKrijgslaan 281-S4B-9000 GhentBelgium

To find out the relationship between the oil-based mud,the formation fluid and the extracted gas,we use a thermodynamic approach based on static headspace gas chromatography technique to calculate the partition coefficients of 47 kinds of light hydrocarbons compounds between nC5 and nC8 in two kinds of oil-based mud-air systems,and reconstruct the original formation fluid composition under thermodynamic *** oil-based drilling mud has little effect on the formation fluid compositions in the range of nC5-nC8(less than 1%for low-toxicity oil-based mud and less than 10%for oil-based mud).For most light hydrocarbon compositions,the partition coefficients obtained by vapor phase calibration and the direct quantitative methods have errors of less than 10%,and the partition coefficients obtained by direct quantitative method are more *** reconstructed compositions of the two kinds of crude oil have match degrees of 91%and 89%with their real compositions,proving the feasibility and accuracy of reconstructing the composition of original formation fluid by using partition coefficients of light hydrocarbon compositions between nC5 and nC8.

关键词： oil-based mud drilling mud gas light hydrocarbon compositions partition coefficients reservoir fluid

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Toward connectionist model for predicting bubble point pressure of crude oils: Application of artificial intelligence

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Petroleum 2015年第4期1卷 307-317页

作者： Mohammad Ali Ahmadi Maysam Pournik Seyed Reza Shadizadeh Department of Petroleum Engineering Ahwaz Faculty of Petroleum EngineeringPetroleum University of TechnologyAhwazIran Department of Petroleum Engineering Mewbourne School of Petroleum&Geological EngineeringUniversity of OklahomaOKUnited States Department of Petroleum Engineering Abadan Faculty of Petroleum EngineeringPetroleum University of TechnologyAbadanIran

Knowledge about reservoir fluid properties such as bubble point pressure(Pb)plays a vital role in improving reliability of oil reservoir *** this work,hybrid of swarm intelligence and artificial neural network(ANN)as a robust and effective method was executed to determine the Pb of crude oil *** addition,the exactly precise Pb data samples reported in the literatures were employed to create and validate the PSO-ANN *** prove and depict the reliability of the smart model developed in this study for estimating Pb of crude oils,the conventional approaches were applied on the same data *** on the results generated by PSO-ANN model and other conventional methods and equation of states(EOS),the PSO-ANN model is a reliable and accurate approach for estimating Pb of crude *** is certified by high value of correlation coefficient(R2)and insignificant value of average absolute relative deviation(AARD%)which are obtained from PSO-ANN *** of this study could help reservoir engineers to have better understanding of reservoir fluid behavior in absence of reliable and experimental data samples.

关键词： Bubble point pressure Swarm intelligence Crude oil Artificial intelligence reservoir fluid

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