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An iteration-free approach for determining the average reservoir pressure and original gas in place by production data analysis:Methodology and field cases
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作者 Yang Wang Shilong Yang +2 位作者 Hang Xie Naichao Feng Haiyang Yu 《Natural Gas Industry B》 2025年第3期328-338,共11页
Current gas well decline analysis under boundary-dominated flow(BDF)is largely based on the Arps'empirical hyperbolic decline model and the analytical type curve tools associated with pseudo-functions.Due to the n... Current gas well decline analysis under boundary-dominated flow(BDF)is largely based on the Arps'empirical hyperbolic decline model and the analytical type curve tools associated with pseudo-functions.Due to the nonlinear flow behavior of natural gas,these analysis methods generally require iterative calculations.In this study,the dimensionless gas rate(qg/qgi)is introduced,and an explicit method to determine the average reservoir pressure and the original gas in place(OGIP)for a volumetric gas reservoir is proposed.We show that the dimensionless gas rate in the BDF is only the function of the gas PVT parameters and reservoir pressure.Step-by-step analysis procedures are presented that enable explicit and straightforward estimation of average reservoir pressure and OGIP by straight-line analysis.Compared with current techniques,this methodology avoids the iterative calculation of pseudo-time and pseudo-pressure functions,lowers the multiplicity of type curve analysis,and is applicable in different production situations(constant/variable gas flow rate,constant/variable bottom-hole pressure)with a broad range of applications and ease of use.Reservoir numerical simulation and field examples are thoroughly discussed to highlight the capabilities of the proposed approach. 展开更多
关键词 Gas rate decline Original gas in place average reservoir pressure Explicit calculation Dynamic production analysis
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Estimating Average Reservoir Pressure: A Neural Network Approach with Limited Data
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作者 Saber Elmabrouk Ezeddin Shirit Rene Mayouga 《Journal of Earth Science and Engineering》 2012年第11期663-675,共13页
Insight into average oil pressure in gas reservoirs and changes in production (time), play a critical role in reservoir and production performance, economic evaluation and reservoir management. In all practicality, ... Insight into average oil pressure in gas reservoirs and changes in production (time), play a critical role in reservoir and production performance, economic evaluation and reservoir management. In all practicality, average reservoir pressure can be conducted only when producing wells are shut in. This is regarded as a pressure build-up test. During the test, the wellbore pressure is recorded as a function of time. Currently, the only available method with which to obtain average reservoir pressure is to conduct an extended build-up test. It must then be evaluated using Homer or MDH (Miller, Dyes and Huchinson) valuation procedures. During production, average reservoir pressure declines due to fluid withdrawal from the wells and therefore, the average reservoirpressure is updated, periodically. A significant economic loss occurs during the entire pressure build-up test when producing wells are shut in. In this study, a neural network model has been established to map a nonlinear time-varying relationship which controls reservoir production history in order to predict and interpolate average reservoir pressure without closing the producing wells. This technique is suitable for constant and variable flow rates. 展开更多
关键词 Artificial neural networks average reservoir pressure estimation modeling error analysis.
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Pressure and Temperature Feasibility of NCEP/NCAR Reanalysis Data at Mt.Everest 被引量:1
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作者 XIE Aihong REN Jiawen +1 位作者 QIN Xiang KANG Shikang 《Journal of Mountain Science》 SCIE CSCD 2008年第1期32-37,共6页
Mt.Everest (27°54' N,86°54' E),the highest peak,is often referred to as the earth's 'third' pole,at an elevation of 8844.43 m. Due to the difficult logistics in the extreme high elevation... Mt.Everest (27°54' N,86°54' E),the highest peak,is often referred to as the earth's 'third' pole,at an elevation of 8844.43 m. Due to the difficult logistics in the extreme high elevation regions over the Himalayas,observational meteorological data are very few on Mt. Everest. In 2005,an automatic weather station was operated at the East Rongbuk glacier Col of Mt. Everest over the Himalayas. The observational data have been compared with the reanalysis data from the National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR),and the reliability of NCEP/NCAR reanalysis data has been investigated in the Himalayan region,after the reanalyzed data were interpolated in the horizontal to the location of Mt. Everest and in the vertical to the height of the observed sites. The reanalysis data can capture much of the synoptic-scale variability in temperature and pressure,although the reanalysis values are systematically lower than the observation. Furthermore,most of the variability magnitude is,to some degree,underestimated. In addition,the variation extracted from the NCEP/NCAR reanalyzed pressure and temperature prominently appears one-day lead to that from the observational data,which is more important from the standpoint of improving the safety of climbers who attempt to climb Mt. Everest peak. 展开更多
关键词 NCEP/NCAR daily averaged pressure daily minimum temperature high Himalayas Mt.Everest
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MECHANICS ANALYSIS ON PRECISE FORMING PROCESS OF EXTERNAL SPLINE COLD ROLLING 被引量:18
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作者 ZHANG Dawei LI Yongtang +1 位作者 FU Jianhua ZHENG Quangang 《Chinese Journal of Mechanical Engineering》 SCIE EI CAS CSCD 2007年第3期54-58,共5页
According to the suitable assumption,the deformation process of external spline cold rolling is analyzed.By the graphing method,the slip-line field of plastically deforming area in process of external spline cold roll... According to the suitable assumption,the deformation process of external spline cold rolling is analyzed.By the graphing method,the slip-line field of plastically deforming area in process of external spline cold rolling is set up.Different friction-conditions are used in different contact areas in order to realistically reflect the actual situation.The unit average pressure on contact surface of the rolling process is solved according to the stress filed theory of slip-line.And the formulae of the rolling-force and rolling-moment are established.The theoretical result is well consistent with the finite element analysis.A theoretical basis is provided for the precise forming process of spline cold rolling and the production of external splined shafts. 展开更多
关键词 External spline Cold rolling Slip-line Unit average pressure Rolling-force
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On the ratio of expectation crossings of random-excited dielectric elastomer balloon 被引量:2
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作者 xiaoling Jin Yong Wang Zhilong Huang 《Theoretical & Applied Mechanics Letters》 CAS CSCD 2017年第2期100-104,共5页
The ratio of expectation crossings of dielectric elastomer balloon excited by random pressure is analytically evaluated in this letter.The Mooney-Rivlin model is adopted to describe the constitutive relation while the... The ratio of expectation crossings of dielectric elastomer balloon excited by random pressure is analytically evaluated in this letter.The Mooney-Rivlin model is adopted to describe the constitutive relation while the random pressure is described by Gaussian white noise.Through a specific transformation,the stochastic differential equations for the total energy and phase are derived.With the application of the stochastic averaging,the system total energy is then approximated by a one-dimensional diffusion pro-cess.Solving the associated Fokker-Planck-Kolmogorov(FPK)equation yields the stationary probability density of the system total energy.The ratio of expectation crossings is then derived based on the joint stationary probability density of stretch ratio and its ratio of change.The efficacy and accuracy of the proposed procedure are verified by comparing with the results from Monte Carlo simulation(MCS). 展开更多
关键词 Dielectric elastomer balloon Ratio of expectation crossings Random pressure Stochastic averaging
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