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Featured researches published by Juntai Shi.


Transport in Porous Media | 2018

A Fractal Model for Gas–Water Relative Permeability in Inorganic Shale with Nanoscale Pores

Tao Zhang; Xiangfang Li; Jing Li; Dong Feng; Keliu Wu; Juntai Shi; Zheng Sun; Song Han

A reliable gas–water relative permeability model in shale is extremely important for the accurate numerical simulation of gas–water two-phase flow (e.g., fracturing fluid flowback) in gas-shale reservoirs, which has important implication for the economic development of gas-shale reservoir. A gas–water relative permeability model in inorganic shale with nanoscale pores at laboratory condition and reservoir condition was proposed based on the fractal scaling theory and modified non-slip boundary of continuity equation in the nanotube. The model not only considers the gas slippage in the entire Knudsen regime, multilayer sticking (near-wall high-viscosity water) and the quantified thickness of water film, but also combines the real gas effect and stress dependence effect. The presented model has been validated by various experiments data of sandstone with microscale pores and bulk shale with nanoscale pores. The results show that: (1) The Knudsen diffusion and slippage effects enhance the gas relative permeability dramatically; however, it is not obviously affected at high pressure. (2) The multilayer sticking effect and water film should not be neglected: the multilayer sticking would reduce the water relative permeability as well as slightly decrease gas relative permeability, and the film flow has a negative impact on both of the gas and water relative permeability. (3) The increased fractal dimension for pore size distribution or tortuosity would increase gas relative permeability but decrease the water relative permeability for a given saturation; however, the effect on relative permeability is not that notable. (4) The real gas effect is beneficial for the gas relative permeability, and the influence is considerable when the pressure is high enough and when the nanopores of bulk shale are mostly with smaller size. For the stress dependence, not like the intrinsic permeability, none of the gas or water relative permeability is sensitive to the net pressure and it can be ignored completely.


Petroleum Science and Technology | 2013

Deliverability Prediction of Gas Condensate Wells Based on Statistics

Juntai Shi; Xiang Fang Li; J. Zhou; Q. Li; K. Wu

The deliverability of gas condensate well can be calculated by using the modified deliverability equation of dry gas well and the pseudopressure deliverability equation. The modified deliverability equation of dry gas well, without considering the effect of condensate accumulation on the gas flow, results in a relatively large error; the practical application of the pseudopressure deliverability equation is not widespread because of the complex in calculating process of the pseudopressure function. The gas relative permeability and pressure is correlated based on the statistics of gas condensate wells, and an accurate and convenient deliverability equation of gas condensate well is derived. The results of case studies verify that the deliverability equation of gas condensate wells proposed is more appropriate to predict the production of the gas condensate wells.


Petroleum Science | 2018

Optimization of shale gas reservoir evaluation and assessment of shale gas resources in the Oriente Basin in Ecuador

Hong Zhang; Juntai Shi; Xiangfang Li

The petroleum geological features of hydrocarbon source rocks in the Oriente Basin in Ecuador are studied in detail to determine the potential of shale gas resources in the basin. The favorable shale gas layer in the vertical direction is optimized by combining logging identification and comprehensive geological analysis. The thickness in this layer is obtained by logging interpretation in the basin. The favorable shale gas accumulation area is selected by referring to thickness and depth data. Furthermore, the shale gas resource amount of the layer in the favorable area is calculated using the analogy method. Results show that among the five potential hydrocarbon source rocks, the lower Napo Formation is the most likely shale gas layer. The west and northwest zones, which are in the deep-sea slope and shelf sedimentary environments, respectively, are the favorable areas for shale gas accumulation. The favorable sedimentary environment formed thick black shale that is rich in organic matter. The black shale generated hydrocarbon, which migrated laterally to the eastern shallow water shelf to form numerous oil fields. The result of the shale gas resource in the two favorable areas, as calculated by the analogy method, is 55,500 × 108 m3. This finding shows the high exploration and development potential of shale gas in the basin.


International Journal of Coal Geology | 2016

Water distribution characteristic and effect on methane adsorption capacity in shale clay

Jing Li; Xiangfang Li; Xiangzeng Wang; Yingying Li; Keliu Wu; Juntai Shi; Liu Yang; Dong Feng; Tao Zhang; Pengliang Yu


SPE Unconventional Resources Conference Canada | 2013

Diffusion and Flow Mechanisms of Shale Gas through Matrix Pores and Gas Production Forecasting

Juntai Shi; Lei Zhang; Yuansheng Li; Wei Yu; Xiangnan He; Ning Liu; Xiangfang Li; Tao Wang


International Journal of Heat and Mass Transfer | 2017

Apparent permeability model for real gas transport through shale gas reservoirs considering water distribution characteristic

Zheng Sun; Xiangfang Li; Juntai Shi; Tao Zhang; Fengrui Sun


Fuel | 2017

A semi-analytical model for drainage and desorption area expansion during coal-bed methane production

Zheng Sun; Xiangfang Li; Juntai Shi; Pengliang Yu; Liang Huang; Jun Xia; Fengrui Sun; Tao Zhang; Dong Feng


Energy & Fuels | 2011

Viscosity Model of Preformed Microgels for Conformance and Mobility Control

Juntai Shi; Abdoljalil Varavei; Chun Huh; Mojdeh Delshad; Kamy Sepehrnoori; Xiangfang Li


Energy & Fuels | 2016

Water Sorption and Distribution Characteristics in Clay and Shale: Effect of Surface Force

Jing Li; Xiangfang Li; Keliu Wu; Xiangzeng Wang; Juntai Shi; Liu Yang; Hong Zhang; Zheng Sun; Rui Wang; Dong Feng


Energy & Fuels | 2011

Transport Model Implementation and Simulation of Microgel Processes for Conformance and Mobility Control Purposes

Juntai Shi; Abdoljalil Varavei; Chun Huh; Mojdeh Delshad; Kamy Sepehrnoori; Xiangfang Li

Collaboration


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Xiangfang Li

China University of Petroleum

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Zheng Sun

China University of Petroleum

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Tao Zhang

China University of Petroleum

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Dong Feng

China University of Petroleum

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Keliu Wu

University of Calgary

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Jing Li

China University of Petroleum

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Yanan Miao

China University of Petroleum

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Fengrui Sun

China University of Petroleum

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K. Wu

China University of Petroleum

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Shan Wang

China University of Petroleum

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