Permeability evaluation on oil-window shale based on hydraulic flow unit: A new approach

Permeability is one of the most important petrophysical properties of shale reservoirs, controlling the fluid flow from the shale matrix to artificial fracture networks, the production and ultimate recovery of shale oil/gas. Various methods have been used to measure this parameter in shales, but no...

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Main Authors: Pengfei Zhang, Shuangfang Lu, Junqian Li, Jie Zhang, Haitao Xue, Chen Chen
Format: Article
Language:English
Published: Yandy Scientific Press 2018-01-01
Series:Advances in Geo-Energy Research
Subjects:
Online Access:http://www.astp-agr.com/index.php/Index/Index/detail?id=44
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spelling doaj-18ef8bb2acaf49ff8788caadb0dab9582020-11-25T03:49:14ZengYandy Scientific PressAdvances in Geo-Energy Research2208-598X2208-598X2018-01-012111310.26804/ager.2018.01.01Permeability evaluation on oil-window shale based on hydraulic flow unit: A new approachPengfei Zhang0Shuangfang Lu1Junqian Li2Jie Zhang3Haitao Xue4Chen Chen5Research Institute of Unconventional Oil & Gas and Renewable Energy, China University of Petroleum (East China), Qingdao 266580, P. R. China; School of Geosciences, China University of Petroleum (East China), Qingdao 266580, P. R. ChinaResearch Institute of Unconventional Oil & Gas and Renewable Energy, China University of Petroleum (East China), Qingdao 266580, P. R. ChinaResearch Institute of Unconventional Oil & Gas and Renewable Energy, China University of Petroleum (East China), Qingdao 266580, P. R. ChinaResearch Institute of Unconventional Oil & Gas and Renewable Energy, China University of Petroleum (East China), Qingdao 266580, P. R. China; School of Geosciences, China University of Petroleum (East China), Qingdao 266580, P. R. ChinaResearch Institute of Unconventional Oil & Gas and Renewable Energy, China University of Petroleum (East China), Qingdao 266580, P. R. ChinaResearch Institute of Unconventional Oil & Gas and Renewable Energy, China University of Petroleum (East China), Qingdao 266580, P. R. China; School of Geosciences, China University of Petroleum (East China), Qingdao 266580, P. R. ChinaPermeability is one of the most important petrophysical properties of shale reservoirs, controlling the fluid flow from the shale matrix to artificial fracture networks, the production and ultimate recovery of shale oil/gas. Various methods have been used to measure this parameter in shales, but no method effectively estimates the permeability of all well intervals due to the complex and heterogeneous pore throat structure of shale. A hydraulic flow unit (HFU) is a correlatable and mappable zone within a reservoir, which is used to subdivide a reservoir into distinct layers based on hydraulic flow properties. From these units, correlations between permeability and porosity can be established. In this study, HFUs were identified and combined with a back propagation neural network to predict the permeability of shale reservoirs in the Dongying Depression, Bohai Bay Basin, China. Well data from three locations were used and subdivided into modeling and validation datasets. The modeling dataset was applied to identify HFUs in the study reservoirs and to train the back propagation neural network models to predict values of porosity and flow zone indicator (FZI). Next, a permeability prediction method was established, and its generalization capability was evaluated using the validation dataset. The results identified five HFUs in the shale reservoirs within the Dongying Depression. The correlation between porosity and permeability in each HFU is generally greater than the correlation between the two same variables in the overall core data. The permeability estimation method established in this study effectively and accurately predicts the permeability of shale reservoirs in both cored and un-cored wells. Predicted permeability curves effectively reveal favorable shale oil/gas seepage layers and thus are useful for the exploration and the development of hydrocarbon resources in the Dongying Depression.http://www.astp-agr.com/index.php/Index/Index/detail?id=44Permeabilityporosityshalehydraulic flow unitsback propagation neural network
collection DOAJ
language English
format Article
sources DOAJ
author Pengfei Zhang
Shuangfang Lu
Junqian Li
Jie Zhang
Haitao Xue
Chen Chen
spellingShingle Pengfei Zhang
Shuangfang Lu
Junqian Li
Jie Zhang
Haitao Xue
Chen Chen
Permeability evaluation on oil-window shale based on hydraulic flow unit: A new approach
Advances in Geo-Energy Research
Permeability
porosity
shale
hydraulic flow units
back propagation neural network
author_facet Pengfei Zhang
Shuangfang Lu
Junqian Li
Jie Zhang
Haitao Xue
Chen Chen
author_sort Pengfei Zhang
title Permeability evaluation on oil-window shale based on hydraulic flow unit: A new approach
title_short Permeability evaluation on oil-window shale based on hydraulic flow unit: A new approach
title_full Permeability evaluation on oil-window shale based on hydraulic flow unit: A new approach
title_fullStr Permeability evaluation on oil-window shale based on hydraulic flow unit: A new approach
title_full_unstemmed Permeability evaluation on oil-window shale based on hydraulic flow unit: A new approach
title_sort permeability evaluation on oil-window shale based on hydraulic flow unit: a new approach
publisher Yandy Scientific Press
series Advances in Geo-Energy Research
issn 2208-598X
2208-598X
publishDate 2018-01-01
description Permeability is one of the most important petrophysical properties of shale reservoirs, controlling the fluid flow from the shale matrix to artificial fracture networks, the production and ultimate recovery of shale oil/gas. Various methods have been used to measure this parameter in shales, but no method effectively estimates the permeability of all well intervals due to the complex and heterogeneous pore throat structure of shale. A hydraulic flow unit (HFU) is a correlatable and mappable zone within a reservoir, which is used to subdivide a reservoir into distinct layers based on hydraulic flow properties. From these units, correlations between permeability and porosity can be established. In this study, HFUs were identified and combined with a back propagation neural network to predict the permeability of shale reservoirs in the Dongying Depression, Bohai Bay Basin, China. Well data from three locations were used and subdivided into modeling and validation datasets. The modeling dataset was applied to identify HFUs in the study reservoirs and to train the back propagation neural network models to predict values of porosity and flow zone indicator (FZI). Next, a permeability prediction method was established, and its generalization capability was evaluated using the validation dataset. The results identified five HFUs in the shale reservoirs within the Dongying Depression. The correlation between porosity and permeability in each HFU is generally greater than the correlation between the two same variables in the overall core data. The permeability estimation method established in this study effectively and accurately predicts the permeability of shale reservoirs in both cored and un-cored wells. Predicted permeability curves effectively reveal favorable shale oil/gas seepage layers and thus are useful for the exploration and the development of hydrocarbon resources in the Dongying Depression.
topic Permeability
porosity
shale
hydraulic flow units
back propagation neural network
url http://www.astp-agr.com/index.php/Index/Index/detail?id=44
work_keys_str_mv AT pengfeizhang permeabilityevaluationonoilwindowshalebasedonhydraulicflowunitanewapproach
AT shuangfanglu permeabilityevaluationonoilwindowshalebasedonhydraulicflowunitanewapproach
AT junqianli permeabilityevaluationonoilwindowshalebasedonhydraulicflowunitanewapproach
AT jiezhang permeabilityevaluationonoilwindowshalebasedonhydraulicflowunitanewapproach
AT haitaoxue permeabilityevaluationonoilwindowshalebasedonhydraulicflowunitanewapproach
AT chenchen permeabilityevaluationonoilwindowshalebasedonhydraulicflowunitanewapproach
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