A permeability prediction method based on pore structure and lithofacies
Permeability prediction using linear regression of porosity always has poor performance when the reservoir with complex pore structure and large variation of lithofacies. A new method is proposed to predict permeability by comprehensively considering pore structure, porosity and lithofacies. In this...
Main Authors: | , , , , , , |
---|---|
Format: | Article |
Language: | English |
Published: |
KeAi Communications Co., Ltd.
2019-10-01
|
Series: | Petroleum Exploration and Development |
Online Access: | http://www.sciencedirect.com/science/article/pii/S1876380419602508 |
_version_ | 1818670971779809280 |
---|---|
author | Lideng GAN Yaojun WANG Xianzhe LUO Ming ZHANG Xianbin LI Xiaofeng DAI Hao YANG |
author_facet | Lideng GAN Yaojun WANG Xianzhe LUO Ming ZHANG Xianbin LI Xiaofeng DAI Hao YANG |
author_sort | Lideng GAN |
collection | DOAJ |
description | Permeability prediction using linear regression of porosity always has poor performance when the reservoir with complex pore structure and large variation of lithofacies. A new method is proposed to predict permeability by comprehensively considering pore structure, porosity and lithofacies. In this method, firstly, the lithofacies classification is carried out using the elastic parameters, porosity and shear frame flexibility factor. Then, for each lithofacies, the elastic parameters, porosity and shear frame flexibility factor are used to obtain permeability from regression. The permeability prediction test by logging data of the study area shows that the shear frame flexibility factor that characterizes the pore structure is more sensitive to permeability than the conventional elastic parameters, so it can predict permeability more accurately. In addition, the permeability prediction is depending on the precision of lithofacies classification, reliable lithofacies classification is the precondition of permeability prediction. The field data application verifies that the proposed permeability prediction method based on pore structure parameters and lithofacies is accurate and effective. This approach provides an effective tool for permeability prediction. Key words: seismic reservoir prediction, pore structure, permeability, lithofacies, shear frame flexibility factor, boosting learning |
first_indexed | 2024-12-17T07:16:35Z |
format | Article |
id | doaj.art-e6f54797f90c4a18b9c2508593088a37 |
institution | Directory Open Access Journal |
issn | 1876-3804 |
language | English |
last_indexed | 2024-12-17T07:16:35Z |
publishDate | 2019-10-01 |
publisher | KeAi Communications Co., Ltd. |
record_format | Article |
series | Petroleum Exploration and Development |
spelling | doaj.art-e6f54797f90c4a18b9c2508593088a372022-12-21T21:58:53ZengKeAi Communications Co., Ltd.Petroleum Exploration and Development1876-38042019-10-01465935942A permeability prediction method based on pore structure and lithofaciesLideng GAN0Yaojun WANG1Xianzhe LUO2Ming ZHANG3Xianbin LI4Xiaofeng DAI5Hao YANG6Research Institute of Petroleum Exploration & Development, PetroChina, Beijing 100083, China; Corresponding authorUniversity of Electronic Science and Technology of China, Chengdu 611731, ChinaUniversity of Electronic Science and Technology of China, Chengdu 611731, ChinaResearch Institute of Petroleum Exploration & Development, PetroChina, Beijing 100083, ChinaResearch Institute of Petroleum Exploration & Development, PetroChina, Beijing 100083, ChinaResearch Institute of Petroleum Exploration & Development, PetroChina, Beijing 100083, ChinaResearch Institute of Petroleum Exploration & Development, PetroChina, Beijing 100083, ChinaPermeability prediction using linear regression of porosity always has poor performance when the reservoir with complex pore structure and large variation of lithofacies. A new method is proposed to predict permeability by comprehensively considering pore structure, porosity and lithofacies. In this method, firstly, the lithofacies classification is carried out using the elastic parameters, porosity and shear frame flexibility factor. Then, for each lithofacies, the elastic parameters, porosity and shear frame flexibility factor are used to obtain permeability from regression. The permeability prediction test by logging data of the study area shows that the shear frame flexibility factor that characterizes the pore structure is more sensitive to permeability than the conventional elastic parameters, so it can predict permeability more accurately. In addition, the permeability prediction is depending on the precision of lithofacies classification, reliable lithofacies classification is the precondition of permeability prediction. The field data application verifies that the proposed permeability prediction method based on pore structure parameters and lithofacies is accurate and effective. This approach provides an effective tool for permeability prediction. Key words: seismic reservoir prediction, pore structure, permeability, lithofacies, shear frame flexibility factor, boosting learninghttp://www.sciencedirect.com/science/article/pii/S1876380419602508 |
spellingShingle | Lideng GAN Yaojun WANG Xianzhe LUO Ming ZHANG Xianbin LI Xiaofeng DAI Hao YANG A permeability prediction method based on pore structure and lithofacies Petroleum Exploration and Development |
title | A permeability prediction method based on pore structure and lithofacies |
title_full | A permeability prediction method based on pore structure and lithofacies |
title_fullStr | A permeability prediction method based on pore structure and lithofacies |
title_full_unstemmed | A permeability prediction method based on pore structure and lithofacies |
title_short | A permeability prediction method based on pore structure and lithofacies |
title_sort | permeability prediction method based on pore structure and lithofacies |
url | http://www.sciencedirect.com/science/article/pii/S1876380419602508 |
work_keys_str_mv | AT lidenggan apermeabilitypredictionmethodbasedonporestructureandlithofacies AT yaojunwang apermeabilitypredictionmethodbasedonporestructureandlithofacies AT xianzheluo apermeabilitypredictionmethodbasedonporestructureandlithofacies AT mingzhang apermeabilitypredictionmethodbasedonporestructureandlithofacies AT xianbinli apermeabilitypredictionmethodbasedonporestructureandlithofacies AT xiaofengdai apermeabilitypredictionmethodbasedonporestructureandlithofacies AT haoyang apermeabilitypredictionmethodbasedonporestructureandlithofacies AT lidenggan permeabilitypredictionmethodbasedonporestructureandlithofacies AT yaojunwang permeabilitypredictionmethodbasedonporestructureandlithofacies AT xianzheluo permeabilitypredictionmethodbasedonporestructureandlithofacies AT mingzhang permeabilitypredictionmethodbasedonporestructureandlithofacies AT xianbinli permeabilitypredictionmethodbasedonporestructureandlithofacies AT xiaofengdai permeabilitypredictionmethodbasedonporestructureandlithofacies AT haoyang permeabilitypredictionmethodbasedonporestructureandlithofacies |