Prediction of petroleum resource abundance based on artificial neural network method: a case study of third member of Paleogene Shahejie Formation in Wenliu area of Dongpu Sag, Bohai Bay Basin

YANG Zijie; CHEN Dongxia; WANG Qiaochu; WANG Fuwei; LI Sha; TIAN Ziye; CHEN Shumin; ZHANG Wanrong; YAO Dongsheng; WANG Yuchao

doi:10.11781/sysydz202402428

Volume 46 Issue 2

Mar. 2024

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Article Navigation > PETROLEUM GEOLOGY & EXPERIMENT > 2024 > 46(2): 428-440

YANG Zijie, CHEN Dongxia, WANG Qiaochu, WANG Fuwei, LI Sha, TIAN Ziye, CHEN Shumin, ZHANG Wanrong, YAO Dongsheng, WANG Yuchao. Prediction of petroleum resource abundance based on artificial neural network method: a case study of third member of Paleogene Shahejie Formation in Wenliu area of Dongpu Sag, Bohai Bay Basin[J]. PETROLEUM GEOLOGY & EXPERIMENT, 2024, 46(2): 428-440. doi: 10.11781/sysydz202402428

Citation:

YANG Zijie, CHEN Dongxia, WANG Qiaochu, WANG Fuwei, LI Sha, TIAN Ziye, CHEN Shumin, ZHANG Wanrong, YAO Dongsheng, WANG Yuchao. Prediction of petroleum resource abundance based on artificial neural network method: a case study of third member of Paleogene Shahejie Formation in Wenliu area of Dongpu Sag, Bohai Bay Basin[J]. PETROLEUM GEOLOGY & EXPERIMENT, 2024, 46(2): 428-440. doi: 10.11781/sysydz202402428

Citation:

YANG Zijie, CHEN Dongxia, WANG Qiaochu, WANG Fuwei, LI Sha, TIAN Ziye, CHEN Shumin, ZHANG Wanrong, YAO Dongsheng, WANG Yuchao. Prediction of petroleum resource abundance based on artificial neural network method: a case study of third member of Paleogene Shahejie Formation in Wenliu area of Dongpu Sag, Bohai Bay Basin[J]. PETROLEUM GEOLOGY & EXPERIMENT, 2024, 46(2): 428-440. doi: 10.11781/sysydz202402428

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Prediction of petroleum resource abundance based on artificial neural network method: a case study of third member of Paleogene Shahejie Formation in Wenliu area of Dongpu Sag, Bohai Bay Basin

doi: 10.11781/sysydz202402428

YANG Zijie^{1, 2
,},
CHEN Dongxia^{1, 2
,
,},
WANG Qiaochu^{1, 2},
WANG Fuwei^{1, 2},
LI Sha^{1, 2},
TIAN Ziye^{1, 2},
CHEN Shumin^{1, 2},
ZHANG Wanrong^{1, 2},
YAO Dongsheng^{1, 2},
WANG Yuchao^{1, 2}

1.
College of Geosciences, China University of Petroleum(Beijing), Beijing 102249, China
2.
National Key Laboratory of Petroleum Resources and Engineering, China University of Petroleum(Beijing), Beijing 102249, China

Received Date: 2023-04-26
Rev Recd Date: 2024-02-06
Publish Date: 2024-03-28

Abstract

Abstract

The abundance of petroleum resource is influenced by various factors and involves complex parameters and extensive data. Consequently, traditional geostatistical methods often lack precision in quantitative prediction. To address this issue, this study focuses on the third member of Paleogene Shahejie Formation (member Es³) in the Wenliu area of the Dongpu Sag and utilizes a multi-layer perceptron neural network (MLP) for predicting petroleum resource abundance and employed the Boosting ensemble learning algorithm to optimize the prediction model. The MLP and MLP-Boosting algorithm models were test on 66 sample groups, yielding correlation coefficients of 0.789 and 0.989 for the training set, 0.618 and 0.825 for the validation set and 0.689 and 0.845 for the test set. The analysis identified effective thickness, average permeability and effective porosity are the most significant geological factors influencing petroleum resource abundance, with importance coefficients of 33.93%, 20.12% and 19.53%, respectively. Other factors such as trap area, surface crude oil density and sedimentary facies assignment were found to be less influential. Overall, the Boosting ensemble learning algorithm significantly enhanced the prediction accuracy of the multi-layer perceptron model, offering valuable insights for target optimization, exploration planning and petroleum resource evaluation in other blocks in the sag.
- machine learning,
- neural network,
- prediction model,
- resource abundance,
- Dongpu Sag,
- Bohai Bay Basin

All authors disclose no relevant conflict of interests.
The study was designed by YANG Zijie, CHEN Dongxia, WANG Qiaochu, WANG Fuwei, LI Sha and TIAN Ziye. The prediction of model data was made by YANG Zijie, CHEN Shumin, ZHANG Wanrong, YAO Dongsheng and WANG Yuchao. The manuscript was drafted and revised by YANG Zijie, CHEN Dongxia, WANG Qiaochu and WANG Fuwei. All the authors have read the last version of paper and consented for submission.

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References(30)

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Prediction of petroleum resource abundance based on artificial neural network method: a case study of third member of Paleogene Shahejie Formation in Wenliu area of Dongpu Sag, Bohai Bay Basin

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Prediction of petroleum resource abundance based on artificial neural network method: a case study of third member of Paleogene Shahejie Formation in Wenliu area of Dongpu Sag, Bohai Bay Basin

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