一种基于常规测井资料计算碳酸盐岩储层裂缝孔隙度新方法

雷明; 陈涛; 韩乾凤; 程木伟; 高庚; 沙雪梅; 张亚军

doi:10.3799/dqkx.2022.202

Volume 48 Issue 7

Jul. 2023

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Article Navigation > Earth Science > 2023 > 48(7): 2678-2689

Lei Ming, Chen Tao, Han Qianfeng, Cheng Muwei, Gao Geng, Sha Xuemei, Zhang Yajun, 2023. A New Method for Calculating Fracture Porosity Based on Conventional Logging Data. Earth Science, 48(7): 2678-2689. doi: 10.3799/dqkx.2022.202

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Lei Ming, Chen Tao, Han Qianfeng, Cheng Muwei, Gao Geng, Sha Xuemei, Zhang Yajun, 2023. A New Method for Calculating Fracture Porosity Based on Conventional Logging Data. Earth Science, 48(7): 2678-2689. doi: 10.3799/dqkx.2022.202

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A New Method for Calculating Fracture Porosity Based on Conventional Logging Data

doi: 10.3799/dqkx.2022.202

Lei Ming^{1, 2
,
,},
Chen Tao^{1, 2},
Han Qianfeng^{1, 2},
Cheng Muwei³,
Gao Geng⁴,
Sha Xuemei^{1, 2},
Zhang Yajun^{1, 2}

1.
PetroChina Research Institute of Petroleum Exploration & Development-Northwest, Lanzhou 730020, China
2.
Key Laboratory of Reservoir Description, CNPC, Lanzhou 730020, China
3.
PetroChina Research Institute of Petroleum Exploration & Development, Beijing 100083, China
4.
Exploration and Development Research Institute of Daqing Oilfield, Daqing 163712, China

Received Date: 2022-01-20
Publish Date: 2023-07-25

Abstract

Abstract

Fracture as reservoir space and migration channel of oil and gas, is an important part of the fracture reservoir study, so that, fracture porosity is the most important parameter in fracture reservoir logging evaluation. Although there are many qualitative identification and description methods, but how to use conventional log data to quantitatively calculate fracture porosity has always been a difficult problem in fracture reservoir interpretation. A new method for calculating fracture porosity based on conventional logging data of probabilistic neural network is proposed in this study, taking a reservoir of a gas field in the Amu Darya Basin as an example. The reservoir in Upper Jurassic Callovian-Oxfordian order group is located on the platform margin slope, with relatively high energy beach facies and high beach complex fracture-pore type. To calculate fracture porosity of the wells which have imaging well logging data, first, a variety of classic model methods are used to calculate fracture porosity with dual laterolog resistivity data, comprehensive with the acoustic data and density data. Then the weighted factor to weighted the fracture porosity is calculated by those kinds of models, and the weighted calculation result is calibrated using the accurate fracture porosity calculated by imaging logging data as a constraint to get the final fracture porosity curve. For the wells which do not have imaging well logging data, using probabilistic neural network algorithm of deep learning to establish the mapping relation between the calculated fracture porosity curve from imaging logging data and conventional well logging data, so that the fracture porosity curve of other wells can be calculated, and the calculation error can be determined by using cross validation criterion. The results show that the fracture porosity calculated by this new method is in good agreement with the fracture porosity interpreted by imaging logging. For the wells without imaging logging data, after the lateral extrapolation calculation, according to the actual lost circulation of the target interval, the analysis of production performance data and the verification and comparison of reservoir parameters were made, which is consistent with the oilfield production situation, which indirectly confirms the reliability of the calculation results and indicates that this method is an effective method.
- conventional logging,
- imaging logging,
- fracture porosity,
- Amu Darya Basin,
- probabilistic neural network

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References(53)

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A New Method for Calculating Fracture Porosity Based on Conventional Logging Data

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