Prediction Model and Risk Quantification of Natural Gas Peak Production in Central Sichuan Paleo-Uplift Gas Reservoirs
Located in the Sichuan Basin of China, the central Sichuan paleo-uplift is a geological structure that spanned several areas in Sichuan province and was formed 500 million years ago. It is the bottom layer with rich conventional natural gas resources of more than 3×1012 m3, and the proven reserves a...
Saved in:
| Main Authors: | , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2023-01-01
|
| Series: | Geofluids |
| Online Access: | http://dx.doi.org/10.1155/2023/4858118 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1849304697527074816 |
|---|---|
| author | Haitao Li Guo Yu Chun Li Zhenglong Xie Chenxi Liu Dongming Zhang Chongyang Wang |
| author_facet | Haitao Li Guo Yu Chun Li Zhenglong Xie Chenxi Liu Dongming Zhang Chongyang Wang |
| author_sort | Haitao Li |
| collection | DOAJ |
| description | Located in the Sichuan Basin of China, the central Sichuan paleo-uplift is a geological structure that spanned several areas in Sichuan province and was formed 500 million years ago. It is the bottom layer with rich conventional natural gas resources of more than 3×1012 m3, and the proven reserves are about 30%, while the recovery rate is only 1.4%. In this paper, the Hubbert and Gauss models are used to study the peak production of natural gas. The Monte Carlo simulation method is used to predict the realization probability of future medium and long-term production, evaluate the risk level of natural gas production, and realize the whole process research from scale prediction to risk quantification of gas reservoirs. According to the Gauss model, under the realization probability of P50, the gas reservoir in the central Sichuan paleo-uplift can reach a peak production value of 145×108m3/a, in 2040, and maintain a stable production state in 2034-2046. The risk grade evaluation matrix, through which the dispersion degree C ∈ (5% and 10%) in the rising stage and rapid production decline stage can be obtained, and the dispersion degree C ∈ (10% and 25%) in the stable production stage and slow production decline stage can be obtained. The dispersion degree and realization probability can be integrated to obtain the risk level at different stages. |
| format | Article |
| id | doaj-art-3a80eac7d8c843a5be818aaa22b41b2b |
| institution | Kabale University |
| issn | 1468-8123 |
| language | English |
| publishDate | 2023-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Geofluids |
| spelling | doaj-art-3a80eac7d8c843a5be818aaa22b41b2b2025-08-20T03:55:40ZengWileyGeofluids1468-81232023-01-01202310.1155/2023/4858118Prediction Model and Risk Quantification of Natural Gas Peak Production in Central Sichuan Paleo-Uplift Gas ReservoirsHaitao Li0Guo Yu1Chun Li2Zhenglong Xie3Chenxi Liu4Dongming Zhang5Chongyang Wang6Exploration and Development Research Institute of PetroChina Southwest Oil and Gas Field CompanyPetroChina Southwest Oil and Gas Field Company Planning DepartmentSinopec Xinan Oilfield Service Corporation First Drilling BranchExploration and Development Research Institute of PetroChina Southwest Oil and Gas Field CompanyCollege of Resources and SecurityCollege of Resources and SecurityCollege of Resources and SecurityLocated in the Sichuan Basin of China, the central Sichuan paleo-uplift is a geological structure that spanned several areas in Sichuan province and was formed 500 million years ago. It is the bottom layer with rich conventional natural gas resources of more than 3×1012 m3, and the proven reserves are about 30%, while the recovery rate is only 1.4%. In this paper, the Hubbert and Gauss models are used to study the peak production of natural gas. The Monte Carlo simulation method is used to predict the realization probability of future medium and long-term production, evaluate the risk level of natural gas production, and realize the whole process research from scale prediction to risk quantification of gas reservoirs. According to the Gauss model, under the realization probability of P50, the gas reservoir in the central Sichuan paleo-uplift can reach a peak production value of 145×108m3/a, in 2040, and maintain a stable production state in 2034-2046. The risk grade evaluation matrix, through which the dispersion degree C ∈ (5% and 10%) in the rising stage and rapid production decline stage can be obtained, and the dispersion degree C ∈ (10% and 25%) in the stable production stage and slow production decline stage can be obtained. The dispersion degree and realization probability can be integrated to obtain the risk level at different stages.http://dx.doi.org/10.1155/2023/4858118 |
| spellingShingle | Haitao Li Guo Yu Chun Li Zhenglong Xie Chenxi Liu Dongming Zhang Chongyang Wang Prediction Model and Risk Quantification of Natural Gas Peak Production in Central Sichuan Paleo-Uplift Gas Reservoirs Geofluids |
| title | Prediction Model and Risk Quantification of Natural Gas Peak Production in Central Sichuan Paleo-Uplift Gas Reservoirs |
| title_full | Prediction Model and Risk Quantification of Natural Gas Peak Production in Central Sichuan Paleo-Uplift Gas Reservoirs |
| title_fullStr | Prediction Model and Risk Quantification of Natural Gas Peak Production in Central Sichuan Paleo-Uplift Gas Reservoirs |
| title_full_unstemmed | Prediction Model and Risk Quantification of Natural Gas Peak Production in Central Sichuan Paleo-Uplift Gas Reservoirs |
| title_short | Prediction Model and Risk Quantification of Natural Gas Peak Production in Central Sichuan Paleo-Uplift Gas Reservoirs |
| title_sort | prediction model and risk quantification of natural gas peak production in central sichuan paleo uplift gas reservoirs |
| url | http://dx.doi.org/10.1155/2023/4858118 |
| work_keys_str_mv | AT haitaoli predictionmodelandriskquantificationofnaturalgaspeakproductionincentralsichuanpaleoupliftgasreservoirs AT guoyu predictionmodelandriskquantificationofnaturalgaspeakproductionincentralsichuanpaleoupliftgasreservoirs AT chunli predictionmodelandriskquantificationofnaturalgaspeakproductionincentralsichuanpaleoupliftgasreservoirs AT zhenglongxie predictionmodelandriskquantificationofnaturalgaspeakproductionincentralsichuanpaleoupliftgasreservoirs AT chenxiliu predictionmodelandriskquantificationofnaturalgaspeakproductionincentralsichuanpaleoupliftgasreservoirs AT dongmingzhang predictionmodelandriskquantificationofnaturalgaspeakproductionincentralsichuanpaleoupliftgasreservoirs AT chongyangwang predictionmodelandriskquantificationofnaturalgaspeakproductionincentralsichuanpaleoupliftgasreservoirs |