| Autor: |
Qikang ZHU, Botao LIN, Guang YANG, Lijia WANG, Man CHEN |
| Jazyk: |
English<br />Chinese |
| Rok vydání: |
2022 |
| Předmět: |
|
| Zdroj: |
Petroleum Exploration and Development, Vol 49, Iss 4, Pp 886-894 (2022) |
| Druh dokumentu: |
article |
| ISSN: |
1876-3804 |
| DOI: |
10.1016/S1876-3804(22)60318-5 |
| Popis: |
Shale gas wells frequently suffer from liquid loading and insufficient formation pressure in the late stage of production. To address this issue, an intelligent production optimization method for low pressure and low productivity shale gas well is proposed. Based on the artificial intelligence algorithms, this method realizes automatic production and monitoring of gas well. The method can forecast the production performance of a single well by using the long short-term memory neural network and then guide gas well production accordingly, to fulfill liquid loading warning and automatic intermittent production. Combined with adjustable nozzle, the method can keep production and pressure of gas wells stable automatically, extend normal production time of shale gas wells, enhance automatic level of well sites, and reach the goal of refined production management by making production regime for each well. Field tests show that wells with production regime optimized by this method increased 15% in estimated ultimate reserve (EUR). Compared with the development mode of drainage after depletion recovery, this method is more economical and can increase and stabilize production effectively, so it has a bright application prospect. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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