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| 005 | 20260520175316.0 | ||
| 008 | 260224s2021 xxu ing | ||
| 041 | _aInglés | ||
| 245 | 0 | 0 | _aMachine-Learning Approach Optimizes Well Spacing |
| 260 | _csept. 2021 | ||
| 270 | _a03/01/2022 ; 03/01/2022 | ||
| 300 | _a2 p. ; 44-45 | ||
| 500 | _aThis article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper SPE 201698, "Finding a Trend Out of Chaos: A MachineLearning Approach for WellSpacing Optimization," by Zheren Ma, Ehsan Davani, SPE, and Xiaodan Ma, SPE, Quantum Reservoir Impact, et al., prepared for the 2020 SPE Annual Technical Conference and Exhibition, originally scheduled to be held in Denver, Colorado, 5-7 October. The paper has not been peer reviewed. | ||
| 581 | _a9 | ||
| 773 | 0 | _tJournal of Petroleum Technology | |
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