陆相页岩气资源评价中人工智能算法的探索——以苏北盆地溱潼凹陷为例
|
谈迎, 杨伟松, 李振生
|
The tentative application of artificial intelligence algorithm to evaluating continental shale gas resources: A case study of Qintong sag in Subei (North Jiangsu) Basin
|
Ying TAN, Wei-Song YANG, Zhen-Sheng LI
|
|
表6 溱潼凹陷页岩气目的层评价结果 |
|
|
目的层 | 样品区号 | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 | 13 | 14 | 15 | 16 | 17 | 阜宁组四段B1 | 0.30 | 0.33 | 0.41 | 0.46 | 0.67 | 0.36 | 0.46 | 0.70 | 0.79 | 0.43 | 0.49 | 0.66 | 0.41 | 0.26 | 0.33 | 0.32 | 0.67 | 阜宁组三段B2 | 0.27 | 0.26 | 0.35 | 0.71 | 0.76 | 0.33 | 0.60 | 0.73 | 0.67 | 0.99 | 0.46 | 0.66 | 0.46 | 0.37 | 0.17 | 0.48 | 0.68 | 阜宁组二段B3 | 0.31 | 0.21 | 0.32 | 0.73 | 0.59 | 0.23 | 0.57 | 0.74 | 0.69 | 0.49 | 0.58 | 0.61 | 0.40 | 0.41 | 0.16 | 0.64 | 0.71 | 阜宁组一段B4 | 0.40 | 0.48 | 0.44 | 0.48 | 0.47 | 0.44 | 0.52 | 0.63 | 0.46 | 0.56 | 0.56 | 0.36 | 0.35 | 0.46 | 0.11 | 0.49 | 0.66 | 泰州组二段B5 | 0.46 | 0.63 | 0.46 | 0.61 | 0.45 | 0.36 | 0.36 | 0.50 | 0.67 | 0.37 | 0.46 | 0.56 | 0.36 | 0.35 | 0.25 | 0.66 | 0.72 | ∑Bi | 1.74 | 1.91 | 1.88 | 2.99 | 2.94 | 1.72 | 2.51 | 3.30 | 3.28 | 2.50 | 2.55 | 2.85 | 1.98 | 1.85 | 1.02 | 2.79 | 3.44 | B总 | 0.35 | 0.38 | 0.37 | 0.59 | 0.59 | 0.34 | 0.50 | 0.66 | 0.66 | 0.47 | 0.51 | 0.57 | 0.40 | 0.37 | 0.20 | 0.56 | 0.69 |
|
|
|