An intelligent automatic correlation method of oil-bearing strata based on pattern constraints: An example of accretionary stratigraphy of Shishen 100 block in Shinan Oilfield of Bohai Bay Basin, East China

IF 7 Q1 ENERGY & FUELS
Degang WU , Shenghe WU , Lei LIU , Yide SUN
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引用次数: 0

Abstract

Aiming at the problem that the data-driven automatic correlation methods which are difficult to adapt to the automatic correlation of oil-bearing strata with large changes in lateral sedimentary facies and strata thickness, an intelligent automatic correlation method of oil-bearing strata based on pattern constraints is formed. We propose to introduce knowledge-driven in automatic correlation of oil-bearing strata, constraining the correlation process by stratigraphic sedimentary patterns and improving the similarity measuring machine and conditional constraint dynamic time warping algorithm to automate the correlation of marker layers and the interfaces of each strata. The application in Shishen 100 block in the Shinan Oilfield of the Bohai Bay Basin shows that the coincidence rate of the marker layers identified by this method is over 95.00%, and the average coincidence rate of identified oil-bearing strata reaches 90.02% compared to artificial correlation results, which is about 17 percentage points higher than that of the existing automatic correlation methods. The accuracy of the automatic correlation of oil-bearing strata has been effectively improved.

基于模式约束的含油地层智能自动相关方法:以华东渤海湾盆地新安油田石深100区块增生地层为例
针对数据驱动的自动相关方法难以适应侧向沉积面和地层厚度变化较大的含油地层自动相关的问题,形成了基于模式约束的含油地层智能自动相关方法。我们提出在含油地层自动相关中引入知识驱动,以地层沉积模式约束相关过程,改进相似度测量机和条件约束动态时间扭曲算法,实现标记层与各地层界面的自动相关。在渤海湾盆地新安油田石深100区块的应用表明,与人工相关结果相比,该方法识别的标志层重合率超过95.00%,识别的含油层平均重合率达到90.02%,比现有自动相关方法高出约17个百分点。有效提高了含油地层自动相关的精度。
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CiteScore
11.50
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发文量
473
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