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Big data analysis and achievements of global Petroleum exploration

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<p>Through applying the data mining analysis techniques of cluster analysis and correlation analysis, as well as spatial analysis and data visualization analysis techniques closely combined with GIS technology, based on IHS’s global exploratory well data, global oil and gas field data,  the data and its classification schemes of 468 petroliferous basins identified by the Oil and Gas Resources Evaluation Project Team of PetroChina, this paper conducted topological analysis, spatial overlay analysis and spatial statistical analysis research in the system of ArcGISn. For the first time, it completed the globally big data mining and analysis of various basin drilling exploration. Meanwhile, it applied small patches technique to analyze the heat of global oil and gas drilling exploration, obtained some new understandings of the global oil and gas exploration activity routines, which is considered to be significant in guiding the optimization of new exploration projects worldwide, and indicated the good application prospect of the big data analysis technology in the oil and gas industry.The new findings are as follows. (1) The prospects with high degree of exploration globally mainly concentrate in Tethyan tectonic domain. (2) In the history of petroleum industry, the active period was distinct with basin types. Specifically, it was in 1910-1920 for for-arc basins, 1950-1980 for foreland basins, and 1980-1990 for continental rift basins. (3) The global success ratio of exploratory wells is 28.8% on the average, and the success ratio does not differ greatly for various types of basins. Generally, the ratio is relatively higher for passive continental margin basins, but relatively lower for for-arc basins. (4) Through estimating the average well-controllable reserves to denote the exploration efficiency in a specific basin type, it is illustrated that the exploration efficiency was the highest in passive continental margin basins, followed by continental rift basins and foreland basins, and the lowest in fore-arc basins.</p>
Title: Big data analysis and achievements of global Petroleum exploration
Description:
<p>Through applying the data mining analysis techniques of cluster analysis and correlation analysis, as well as spatial analysis and data visualization analysis techniques closely combined with GIS technology, based on IHS’s global exploratory well data, global oil and gas field data,  the data and its classification schemes of 468 petroliferous basins identified by the Oil and Gas Resources Evaluation Project Team of PetroChina, this paper conducted topological analysis, spatial overlay analysis and spatial statistical analysis research in the system of ArcGISn.
For the first time, it completed the globally big data mining and analysis of various basin drilling exploration.
Meanwhile, it applied small patches technique to analyze the heat of global oil and gas drilling exploration, obtained some new understandings of the global oil and gas exploration activity routines, which is considered to be significant in guiding the optimization of new exploration projects worldwide, and indicated the good application prospect of the big data analysis technology in the oil and gas industry.
The new findings are as follows.
(1) The prospects with high degree of exploration globally mainly concentrate in Tethyan tectonic domain.
(2) In the history of petroleum industry, the active period was distinct with basin types.
Specifically, it was in 1910-1920 for for-arc basins, 1950-1980 for foreland basins, and 1980-1990 for continental rift basins.
(3) The global success ratio of exploratory wells is 28.
8% on the average, and the success ratio does not differ greatly for various types of basins.
Generally, the ratio is relatively higher for passive continental margin basins, but relatively lower for for-arc basins.
(4) Through estimating the average well-controllable reserves to denote the exploration efficiency in a specific basin type, it is illustrated that the exploration efficiency was the highest in passive continental margin basins, followed by continental rift basins and foreland basins, and the lowest in fore-arc basins.
</p>.

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