Geological Modeling Technology and Application Based on Seismic Interpretation Results under the Background of Artificial Intelligence

Author:

Peng Ximing12,Li Minglu3,Zhu Yalin14,Li Na5,Dong Hao678ORCID

Affiliation:

1. State Key Laboratory of Continental Dynamics, Department of Geology, Northwest University, Xi’an 710069, Shannxi, China

2. Institute of Geo-Environment Monitoring of Jingxian, Xuancheng 242500, Anhui, China

3. School of Media, Zhengzhou Institute of Engineering and Technology, Zhengzhou 450045, Henan, China

4. Henan Provincial Academy of Building Research, Zhengzhou 450053, Henan, China

5. School of Doctor of Business Administration, Jose Rizal University, Mandaluyong 1552, Philippines

6. Shaanxi Provincial Land Engineering Construction Group Co., Ltd, Xi’an 710075, Shannxi, China

7. Institute of Land Engineering and Technology, Shaanxi Provincial Land Engineering Construction Group Co. Ltd., Xi’an 710075, Shannxi, China

8. School of Management, Xi’an Jiaotong University, Xi’an 710049, Shannxi, China

Abstract

The development of seismic technology has made seismic data to be widely used in the interpretation of stratigraphic sequence frames, reservoir identification, fluid detection, and other research fields involved in reservoir description. The 3D technology reservoirs have always been the focus, as well as difficulty, of research. With the rapid development of information technology and the continuous improvement of seismic exploration level, people have put forward higher requirements for the accuracy of seismic data interpretation results. Aiming at the large number of structural and unstructured data in seismic, logging, geology, and other disciplines involved in seismic interpretation, how to effectively organize and coordinate analysis to discover the hidden reservoir structure and oil and gas distribution information has always been a geological and important topic for information processing technicians. This thesis is aimed at the current high-water-phase development of Shengtuo Oilfield reservoir and the problems existing in geological research. Based on seismic structural interpretation and attribute analysis, this paper analyzes the reservoir structural characteristics, sedimentary characteristics, and reservoir physical parameter characteristics based on geology, logging interpretation, core analysis, drilling, and seismic interpretation. Using the kriging method with external drift can cooperate with seismic variables to establish a reservoir geological model to study the Shengtuo Oilfield reservoir. We combine artificial intelligence technology with geological modeling technology of seismic interpretation results to explore the best method for predicting earthquakes. The research results in this paper show that the relative error of the model established by the kriging method in the article is relatively small for thinning wells, mainly concentrated around 1%. Examination of the thinning wells of 45 wells shows that the model established is basically good and the example has high accuracy. The research results in this paper have a guiding study of distribution and tapping potentials in the study area, formulating reasonable development and adjustment plans and improving oil recovery.

Funder

National Natural Science Foundation of China

Publisher

Hindawi Limited

Subject

Computer Networks and Communications,Computer Science Applications

Reference25 articles.

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Detection and Analysis of Engineering Quality of Mine Oil and Gas Reservoir based on Computer Image Analysis Technology;2023 3rd International Conference on Intelligent Technologies (CONIT);2023-06-23

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