Paper
18 March 2022 Geological modeling of carboniferous reservoir in Xiquan 103 well area
Author Affiliations +
Proceedings Volume 12168, International Conference on Computer Graphics, Artificial Intelligence, and Data Processing (ICCAID 2021); 121680Y (2022) https://doi.org/10.1117/12.2631114
Event: International Conference on Computer Graphics, Artificial Intelligence, and Data Processing (ICCAID 2021), 2021, Harbin, China
Abstract
To analyze Carboniferous oil and gas resources in Xiquan 103 well area, Petrel modeling software is used to integrate the previous geological research results, According to the geological structure characteristics of volcanic rocks, the modeling ideas are reasonably formulated, three-dimensional geological model of dual-medium reservoir of volcanic rock is established by establishing key steps such as structural model, reservoir facies model, matrix reservoir parameter model and fracture model, so as to realize three-dimensional quantitative prediction of matrix and fracture reservoir parameters. On the basis of model verification, reasonable coarsening grid provides reliable three-dimensional geological model for numerical simulation. The accuracy of the model established in this paper is 25 × 25 × 0. 5m, and the total number of grids is 5.81 million. The model verification has high coincidence, and the reserves are calculated by units, and the fitting error of reserves is less than 5%. In this paper, Carboniferous oil and gas resources in Xiquan 103 well area is studied and implemented, which provides reference for subsequent oil and gas field development.
© (2022) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Tong Zhang, Xingwang Luo, Guanghua Li, Wenjun Tang, Wu Zhang, Chen Li, Qiang Luo, Ruixue Zhang, Jian Ma, and Yanmei Zhang "Geological modeling of carboniferous reservoir in Xiquan 103 well area", Proc. SPIE 12168, International Conference on Computer Graphics, Artificial Intelligence, and Data Processing (ICCAID 2021), 121680Y (18 March 2022); https://doi.org/10.1117/12.2631114
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KEYWORDS
Stochastic processes

Process modeling

Statistical analysis

Computer simulations

Lithium

Numerical simulations

Modeling

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