Data-Driven Exploration and Analysis of Natural Gas Hydrate Resource Distribution
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DOI: 10.25236/icetmr.2024.007
Corresponding Author
Jingyao Zhang
Abstract
This paper employs a data-driven approach to explore and analyze the distribution of natural gas hydrate resources. Key indicators, including total effective thickness, average porosity of oil layers, and absolute average saturation, were constructed to assess the resource potential of 14 exploration points. Spatial modeling and comprehensive scoring of monitoring points were performed using Kriging interpolation and TOPSIS evaluation methods to determine the distribution of natural gas hydrate resources. Additionally, a probability distribution model was constructed using kernel density estimation, and multivariate nonlinear regression analysis was applied to study the spatial distribution patterns of effective thickness, stratigraphic porosity, and saturation. Finally, the model was optimized using the differential evolution algorithm, and the results indicated a strong correlation between total effective thickness, stratigraphic porosity, and saturation with geographical locations, with good model fit, providing a scientific basis for the exploration and development of natural gas hydrate resources.
Keywords
Natural gas hydrate, resource distribution, Kriging interpolation, TOPSIS evaluation, kernel density estimation, differential evolution algorithm