A comprehensive logging evaluation method for identifying high-quality shale gas reservoirs based on multifractal...

Area of Science:

• Geosciences
• Petroleum Engineering
• Data Analysis

Background:

• Conventional methods for identifying shale reservoirs are often qualitative and struggle with complex formations.
• Accurate characterization of high-quality shale reservoirs is crucial for efficient gas extraction.

Purpose of the Study:

• To develop and validate a comprehensive, quantitative method for identifying high-quality shale gas reservoirs.
• To improve the accuracy and efficiency of shale reservoir evaluation using well log data.

Main Methods:

• Multi-fractal spectral analysis and R/S analysis of conventional well logs.
• Gray relational analysis to integrate production data with fractal characteristics.
• Introduction of comprehensive fractal evaluation indices (λ and γ) for productivity assessment.

Main Results:

• The proposed fractal evaluation method effectively classifies reservoir productivity.
• Simplified calculation of formation evaluation parameters is achieved.
• Improved correlation between identified sweet spots and actual gas production is demonstrated.

Conclusions:

• The fractal-based evaluation method offers a robust and applicable approach for identifying high-quality shale gas reservoir areas.
• This technique provides valuable technical support for the large-scale development of shale gas resources.
• The method overcomes limitations of traditional approaches in predicting sweet spot zones.