Study on a New Rock Fracability Evaluation Model of Shale Gas Reservoir

Wang, Fei; Zhang, Yonghao; Li, Xin; Han, Xue

doi:10.1155/2020/8882899

Cited by 1 publication

(1 citation statement)

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“…The complex seam network structure of shale fractures can be quantitatively characterized using fractal analysis in three-dimensional CT scanning experiments 22, 23 .…”

Section: Introductionmentioning

confidence: 99%

A Comprehensive Logging Evaluation Method for Identifying High-Quality Shale Gas Reservoirs Based on Multifractal Spectra Analysis

Bi,

Li,

Lian

2024

Preprint

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Conventional logging interpretation methods can help to qualitatively identify shale reservoirs using shale attribute parameters and interpretation templates. However, improving the identification accuracy of complex shale reservoirs is challenging due to the numerous evaluation parameters and the complexity of model calculations. This study examines the JY6-2 and JY10-4 wells in the Fuling shale gas field as examples to effectively quantify the characteristics of high-quality shale reservoirs. We establish a comprehensive evaluation method for identifying high-quality shale gas reservoirs, utilizing multi-fractal spectra analysis of well logs. First, the conventional well logs are qualitatively analyzed and evaluated using the methods of multiple fractals and R/S analysis. Subsequently, a gray relational analysis is employed to combine the production well logs, which reflect dimensionless productivity contributions, with the fractal characteristics of conventional well logs to obtain the corrected weight multifractal spectrum width ∆α' and the fractal dimension D'. The comprehensive fractal evaluation indexes λ and γ are introduced, forming three categories of productivity evaluation standards for shale gas reservoirs characterized by fractals. The calculation results show that the ∆α' comprehensive fractal evaluation index for Class I gas reservoirs is 0.6 λ< 1, and the D' comprehensive fractal evaluation index is 0 γ < 0.5; for Class II gas reservoirs, the ∆α' comprehensive fractal evaluation index is 0.25 λ < 0.6, and the D' comprehensive fractal evaluation index is 0.5 γ < 0.8; for Class III gas reservoirs, the ∆α' comprehensive fractal evaluation index is 0 λ < 0.25, and the D' comprehensive fractal evaluation index is 0.8 γ < 1. Overall, the comprehensive fractal evaluation index of the high-production wells ∆α' is close to 1 and shows a decreasing trend from high to low production; the comprehensive fractal evaluation index of the low-production wells with the R/S fractal dimension D' is close to 1 and shows a decreasing trend from low-production to high-production. Finally, Well JY8-2 is employed as a validation well to demonstrate the effectiveness of the evaluation method. This research method is a simple way to extract the multifractal spectra based on conventional logging data to evaluate comprehensive sweet spot zones. It is of great significance for identifying high-quality reservoir areas in shale gas reservoirs, and provides technical support for the effective development of shale reservoirs on a large scale.

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“…The complex seam network structure of shale fractures can be quantitatively characterized using fractal analysis in three-dimensional CT scanning experiments 22, 23 .…”

Section: Introductionmentioning

confidence: 99%