Production Performance Analysis and Fracture Volume Parameter Inversion of Deep Coalbed Methane Wells

Deep coalbed methane development faces technical challenges, such as high in situ stress and low permeability. The dynamic evolution of fractures after hydraulic fracturing and the flowback mechanism are crucial for optimizing productivity. This paper focuses on the inversion of post-fracturing fracture volume parameters and dynamic analysis of the flowback in deep coalbed methane wells, with 89 vertical wells in the eastern margin of the Ordos Basin as the research objects, conducting systematic studies. Firstly, through the analysis of the double-logarithmic curve of normalized pressure and material balance time, the quantitative inversion of the volume of propped fractures and unpropped secondary fractures was realized. Using Pearson correlation coefficients to screen characteristic parameters, four machine learning models (Ridge Regression, Decision Tree, Random Forest, and AdaBoost) were constructed for fracture volume inversion prediction. The results show that the Random Forest model performed the best, with a test set R2 of 0.86 and good generalization performance, so it was selected as the final prediction model. With the help of the SHAP model to analyze the influence of each characteristic parameter, it was found that the total fluid volume into the well, proppant intensity, minimum horizontal in situ stress, and elastic modulus were the main driving factors, all of which had threshold effects and exerted non-linear influences on fracture volume. The interaction of multiple parameters was explored by the Partial Dependence Plot (PDP) method, revealing the synergistic mechanism of geological and engineering parameters. For example, a high elastic modulus can enhance the promoting effect of fluid volume into the well and proppant intensity. There is a critical threshold of 2600 m3 in the interaction between the total fluid volume into the well and the minimum horizontal in situ stress. These findings provide a theoretical basis and technical support for optimizing fracturing operation parameters and efficient development of deep coalbed methane.

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Publication Details

Journal
Energies
Published
2025-09-15
DOI
https://doi.org/10.3390/en18184897
Primary Topic
Coal Properties and Utilization
Type
article
Field-Weighted Citation Impact
0.00

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article

Production Performance Analysis and Fracture Volume Parameter Inversion of Deep Coalbed Methane Wells

Xiaotong Xin, Guangai Wu, Wen Heng, Jianshu Wu et al.
Energies
Coal Properties and Utilization
article

Production Performance Analysis and Fracture Volume Parameter Inversion of Deep Coalbed Methane Wells

Xiaotong Xin, Guangai Wu, Wen Heng, Jianshu Wu, Cong Xiao, Jie Liu, Lei Zou, Shicheng Zhang
article en

Abstract

Deep coalbed methane development faces technical challenges, such as high in situ stress and low permeability. The dynamic evolution of fractures after hydraulic fracturing and the flowback mechanism are crucial for optimizing productivity. This paper focuses on the inversion of post-fracturing fracture volume parameters and dynamic analysis of the flowback in deep coalbed methane wells, with 89 vertical wells in the eastern margin of the Ordos Basin as the research objects, conducting systematic studies. Firstly, through the analysis of the double-logarithmic curve of normalized pressure and material balance time, the quantitative inversion of the volume of propped fractures and unpropped secondary fractures was realized. Using Pearson correlation coefficients to screen characteristic parameters, four machine learning models (Ridge Regression, Decision Tree, Random Forest, and AdaBoost) were constructed for fracture volume inversion prediction. The results show that the Random Forest model performed the best, with a test set R2 of 0.86 and good generalization performance, so it was selected as the final prediction model. With the help of the SHAP model to analyze the influence of each characteristic parameter, it was found that the total fluid volume into the well, proppant intensity, minimum horizontal in situ stress, and elastic modulus were the main driving factors, all of which had threshold effects and exerted non-linear influences on fracture volume. The interaction of multiple parameters was explored by the Partial Dependence Plot (PDP) method, revealing the synergistic mechanism of geological and engineering parameters. For example, a high elastic modulus can enhance the promoting effect of fluid volume into the well and proppant intensity. There is a critical threshold of 2600 m3 in the interaction between the total fluid volume into the well and the minimum horizontal in situ stress. These findings provide a theoretical basis and technical support for optimizing fracturing operation parameters and efficient development of deep coalbed methane.

EnergiesVol. 18(18)
China University of Petroleum, Beijing (CN)
National Natural Science Foundation of China, China National Offshore Oil Corporation
Openalex Percentile: Top 69%
Coal Properties and Utilization
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