It is difficult to systematically analyze the nonlinear relationship between CBM fracturing effect and influencing factors from the perspective of mechanism, and a method based on cluster matching was proposed to identify the main controlling factors of fracturing effect. The method analyzed the connection between fracturing effect and influencing factors by tapping into the intrinsic connection of influencing factors based on data rather than by subjective judgment. Firstly, the data of gas production indicator after fracturing was taken as the object of study and the agglomerative clustering method was employed to classify and evaluate the effect of sample wells. Secondly, the influencing factors were classified and screened by K-means clustering algorithm in conjunction with information gain sequencing and correction analysis, from which 8 factors were selected: prepad fluid dosage, proppant-carrying fluid dosage, gas saturation, gas content, vertical stress, proppant dosage, fracturing pressure and proppant filling strength. Finally, the selected factors were clustered, and the clustering results were clustered and matched with the evaluation and classification results of fracturing effect, so as to identify the main controlling factors of fracturing effect. The effectiveness and operability of this method were verified by comparing it with other methods for identifying the main controlling factors. The study can provide technical support for optimizing the secondary fracturing plan.
Min Chao
,
Dai Boren
,
Shi Yongheng
,
Yang Zhaozhong
,
Li Xiaogang
,
Zhang Xinhui
. Identification of Main Controlling Factors of Coalbed Methane Fracturing Effect Based on Cluster Matching[J]. Special Oil & Gas Reservoirs, 2022
, 29(4)
: 135
-141
.
DOI: 10.3969/j.issn.1006-6535.2022.04.019
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