1.China United Coalbed Methane Corporation Ltd.,Beijing 100016,China;
2.School of Resources and Geosciences, China University of Mining and Technology, Xuzhou 221116, China
Abstract Deep coalbed methane (CBM) resources are enormous and have become a hot topic in the unconventional exploration and development of natural gas. The fractures in CBM reservoirs are important channels for the storage and migration of CBM and control the high production and enrichment of CBM. Therefore, fracture prediction in deep CBM reservoirs is of great significance for the exploration and development of CBM. First, the basic principles of calculating texture attributes by gray-level cooccurrence matrix (GLCM) and gray-level run-length matrix (GLRLM) were introduced. A geological model of the deep CBM reservoirs with fractures was then constructed and subjected to seismic forward simulation. The seismic texture attributes were extracted using the GLCM and GLRLM. The research results indicate that the texture attributes calculated by both methods are responsive to fractures, with the 45° and 135° gray level inhomogeneity texture attributes based on the GLRLM showing better identification effects for fractures. Fracture prediction of a deep CBM reservoir in the Ordos Basin was carried out based on the GLRLM texture attributes, providing an important basis for the efficient development and utilization of deep CBM.
Fund: This work was supported by the National Natural Science Foundation of China (Grant No. 42274180) and the National Key Research and Development Program of China (2021YFC2902003).
About author: Zhang Bing, Senior Engineer, graduated from China University of Petroleum (Beijing) in 2009. He is now engaged in technical research and management of coalbed methane and tight gas exploration and development in China United Coalbed Methane Co., Ltd.
Cite this article:
. Fracture prediction method for deep coalbed methane reservoirs based on seismic texture attributes[J]. APPLIED GEOPHYSICS, 2024, 21(4): 794-804.
2024, Vol. 21 
