Coalbed methane gas content prediction by compound parameter model in S block of Australia

HUAI Yinchao; ZHANG Ming; XIA Zhaohui; LIU Bobiao; WANG Xin

doi:10.3969/j.issn.1001-1986.2018.01.027

Volume 46 Issue 1

Feb. 2018

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COAL GEOLOGY & EXPLORATION > 2018 > 46(1): 159-164. > DOI: 10.3969/j.issn.1001-1986.2018.01.027

HUAI Yinchao, ZHANG Ming, XIA Zhaohui, LIU Bobiao, WANG Xin. Coalbed methane gas content prediction by compound parameter model in S block of Australia[J]. COAL GEOLOGY & EXPLORATION, 2018, 46(1): 159-164. DOI: 10.3969/j.issn.1001-1986.2018.01.027

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Coalbed methane gas content prediction by compound parameter model in S block of Australia

1. School of Earth Science and Resources, Chang'an University, Xi'an 710054, China;
2. Research Institute of Petroleum Exploration and Development, Beijing 100083, China;
3. Petroleum Engineering Institute, Xi'an Shiyou University, Xi'an 710065, China

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Central University of basic scientific research business special funds funded project(310826161014)

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Received Date: March 04, 2017
Published Date: February 24, 2018

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Abstract

Abstract

Gas content is the most important research content for coalbed methane (CBM) development. Accuracy characterization is very important for CBM. Logging characterization of gas content is the most commonly used method, while different logs have different sensitivity to the change of gas content, and single logging curve predicting coalbed methane content has the disadvantages of poor stability and low accuracy. In order to study the accurate prediction method of CBM, CBM reservoirs in S Block of Australia is taken as study object. Based on the laboratory analysis data and logging data, the logging data response analysis was carried out to realize logging data expansion correction and depth shift. Logging data such as buried coal depth, AC, GR and LSD were selected as the basic parameters for gas content prediction on the basis of correlation analysis between gas content and logging data. After the sensitivity analysis between gas content and logging data, compound parameters of gas content prediction were constructed, and finally the compound parameter prediction model for gas content prediction was established. Batch calculation of CBM was achieved by plug-in module of logging interpretation software. In the practical application, the prediction model can overcome the shortcomings of the low accuracy and poor stability of the traditional coal seam gas content calculation. At the same time, it can realize the batch calculation and greatly speed up the calculation of gas content. The prediction of gas content by compound parameters can also provide a solid geological foundation for the CBM subsequent development of S block.
- coalbed methane,
- gas content,
- logging data,
- compound parameter,
- sensitivity analysis,
- Australia

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