Important Factors to Propose High-Produced New Development Wells in CBM Project

2014 ◽  
Vol 1030-1032 ◽  
pp. 2578-2581
Author(s):  
Zhao Hui Xia ◽  
Ming Zhang ◽  
Bin Ren ◽  
Liang Chao Qu ◽  
Ze Hong Cui ◽  
...  

Coal bed methane (CBM) is a kind of natural gas that generated from coal and disseminated organic matters during the stage of diagenesis and coalification, which mainly composed of methane and hosted in coal seam by free, adsorbed, and dissolved forms. Genetic, reservoir type and occurrence condition in CBM are different from traditional reservoir. And the high-produced development wells in CBM aiming to drill more coal seams with high quality therefore needs to be analyzed in the methods that are different from traditional reservoir. 3 important factors including the study on correlation and elevation depth of coal seam roof and floor in section and areal by using well-seismic ties, outcrop boundary based on coal mine data and distributions of CBM reservoir properties in 3D model are needed for high-produced development well analyze in CBM. Application in Australia CBM project shows this methodology is very successful for the development well design with high production.

2019 ◽  
Vol 12 (16) ◽  
Author(s):  
Dawei Lv ◽  
Changyong Lu ◽  
Zhijie Wen ◽  
Hongzhu Song ◽  
Shuai Yin

2019 ◽  
Vol 2019 ◽  
pp. 1-7
Author(s):  
Guiqiang Zheng ◽  
Bin Sun ◽  
Dawei Lv ◽  
Zhejun Pan ◽  
Huiqing Lian

Coalbed methane (CBM) reservoir properties and relationship of properties with burial depth were studied based on the data derived from 204 deep CBM production wells in Qinshui Basin, China. Through the study, it is found that permeability and porosity decrease with the increase of burial depth and the decreasing trend shows step-change characteristics at a critical burial depth. They also show divisional characteristics at certain burial depth. Gas content, geostress, and geotemperature increase with the increase of burial depth, and the increasing trend shows step-change characteristics and also have divisional characteristics at certain burial depth. Based on the previous study on the reservoir property changes with burial depth, three series of critical depth using different parameters are obtained through simulating the critical depth using the BP neural network method. It is found that the critical depth is different when using different parameters. Combined the previous study with the normalization of three different parameter types, the critical depth in Qinshui Basin was defined as shallow coal seam is lower than 650 m and transition band is 650–1000 m, while deep coal seam is deeper than 1000 m. In deep coal seams, the geological conditions and recovery becomes poor, so it can be defined as unfavorable zones. Therefore, other development means, for example, CO2 injection, need to be used to accelerate the deep coal methane development.


2007 ◽  
Vol 29 (4) ◽  
pp. 474 ◽  
Author(s):  
Thomas D. Brown ◽  
Donald K. Harrison ◽  
J. Richard Jones ◽  
Kenneth A. LaSota

2014 ◽  
Vol 1003 ◽  
pp. 183-187
Author(s):  
Huai Jie Yang ◽  
He Ping Pan

In this study, the well logging response of CBM reservoir have been analyzed, and discussing the factors that affect the gas content of coal seam. The well logging technology has been employed in connection with log data and gas content. Take one oilfield’s well logging data for example, statistical analysis method and Langmuir equation method are selected to calculate the gas content of one coal seam, the two calculated results are basically the same, the highest value are about 26 cm3/g, is a high-yield coal seam.


2014 ◽  
Vol 962-965 ◽  
pp. 213-216
Author(s):  
Guo Ping Jiang

In this paper, four general directions are described to make evaluations and their resource potential; those are coal structure and coal level, gas content of deep coalbed, the coalbed thickness and distribution and the buried depth of coalbed. Coalfields of the study area are mainly Permian and Carboniferous coal seam of Shanxi Formation coal and Benxi group 11 # coal, coal seam depth 1370-1812m. No. 3 coal-seam average layer thickness of 1.6 m, the monolayer most 2 m thick; No. 11 coal-seam in the average layer thickness of 3 m, single-layer thickness of 4.5 m. Predict the amount of coal resources of 17.3 one hundred million t. Predict coal-bed methane resources of 27.68 billion cubic reserve abundance of 104 million square / km2 in. The exploration results show that this region has good development prospects.


Geophysics ◽  
2006 ◽  
Vol 71 (4) ◽  
pp. C49-C56 ◽  
Author(s):  
Suping Peng ◽  
Huajing Chen ◽  
Ruizhao Yang ◽  
Yunfeng Gao ◽  
Xinping Chen

There are similarities and differences in employing amplitude variation with offset (AVO) to explore for gas-sand reservoirs, as opposed to coal-bed methane (CBM) reservoirs. The main similarity is that large Poisson’s ratio contrasts, resulting in AVO gradient anomalies, are expected for both kinds of reservoirs. The main difference is that cleating and fracturing raise the Poisson’s ratio of a coal seam as it improves its reservoir potential for CBM, while gas always lowers the Poisson’s ratio of a sandstone reservoir. The top of gas sands usually has a negative AVO gradient, leading to a class one, two, or three anomaly depending on the impedance contrast with the overlying caprock. On the other hand, the top of a CBM reservoir has a positive AVO gradient, leading to a class four anomaly. Three environmental factors may limit the usage of AVO for CBM reservoirs: the smaller contrast in Poisson’s ratio between a CBM reservoir and its surrounding rock, variations in the caprock of a specific CBM reservoir, and the fact that CBM is not always free to collect at structurally high points in the reservoir. However, other factors work in favor of using AVO. The strikingly high reflection amplitude of coal improves signal/noise ratio and hence the reliability of AVO measurements. The relatively simple characteristics of AVO anomalies make them easy to interpret. Because faults are known to improve the quality of CBM reservoirs, faults accompanied by AVO anomalies would be especially convincing. A 3D-AVO example offered in this paper shows that AVO might be helpful to delineate methane-rich sweet spots within coal seams.


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