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Predicting gas content in coalbed methane reservoirs using seismic waveform indication inversion: a case study from the Upper Carboniferous Benxi Formation, eastern Ordos Basin, China

  • Research Article - Applied Geophysics
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Abstract

The identification of gas content is very important for exploration and development of coalbed methane (CBM) reservoirs. As a kind of gas-bearing reservoirs in coal seam, CBM reservoirs usually show strong heterogeneity, which makes the gas content varies greatly in the strata. What’s more, the thin interlayer that is common in coal-bearing formation makes it difficult to predict the favorable gas-bearing distribution based on conventional methods. In this study, a seismic waveform indication inversion method was applied to reveal the gas content of No. 8 coal seam reservoirs in the Upper Carboniferous Benxi Formation of the DJ area in the eastern of the Ordos Basin, China. The first step of this method is to calculate the p-wave impedance inversion volume of No. 8 coal seam. The second step is to build the correlation between elastic parameters and gas content in No. 8 coal seam. Through the statistical analysis based on velocity, density, p-wave impedance and measured gas content data of 16 wells, the fitting formula between p-wave impedance and gas content is obtained, with a highest correlation coefficient up to 96%. The third step is to calculate the gas content data volume from the p-wave impedance inversion volume by the above fitting formula, and then the quantitative plane distribution of gas content in No. 8 coal seam can be predicted. The prediction results indicate that the gas content of No. 8 coal seam can be divided into two Classes. To verify the reliability of the inversion results, the production data of well X11 was applied to verify the gas content which located in the Class I area. The application of seismic waveform indication inversion has provided a precise prediction for the spatial distribution of gas content in CBM reservoirs, serving as a basis for locating and designing wells for CBM development.

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References

  • Banerjee A, Chatterjee R (2021) A methodology to estimate proximate and gas content saturation with lithological classification in coalbed methane reservoir Bokaro Field, India. Nat Resour Res 30(3):2413–2429

    Article  Google Scholar 

  • Cai YD, Liu DM, Zhang KM et al (2014) Preliminary evaluation of gas content of the No. 2 coal seam in the Yanchuannan area, southeast Ordos basin, China. J Petrol Sci Eng 122:675–689

    Article  Google Scholar 

  • Cao LT, Chang SL, Yao YB (2019) Application of seismic sedimentology in predicating sedimentary microfacies and coalbed methane gas content. J Nat Gas Sci Eng 69:102944

    Article  Google Scholar 

  • Chen S, Zhao WZ, Ge XM et al (2019) Predicting gas content in high-maturity marine shales using artificial intelligence based seismic multiple-attributes analysis: a case study from the lower Silurian Longmaxi Formation, Sichuan Basin, China. Mar Pet Geol 101:180–194

    Article  Google Scholar 

  • Chen YH, Bi JJ, Qiu XB et al (2020) A method of seismic meme inversion and its application. Pet Explor Dev 47(6):1149–1158

    Article  Google Scholar 

  • Cheng GX, Jiang B, Li M et al (2020) Quantitative characterization of fracture structure in coal based on image processing and multifractal theory. Int J Coal Geol 228:103566

    Article  Google Scholar 

  • Gu W, Zhang X, Xu M et al (2017) High precision prediction of thin reservoir under strong shielding effect and its application: a case study from Sanzhao Depression Songliao Basin. Geophys Prospect Pet 56(3):439–448 (in Chinese with English abstract)

    Google Scholar 

  • Guo P, Yuan YJ, Liu XW et al (2018) Inversion method based on high-resolution waveform and its application on predicting sweet spots: an example from shale gas reservoirs in Jiaoshiba area of Sichuan Basin. Geoscience 32(2):406–414 (in Chinese with English abstract)

    Google Scholar 

  • Han CC, Lin CY, Ren LH et al (2017) Application of seismic waveform inversion in beach- bar sandstone in Wangjiagang area, Dongying Depression. J China Univ Pet 41(2):60–69 (in Chinese with English abstract)

    Google Scholar 

  • He HJ, Zhao YN, Zhang ZM et al (2016) Prediction of coalbed methane content based on uncertainty clustering method. Energy Explor Exploit 34(2):273–281

    Article  Google Scholar 

  • Hou SY (2018) Development status of China coalbed methane industry in recent years. China Coalbed Methane 15(1):44–47 (in Chinese with English abstract)

    Google Scholar 

  • Hou XW, Liu SM, Zhu YM et al (2020) Evaluation of gas contents for a multi-seam deep coalbed methane reservoir and their geological controls: in situ direct method versus indirect method. Fuel 265:116917

    Article  Google Scholar 

  • Hu XC, Yang SQ, Zhou XH et al (2014) A quantification prediction model of coalbed methane content and its application in Pannan coalfield, Southwest China. J Nat Gas Sci Eng 21:900–906

    Article  Google Scholar 

  • Kang JQ, Fu XH, Elsworth D et al (2020) Vertical heterogeneity of permeability and gas content of ultra-high-thickness coalbed methane reservoirs in the southern margin of the Junggar Basin and its influence on gas production. J Nat Gas Sci Eng 81:103455

    Article  Google Scholar 

  • Karthikeyan G, Chand J, Chatterjee R (2020) Impact of geomechanics in coal bed methane development and production, Barakar coals in central India. J Pet Sci Eng 194:107515

    Article  Google Scholar 

  • Kędzior S (2019) Distribution of methane contents and coal rank in the profiles of deep boreholes in the Upper Silesian Coal Basin, Poland. Int J Coal Geol 202:190–208

    Article  Google Scholar 

  • Li SJ, Cui Z, Jiang ZX et al (2016) New method for prediction of shale gas content in continental shale formation using well logs. Appl Geophys 13(2):393–405

    Article  Google Scholar 

  • Li DH, Gao X, Liu Z et al (2018a) Comparison and revelation of coalbed methane resources distribution characteristics and development status between China and America. Coal Sci Technol 46(1):252–261 (in Chinese with English abstract)

    Google Scholar 

  • Li S, Tang DZ, Pan ZJ et al (2018b) Geological conditions of deep coalbed methane in the eastern margin of the Ordos Basin, China: implications for coalbed methane development. J Nat Gas Sci Eng 53:394–402

    Article  Google Scholar 

  • Li D, Peng SP, Du WF et al (2019a) New method for predicting coal seam gas content. Energy Sources Part A Recov Util Environ Effects 41(10):1272–1284

    Article  Google Scholar 

  • Li YZ, Wang LB, Guo HJ et al (2019b) Prediction of glutenite reservoir based on seismic waveform indicative inversion: a case study of the upper Wuerhe Formation in Zhongguai-Manan area. Lithol Reserv 31(2):134–142 (in Chinese with English abstract)

    Google Scholar 

  • Lie ZH, Chao HY, Liu Y et al (2018) Development strategy and production characteristics of deep coalbed methane in the east Ordos Basin: taking Daning-Jixian block for example. J China Coal Soc 43(6):1738–1746 (in Chinese with English abstract)

    Google Scholar 

  • Liu HH, Sang SX, Wang GX et al (2014) Block scale investigation on gas content of coalbed methane reservoirs in southern Qinshui basin with statistical model and visual map. J Pet Sci Eng 114:1–14

    Article  Google Scholar 

  • Liu YL, Xu H, Tang DZ et al (2020a) Coalbed methane production of a heterogeneous reservoir in the Ordos Basin, China. J Nat Gas Sci Eng 82:103502

    Article  Google Scholar 

  • Liu YW, Du Y, Li ZQ et al (2020b) A rapid and accurate direct measurement method of underground coal seam gas content based on dynamic diffusion theory. Int J Min Sci Technol 30(9):799–810

    Article  Google Scholar 

  • Lu YL, Wang LJ, Wang YC (2017) Analysis of the development situation and the trend of coalbed methane industry in China. China Min Mag 26(z1):19–22 (in Chinese with English abstract)

    Google Scholar 

  • Men XY, Han Z, Gao BS (2017) Present situation and development suggestions of CBM exploration and development in China. China Min Mag 26(z2):1–4 (in Chinese with English abstract)

    Google Scholar 

  • Men XY, Han Z, Gong HJ et al (2018) Challenges and opportunities of CBM exploration and development in China under new situations. Nat Gas Ind 38(9):10–16 (in Chinese with English abstract)

    Google Scholar 

  • Pan RF, Gao HN, Lei KH et al (2015) Quantitative prediction of coalbed gas content based on seismic multiple-attribute analyses. J Eng Technol Sci 47(4):447–462

    Article  Google Scholar 

  • Pan HJ, Li HB, Grana D et al (2019) Quantitative characterization of gas hydrate bearing sediment using elastic-electrical rock physics models. Mar Pet Geol 105:273–283

    Article  Google Scholar 

  • Paul S, Ali M, Chatterjee R (2021) Prediction of velocity, gas content from neural network modeling and estimation of coal bed permeability from image log in coal bed methane reservoirs: case study of South Karanpura Coalfield, India. Result Geophys Sci 7:100021

    Google Scholar 

  • Shi JX, Zeng LB, Dong SQ et al (2020) Identification of coal structures using geophysical logging data in Qinshui Basin, China: investigation by kernel Fisher discriminant analysis. Int J Coal Geol 217:103314

    Article  Google Scholar 

  • Turnip L, Li XS, Li YH et al (2019) Research and application of high-production area seismic prediction technology for high-rank coalbed methane reservoir. Chem Technol Fuels Oils 55(5):606–614

    Article  Google Scholar 

  • Wang FT, Guo SB (2019) Shale gas content evolution in the Ordos Basin. Int J Coal Geol 211:103231

    Article  Google Scholar 

  • Wang H, Yao YB, Liu DM et al (2016a) Fault-sealing capability and its impact on coalbed methane distribution in the Zhengzhuang field, southern Qinshui Basin, North China. J Nat Gas Sci Eng 28:613–625

    Article  Google Scholar 

  • Wang HJ, Ma F, Tong XG et al (2016b) Assessment of global unconventional oil and gas resources. Pet Explor Dev 63(6):850–862

    Google Scholar 

  • Wei P, Guo CG, Zhao S et al (2019) Determination of appropriate sampling depth of coalbed gas content: a case study. J Geophys Eng 16(2):411–422

    Article  Google Scholar 

  • Xu FY, Xiao ZH, Chen D et al (2019) Current status and development direction of coalbed methane exploration technology in China. Coal Sci Technol 47(10):205–215 (in Chinese with English abstract)

    Google Scholar 

  • Xu HJ, Pan ZJ, Hu BL et al (2020) A new approach to estimating coal gas content for deep core sample. Fuel 277:118246

    Article  Google Scholar 

  • Xue S, Yuan L (2017) The use of coal cuttings from underground boreholes to determine gas content of coal with direct desorption method. Int J Coal Geol 174:1–7

    Article  Google Scholar 

  • Yang T, Yue YX, Wu Y (2018) Application of the waveform inversion in reservoir prediction. Prog Geophys 32(2):769–776 (in Chinese)

    Google Scholar 

  • Zhang S, Huang HD, Dong YP et al (2017) Direct estimation of the fluid properties and brittleness via elastic impedance inversion for predicting sweet spots and the fracturing area in the unconventional reservoir. J Nat Gas Sci Eng 45:415–427

    Article  Google Scholar 

  • Zunu P, Xiang M, Zhang FW (2019) Study on logging interpretation of coal-bed methane content based on deep learning. Acta Geophys 67(2):589–596

    Article  Google Scholar 

Download references

Acknowledgements

The work was financially supported by Chongqing Natural Science Foundation General Program (No. cstc2019jcyj-msxmX0743). Many thanks to PEGETE Group Inc. for providing inversion software.

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Correspondence to Jiabei Wang.

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Edited by Dr. Liang Xiao (ASSOCIATE EDITOR) / Prof. Michał Malinowski (CO-EDITOR-IN-CHIEF).

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Wang, J., Li, Z., Chen, C. et al. Predicting gas content in coalbed methane reservoirs using seismic waveform indication inversion: a case study from the Upper Carboniferous Benxi Formation, eastern Ordos Basin, China. Acta Geophys. 70, 623–638 (2022). https://doi.org/10.1007/s11600-022-00745-3

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  • DOI: https://doi.org/10.1007/s11600-022-00745-3

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