Skip to main content
SpringerLink
Log in

Accurate Prediction of the Macrolithotype of a High-Rank Coal Reservoir by Logging Interpretation: A Case Study of the Junlian Block, Sichuan Province, China

  • Original Paper
  • Published:
Natural Resources Research Aims and scope Submit manuscript

Abstract

Macrolithotypes control the non-homogeneity of coal reservoirs, and it is important to grasp their distribution patterns for the exploration and development of coalbed methane (CBM). Traditional evaluation of macrolithotypes often relies on drilling cores and downhole workings, which are costly and difficult for obtaining comprehensive physical properties of coal seams. In recent years, geophysical logging technology has been commonly applied for evaluating physical properties of coal reservoirs because of its high efficiency and economic features. Taking the Junlian block in Sichuan province as a case study, based on many CBM evaluation wells and data analysis, a logging prediction method for the macrolithotypes of a high-rank coal reservoir is established. The problem of "boundary effect" is solved by the Haar wavelet analysis. Through a Pearson correlation coefficient matrix combined with backpropagation neural network analysis, density, natural gamma ray, acoustic time, compensated neutron, and deep lateral resistivity are extracted as critical parameters for constructing the method of logging interpretation of macrolithotypes. Logging identification models of different macrolithotypes are established by principal components analysis. Based on the results of logging interpretation, the macrolithotypes in the study area are mainly semi-dull coal and semi-bright coal. The genesis of macrolithotypes is analyzed by trace elements and lithologic characteristics. The bright coal in the study area is formed in a sedimentary environment of low paleotemperature, high anaerobic, saline water, and low sea level. In contrast, dull coal is formed in a sedimentary environment of relatively high sea level, brackish water, relatively rich oxygen, and relatively high paleotemperature.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Figure 1
Figure 2
Figure 3
Figure 4
Figure 5
Figure 6
Figure 7
Figure 8
Figure 9
Figure 10
Figure 11
Figure 12
Figure 13
Figure 14
Figure 15
Figure 16

Similar content being viewed by others

References

  • Austin, S. A. (1979). Depositional environment of the Kentucky No. 12 coal bed (middle Pennsylvanian) of western Kentucky, with special reference to the origin of coal lithotypes. Pennsylvania State University.

  • Cameron, A. R. (1978). Megascopic description of coal with particular reference to seams in southern Illinois. https://doi.org/10.1520/STP35763S

  • Cao, X., Mastalerz, M., Chappell, M. A., Miller, L. F., Li, Y., & Mao, J. (2011). Chemical structures of coal lithotypes before and after CO2 adsorption as investigated by advanced solid-state 13C nuclear magnetic resonance spectroscopy. International Journal of Coal Geology, 88, 67–74.

    Article  Google Scholar 

  • Chao, R., Ning, A., Wang, J., Lian, L., Hu, B., & Shang, D. (2014). Optimal parameters selection for BP neural network based on particle swarm optimization: A case study of wind speed forecasting. Knowledge-Based System, 56, 226–239.

    Article  Google Scholar 

  • Clarkson, C. R., & Bustin, R. M. (1997). Variation in permeability with lithotype and maceral composition of Cretaceous coals of the Canadian Cordillera. International Journal of Coal Geology, 33, 135–151.

    Article  Google Scholar 

  • Crosdale, P. J. (1995). Lithotype sequences in the early miocene maryville coal measures, New Zealand. International Journal of Coal Geology, 28, 37–50s.

    Article  Google Scholar 

  • Cui, C., Chang, S., Yao, Y., & Cao, L. (2021). Quantify coal macrolithotypes of a whole coal seam: A method combing multiple geophysical logging and principal component analysis. Energies, 14, 1–19.

    Article  Google Scholar 

  • Davis, A. (1978). Compromise in coal seam description. https://doi.org/10.1520/STP35764S

  • Esterle, J. S., & Ferm, J. C. (1986). Relationship between petrographic and chemical properties and coal seam geometry, Hance seam, breathitt formation, southeastern Kentucky. International Journal of Coal Geology, 6, 199–214.

    Article  Google Scholar 

  • Fu, X., Qin, Y., Wang, G. G. X., & Rudolph, V. (2009). Evaluation of coal structure and permeability with the aid of geophysical logging technology. Fuel, 88, 2278–2285.

    Article  Google Scholar 

  • Ghosh, S., Chatterjee, R., Paul, S., & Shanker, P. (2014). Designing of plug-in for estimation of coal proximate parameters using statistical analysis and coal seam correlation. Fuel, 134, 63–73.

    Article  Google Scholar 

  • Ghosh, S., Chatterjee, R., & Shanker, P. (2016). Estimation of ash, moisture content and detection of coal lithofacies from well logs using regression and artificial neural network modelling. Fuel, 177, 279–287.

    Article  Google Scholar 

  • Gryglewicz, G., Boudou, J., Boulègue, J., Machnikowska, H., & Jasieńko, S. (1995). Sulfur characterization of Polish coals, their lithotypes and macerals. Fuel, 74, 349–355.

    Article  Google Scholar 

  • Hou, H., Shao, L., Guo, S., Li, Z., Zhang, Z., Yao, M., Zhao, S., & Yan, C. (2017). Evaluation and genetic analysis of coal structures in deep Jiaozuo Coalfield, northern China: Investigation by geophysical logging data. Fuel, 209, 552–566.

    Article  Google Scholar 

  • Hou, H., Shao, L., Tang, Y., Li, Z., Zhao, S., Yao, M., Wang, X., & Zhang, J. (2023a). Pore structure characterization of middle- and high-ranked coal reservoirs in northern china. AAPG Bulletin, 107(2), 213–241.

    Article  Google Scholar 

  • Hou, H., Shao, L., Tang, Y., Li, Y., Liang, G., Xin, Y., & Zhang, J. (2023b). Coal Seam Correlation in Terrestrial Basins by Sequence Stratigraphy and Its Implications for Paleoclimate and Paleoenvironment Evolution. Journal of Earth Science, 34(2), 556–570.

    Article  Google Scholar 

  • Hou, H., Zhang, H., Shao, L., Guo, S., Zhao, M. E., & Wang, S. (2021). Coal macrolithotype distribution and its genetic analyses in the deep jiaozuo coalfield using geophysical logging data. ACS Omega, 6, 35523–35537.

    Article  Google Scholar 

  • Hower, J. C., & Esterle, J. S. (1989). Coal lithotype analysis: Problems and potential.

  • Jr. Degenhardt, J. J., Ali, S., Ali, M., Chin, B., Jr. Von Gonten, W. D., & Peavey, E. (2021). Reservoir scale chemostratigraphy and facies modeling using high sample rate geophysical scans of whole core. In SPWLA 62nd Annual Logging Symposium, pp. D17S-D21S. https://doi.org/10.30632/SPWLA-2021-0051

  • Kang, J., Fu, X., Shen, J., Liang, S., Chen, H., & Shang, F. (2022). Characterization of coal structure of high-thickness coal reservoir using geophysical logging: A Case Study in Southern Junggar Basin, Xinjiang, Northwest China. Natural Resources Research, 31, 929–951.

    Article  Google Scholar 

  • Li, L. J., Liu, D. M., Cai, Y. D., Wang, Y. J., & Jia, Q. F. (2021). Coal structure and its implications for coalbed methane exploitation: A review. Energy & Fuels, 35, 86–110.

    Article  Google Scholar 

  • Li, R., Ma, Y., Guo, T., Li, Y., & Hu, J. (2006). The marine character of the sedimentation and geochemistry of the upper Triassic in the Chuxiong Basin, Yunnan. Acta Geologica Sinica, 80(3), 374–381.

    Google Scholar 

  • Liu, B. (2005). The division and features of macroscopic coal petrography of Huolinhe coalfield. Coal Technology, 11(24), 103–105.

    Google Scholar 

  • Liu, G. (2021). Challenges and countermeasures of log evaluation in unconventional petroleum exploration and development. Petroleum Explor. Dev, 48, 1033–1047.

    Article  Google Scholar 

  • Liu, X., Deng, Z., & Wang, T. (2011). Real estate appraisal system based on GIS and BP neural network. Transactions of the Nonferrous Metals Society of China, 213, S626–S630.

    Article  Google Scholar 

  • Liu, Y., Xu, H., Tang, D., Mathews, J. P., Zhai, Y., Hou, W., Li, S., Tao, S., Xiong, X., & Wang, W. (2019). The impact of the coal macrolithotype on reservoir productivity, hydraulic fracture initiation and propagation. Fuel, 239, 471–483.

    Article  Google Scholar 

  • Liu, Z., & Zhao, J. (2016). Quantitatively evaluating the CBM reservoir using logging data. Journal of Geophysics and Engineering, 13, 59–69.

    Article  Google Scholar 

  • Lu, S., Wang, S., Liu, H., Li, R., Dong, Q., Xiao, H., & Shen, P. (2020). Analysis of the influence of natural fracture system on hydraulic fracture propagation morphology in coal reservoir. Journal of China Coal Society, 45(7), 2590–2601.

    Google Scholar 

  • Mares, T. E., & Moore, T. A. (2008). The influence of macroscopic texture on biogenically-derived coalbed methane, Huntly coalfield. New Zealand. Int. J. Coal Geol, 76, 175–185.

    Article  Google Scholar 

  • Markova, K., Shopova, N., & Valceva, S. (1995). Investigation of low-temperature autooxidation processes in bituminous coal lithotypes. Thermochimica Acta, 265, 111–117.

    Article  Google Scholar 

  • Mastalerz, M., Drobniak, A., & Filippelli, G. (2006). Mercury content and petrographic composition in Pennsylvanian coal beds of Indiana, USA. International Journal of Coal Geology, 68, 2–13.

    Article  Google Scholar 

  • Mastalerz, M., Drobniak, A., Walker, R., & Morse, D. (2010). Coal lithotypes before and after saturation with CO2; insights from micro- and mesoporosity, fluidity, and functional group distribution. International Journal of Coal Geology, 83, 467–474.

    Article  Google Scholar 

  • Moore, T. A. (2012). Coalbed methane: A review. International Journal of Coal Geology, 101, 36–81.

    Article  Google Scholar 

  • Nguyen, T. C., & Reynolds, & K.J.,. (2009). Principal Component Analysis of Lifting Kinematics and Kinetics in Pregnant Subjects. Springer, Berlin Heidelberg, 2009, 1888–1891.

    Google Scholar 

  • Pearson, K. (1895). Note on Regression and Inheritance in the Case of Two Parents. Proceedings of the Royal Society of London, 58, 240–242.

    Article  Google Scholar 

  • Qin, Y., Moore, T. A., Shen, J., Yang, Z., Shen, Y., & Wang, G. (2017). Resources and geology of coalbed methane in China: a review. International Geologiy Review, 60, 777–812.

    Article  Google Scholar 

  • Ren, C., An, N., Wang, J., Li, L., Hu, B., & Shang, D. (2014). Optimal parameters selection for BP neural network based on particle swarm optimization: A case study of wind speed forecasting. Knowledge-Based Syst, 56, 226–239.

    Article  Google Scholar 

  • Ren, P., Xu, H., Tang, D., Li, Y., Sun, C., Tao, S., Li, S., Xin, F., & Cao, L. (2018). The identification of coal texture in different rank coal reservoirs by using geophysical logging data in northwest Guizhou, China: Investigation by principal component analysis. Fuel (Guildford), 230, 258–265.

    Article  Google Scholar 

  • Rhoads, D. C., & Morse, J. W. (1971). Evolutionary and ecologic significance of oxygen-deficient marine basins. Lethaia, 4, 413–428.

    Article  Google Scholar 

  • Rimmer, S. M. (2004). Geochemical paleoredox indicators in Devonian-Mississippian black shales, Central Appalachian Basin (USA). Chemical Geology, 206, 373–391.

    Article  Google Scholar 

  • Rumelhart, D. E., Hinton, G. E., & Williams, R. J. (1986). Learning representations by back-propagating errors. Nature (London), 323, 533–536.

    Article  Google Scholar 

  • Schober, P., Boer, C., & Schwarte, L.A., (2018). Correlation Coefficients: Appropriate Use and Interpretation. Anesthesia & Analgesia. https://doi.org/10.1213/ANE.0000000000002864.

  • Scholes, P.L., & Johnston, D. (1993). Coalbed Methane Applications of Wireline Logs. In: Law, B.E., Rice, D.D. (Eds.), Hydrocarbons from Coal. American Association of Petroleum Geologists.https://doi.org/10.1306/St38577C13.

  • Stankovic, R. S., & Falkowski, B. J. (2003). The Haar wavelet transform: its status and achievements. Computers & Electrical Engineering, 29, 25–44.

    Article  Google Scholar 

  • Stollnitz, E. J., Derose, T. D., & Salesin, D. H. (1994). Wavelets for Computer Graphics: A Primer. IEEE Computer Graphics and Applications, 15, 76–84.

    Article  Google Scholar 

  • Tang, D., Qin, Y., & Hu, A. (2003). Advances and tendencies in geological researches on coalbed methane. Exp. Pet. Geol, 06, 644–647.

    Google Scholar 

  • Tao, S., Pan, Z., Chen, S., & Tang, S. (2019). Coal seam porosity and fracture heterogeneity of marcolithotypes in the Fanzhuang Block, southern Qinshui Basin. China. J. Nat. Gas Sci. Eng., 66, 148–158.

    Article  Google Scholar 

  • Teng, J., Yao, Y., Liu, D., & Cai, Y. (2015). Evaluation of coal texture distributions in the southern Qinshui basin, North China: Investigation by a multiple geophysical logging method. International Journal of Coal Geology, 140, 9–22.

    Article  Google Scholar 

  • Wang, X. (2021). Advances in formation evaluation and well logging technology: overview of the SPWLA 62nd annual logging symposium. Well Logging Technol, 45(05), 451–458.

    Google Scholar 

  • Wang, Y., Liu, D., Cai, Y., Yao, Y., & Zhou, Y. (2018). Evaluation of structured coal evolution and distribution by geophysical logging methods in the Gujiao Block, northwest Qinshui basin. China. J. Nat. Gas Sci. Eng, 51, 210–222.

    Article  Google Scholar 

  • Wang, Z., Hower, J. C., Ferm, J. C., & Wild, G. D. (1996). Characteristics of lithotype thickness and sequential association of some Kentucky coals. Organic Geochemistry, 24, 189–195.

    Article  Google Scholar 

  • Wei, W., Algeo, T. J., Lu, Y., Lu, Y., Liu, H., Zhang, S., Peng, L., Zhang, J., & Chen, L. (2018). Identifying marine incursions into the Paleogene Bohai Bay Basin lake system in northeastern China. International Journal of Coal Geology, 200, 1–17.

    Article  Google Scholar 

  • Xu, H., Tang, D., Zhao, J., Tao, S., Li, S., & Fang, Y. (2015). Geologic controls of the production of coalbed methane in the Hancheng area, southeastern Ordos Basin. J. Nat. Gas Sci. Eng, 26, 156–162.

    Article  Google Scholar 

  • Yang, S., Fu, Q., Liu, J., Ma, W., Yang, B., Zhu, Z., & Teng, W. (2022). Geochemical Characteristics and Environmental Implications of Trace Elements of the Paleocene in the West Lishui Sag. East China Sea Basin. Energies, 15(15), 5748.

    Google Scholar 

  • Yuan, M., Lyu, S., Wang, S., Xu, F., & Yan, X. (2022). Macrolithotype controls on natural fracture characteristics of ultra-thick lignite in Erlian Basin, China: Implication for favorable coalbed methane reservoirs. Journal of Petroleum Science and Engineering, 208, 109598.

    Article  Google Scholar 

  • Zhang, Q., & Pan, Z. (1999). Establishment of macroscopic classification system for bituminous coal in China. Coal Geol. Explor, 02, 3–6.

    Google Scholar 

  • Zhang, Z., Qin, Y., Wang, G., Sun, H., You, Z., Jin, J., & Yang, Z. (2021). Evaluation of Coal Body Structures and Their Distributions by Geophysical Logging Methods: Case Study in the Laochang Block, Eastern Yunnan, China. Natural Resources Research, 30, 2225–2239.

    Article  Google Scholar 

  • Zhao, H., Wang, X., & Liu, Z. (2019a). Experimental investigation of hydraulic sand fracturing on fracture propagation under the influence of coal macrolithotypes in Hancheng block. China. J. Pet. Sci. Eng., 175, 60–71.

    Article  Google Scholar 

  • Zhao, J., Tang, D., Qin, Y., & Xu, H. (2019b). Fractal characterization of pore structure for coal macrolithotypes in the Hancheng area, southeastern Ordos Basin. China. J. Pet. Sci. Eng, 178, 666–677.

    Article  Google Scholar 

Download references

Acknowledgments

Financial support for this work was provided by the National Natural Science Foundation of China (42272195, 42130802), the 14th Five-Year Plan of China National Petroleum Corporation (CNPC), the Research on CBM Exploration and Development Technology, Sub-project 3 of the “New Bedding System and New Field Strategy and Evaluation Technology for New CBM Regions” (2021DJ2303) and Key Laboratory of Coalbed Methane Resources and Reservoir Formation Process of the Ministry of Education (China University of Mining and Technology) (No. 2022-0012).

Author information

Authors and Affiliations

  1. Key Laboratory of Coalbed Methane Resources and Reservoir Formation Process, Ministry of Education, China University of Mining and Technology, Xuzhou, 221008, Jiangsu, China

    Cunlei Li, Zhaobiao Yang, Changqing Liu, Benju Lu, Yuhui Liang & Junyu Gu

  2. Department of Unconventionals, Research Institute of Petroleum Exploration and Development, PetroChina, Langfang, 065007, Hebei, China

    Wenguang Tian

  3. PetroChina Zhejiang Oilfield Company, CNPC, Hangzhou, 310023, Zhejiang, China

    Lisha Peng & Langlang Liu

  4. School of Resource and Geosciences, China University of Mining and Technology, Xuzhou, 221116, Jiangsu, China

    Cunlei Li, Zhaobiao Yang, Changqing Liu, Benju Lu, Yuhui Liang & Junyu Gu

Authors
  1. Cunlei Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Zhaobiao Yang
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Wenguang Tian
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Lisha Peng
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Langlang Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Changqing Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Benju Lu
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Yuhui Liang
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Junyu Gu
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Zhaobiao Yang.

Ethics declarations

Conflict of Interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Li, C., Yang, Z., Tian, W. et al. Accurate Prediction of the Macrolithotype of a High-Rank Coal Reservoir by Logging Interpretation: A Case Study of the Junlian Block, Sichuan Province, China. Nat Resour Res 32, 2289–2311 (2023). https://doi.org/10.1007/s11053-023-10233-0

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11053-023-10233-0

Keywords

Search

Navigation