Skip to main content
SpringerLink
Log in

The application of geostatistical inversion in shale lithofacies prediction: a case study of the Lower Silurian Longmaxi marine shale in Fuling area in the southeast Sichuan Basin, China

  • Original Research Paper
  • Published:
Marine Geophysical Research Aims and scope Submit manuscript

Abstract

Based on cores, well logs and seismic data, we established the isochronous sequence stratigraphic framework of the Lower Silurian Longmaxi Formation and predicted the shale lithofacies distribution within the sequence stratigraphic framework using geostatistical inversion. The results of our study show that the Lower Member of the Longmaxi Formation is a third order sequence that includes a transgressive systems tract (TST), an early highstand systems tract (EHST) and a late highstand systems tract (LHST). Four lithofacies units have been recognized, specifically siliceous shale, argillaceous shale, calcareous shale and mixed shale. The results of geostatistical inversion reveal that the TST is characterized by flaky siliceous shale and some sparsely distributed calcareous shale. The EHST is dominated by mixed shale with minor amounts of siliceous shale, which occurs in only a small area. Moreover, in the LHST, argillaceous shale occupies almost the entire study region. Comparing to traditional geological research with geophysical research, the vertical resolution of the predictive results of geostatistical inversion could reach 1–2 m. Geostatistical inversion effectively solves the problem of precisely identifying the lithofacies in the Fuling shale gas field and predicting their spatial distribution. This successful study showcases the potential of this method for carrying out marine shale lithofacies prediction in China and other locations with similar geological backgrounds.

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

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14
Fig. 15
Fig. 16
Fig. 17
Fig. 18

Similar content being viewed by others

References

  • Aplin AC, Macquaker JHS (2011) Mudstone diversity: Origin and implications for source, seal, and reservoir properties in petroleum systems. AAPG Bull 95(12):2031–2059. doi:10.1306/03281110162

    Article  Google Scholar 

  • Bosch M, Mukerji T, Gonzalez EF (2010) Seismic inversion for reservoir properties combining statistical rock physics and geostatistics: a review. Geophysics 75(5):75A165–75A176. doi:10.1190/1.3478209

    Article  Google Scholar 

  • Campbell TJ, Richards FWB, Silva RL, Wach G, Eliuk L (2015) Interpretation of the penobscot 3d seismic volume using constrained sparse spike inversion, sable sub-basin, offshore nova scotia. Mar Pet Geol 68:73–93. doi:10.1016/j.marpetgeo.2015.08.009

    Article  Google Scholar 

  • Challands TJ, Armstrong HA, Maloney DP, Davies JR, Wilson D, Owen AW (2009) Organic-carbon deposition and coastal upwelling at mid-latitude during the Upper Ordovician (Late Katian): a case study from the Welsh Basin, UK. Palaeogeogr Palaeoclimatol Palaeoecol 273(3–4):395–410. doi:10.1016/j.palaeo.2008.10.004

    Article  Google Scholar 

  • Chen X, Rong JY, Li Y, Boucot AJ (2004) Facies patterns and geography of the Yangtze region, South China, through the Ordovician and Silurian transition. Palaeogeogr Palaeoclimatol Palaeoecol 204(3):353–372. doi:10.1016/S0031-0182(03)00736-3

    Google Scholar 

  • Chen X, Melchin MJ, Sheets HD, Mitchell CE, Fan JX (2005) Patterns and process of latest Ordovician graptolite extinction and recovery based on data from South China. J Paleontol 79(5):842–861. doi:10.1666/0022-3360(2005)079[0842:PAPOLO]2.0.CO;2

    Article  Google Scholar 

  • Chen SB, Zhu YM, Wang HY, Liu HL, Wei W, Fang JH (2012a) Structure characteristics and accumulation significance of nanopores in Longmaxi shale gas reservoir in the southern Sichuan Basin. J China Coal Soc 37:438–444 (Chinese with English abstract)

    Google Scholar 

  • Chen H, Xie XN, Hu CY, Huang JH, Li HJ (2012b) Geochemical characteristics of late Permian sediments in the Dalong formation of the Shangsi section, Northwest Sichuan Basin in south China: implications for organic carbon-rich siliceous rocks formation. J Geochem Explor 112(1):35–53. doi:10.1016/j.gexplo.2011.06.011

    Article  Google Scholar 

  • Chen L, Lu YC, Jiang S, Li JQ, Guo TL, Xing FC (2015) Sequence stratigraphy and its application in marine shale gas exploration: a case study of the Lower Silurian Longmaxi Formation in the Jiaoshiba shale gas field and its adjacent area in southeast Sichuan Basin, SW China. J Nat Gas Sci Eng 27(2):410–423. doi:10.1016/j.jngse.2015.09.016

    Article  Google Scholar 

  • Correia P, Azevedo L, Nunes RFM, Soares A, Guerreiro L, Neto GS (2014) Multidimensional scaling for the evaluation of a geostatistical seismic elastic inversion methodology. Geophysics 79(1):M1–M10. doi:10.1190/geo2013-0037.1

    Article  Google Scholar 

  • Dafflon B, Irving J, Barrash W (2010) Inversion of multiple intersecting high-resolution crosshole GPR profiles for hydrological characterization at the boise hydrogeophysical research site. J Appl Geophys 73(4):305–314. doi:10.1016/j.jappgeo.2011.02.001

    Article  Google Scholar 

  • Dubrule O, Thibaut M, Lamy P, Hass A (1998) Geostatistical reservoir characterization constrained by 3D seismic data. Pet Geosci 4(2):121–128. doi:10.1144/petgeo.4.2.121

    Article  Google Scholar 

  • Guo TL, Zhang HR (2014) Formation and enrichment mode of Jiaoshiba shale gas field, Sichuan Basin. Pet Explor Dev 41(1):31–40. doi:10.1016/S1876-3804(14)60003-3

    Article  Google Scholar 

  • Hass A, Dubrule O (1994) Geostatistical inversion-A sequential method for stochastic reservoir modeling constrained by seismic data. First Break 12(11):561–569. doi:10.3997/1365-2397.1994034

    Google Scholar 

  • Helgesen J (2000) Comparison of constrained sparse spike and stochastic inversion for porosity prediction at kristin field. Leading Edge, 19(4), 400, 403–404, 406–407

  • John S (1986) Lithofacies types and vertical profile models; an alternative approach to the description and environmental interpretation of glacial diamict and diamictic sequences. Sedimentology 33(1):151–155. doi:10.1111/j.1365-3091.1986.tb00751.x

    Article  Google Scholar 

  • John AK, Lake LW, Torres-Verdin C, Srinivasan S (2008) Seismic facies identification and classification using simple statistics. SPE Reserv Eval Eng 11(6):984–990. doi:10.2118/96577-PA

    Article  Google Scholar 

  • Kadkhodaie-Ilkhchi A, Monteiro ST, Ramos F, Hatherly P (2010) Rock recognition from MWD data: a comparative study of boosting, neural networks, and fuzzy logic. IEEE Geosci Remote Sens Lett 7(4):680–684. doi:10.1109/LGRS.2010.2046312

    Article  Google Scholar 

  • Kametaka M, Takebe M, Nagai H, Zhu SZ, Takayanagi Y (2005) Sedimentary environments of the Middle Permian phosphorite–chert complex from the northeastern Yangtze platform, China; the Gufeng Formation: a continental shelf radiolarian chert. Sediment Geol 174(3–4):197–222. doi:10.1016/j.sedgeo.2004.12.005

    Article  Google Scholar 

  • Larsen AL, Ulvmoen M, Omre H, Buland A (2006) Bayesian lithology/fluid prediction and simulation on the basis of a Markov-chain prior model. Geophysics 71(5):R69–R78. doi:10.1190/1.2245469

    Article  Google Scholar 

  • Liang DG, Guo TL, Bian LZ, Chen JP, Zhao Z (2009) Some progress on studies of hydrocarbon generation and accumulation in marine sedimentary regions, Southern China (part 3): controlling factors on the sedimentary facies and development of Palaeozoic marine source rocks. Mar Orig Pet Geol 14:1–19 (Chinese with English abstract)

    Google Scholar 

  • Liu SG, Wang SY, Sun Y, Ran B, Yang D, Luo C, Ye YH, Bai ZQ, Qiu JW, Zhang X (2013) Characteristics of black shale in Wufneg Formation and Longmaxi Formation in Sichuan Basin and its Peripheral areas. J Chengdu Univ Technol 40(6):621–639 (in Chinese with English abstract). doi:10.3969/j.issn.1671-9727.2013.06.02

    Google Scholar 

  • Loucks RG, Ruppel SC (2007) Mississippian Barnett Shale: Lithofacies and depositional setting of a deep-water shale-gas succession in the Fort Worth Basin, Texas. AAPG Bulletin 91(4):579–601

    Article  Google Scholar 

  • Ma YQ, Fan MJ, Lu YC, Guo XS, Hu HY, Chen L, Wang C, Liu XC (2016) Geochemistry and sedimentology of the lower silurian longmaxi mudstone in southwestern china: implications for depositional controls on organic matter accumulation. Mar Pet Geol 75:291–309. doi:10.1016/j.marpetgeo.2016.04.024

    Article  Google Scholar 

  • Ma YQ, Fan MJ, Lu YC, Liu HM, Hao YQ, Xie ZH, Peng L, Du XB, Hu HY (2017) Middle Eocene paleohydrology of the Dongying depression in eastern China from sedimentological and geochemical signatures of lacustrine mudstone. Palaeogeogr Palaeoclimatol Palaeoecol. doi:10.1016/j.palaeo.2017.04.011

    Google Scholar 

  • Maiti S, Tiwari RK (2009) A Hybrid Monte Carlo method based artificial neural networks approach for rock boundaries identification: a case study from KTB borehole. Pure Appl Geophys 166:2059–2090. doi:10.1007/s00024-009-0533-y

    Article  Google Scholar 

  • Maiti S, Tiwari RK (2010a) Automatic discriminations among geophysical signals via the Bayesian neural networks approach. Geophysics 3298501(1):2010

    Google Scholar 

  • Maiti S, Tiwari RK (2010b) Neural network modeling and an uncertainty analysis in Bayesian framework: a case study from the KTB borehole site. J Geophys Res 115:B10208. doi:10.1029/2010JB000864

    Article  Google Scholar 

  • Maiti S, Tiwari RK, Kuempel H-J (2007) Neural network modeling and classification of litho-facies using well log data: a case study from KTB borehole site. Geophys J Int. doi:10.1111/j.1365-246X.2007.03342.x

    Google Scholar 

  • Ojha M, Maiti S (2013) Sediment classification using neural networks: an example from the site-U1344A of IODP Expedition 323 in the Bering Sea. Deep-Sea Research Part II: topical Studies. Oceanography 125–126(7):202–213. doi:10.1016/j.dsr2.2013.03.024

    Google Scholar 

  • Riboulleau A, Baudin F, Deconinck J-F, Derenne S, Largeau C, Tribovillard N (2003) Depositional conditions and organic matter preservation pathways in an epicontinental environment: the Upper Jurassic Kashpir Oil Shales (Volga Basin, Russia). Palaeogeogr Palaeoclimatol Palaeoecol 197(3–4):171–197. doi:10.1016/S0031-0182(03)00460-7

    Article  Google Scholar 

  • Rimstad K, Omre H (2009) Impact of rock-physics depth trends and Markov random fields on hierarchical Bayesian lithology/fluid prediction. Geophysics 75(4):R93–R108. doi:10.1190/1.3463475

    Article  Google Scholar 

  • Rong JY, Chen X, Wang Y (2011) Northward expansion of Central Guizhou Oldland through the Ordovician and Silurian transition: evidence and implications. Sci China Earth Sci 41(10):1407–1415 (Chinese with English abstract)

    Google Scholar 

  • Slatt RM, Rodriguez ND (2012) Comparative sequence stratigraphy and organic geochemistry of gas shales: commonality or coincidence. J Nat Gas Sci Eng 8:68–84. doi:10.1016/j.jngse.2012.01.008

    Article  Google Scholar 

  • Tang H, White CD (2008) Multivariate statistical log log-facies classification on a shallow marine reservoir. J Petrol Sci Eng 61(2):88–93. doi:10.1016/j.petrol.2008.05.004

    Article  Google Scholar 

  • Tian H, Pan L, Xiao XM, Wilkins RWT, Meng ZP, Huang BJ (2013) A preliminary study on the pore characterization of Lower Silurian black shales in Chuandong Thrust Fold Belt, southwestern China using low pressure N2 adsorption and FE-SEM methods. Mar Pet Geol 48:8–19. doi:10.1016/j.marpetgeo.2013.07.008

    Article  Google Scholar 

  • Ulvmoe M, Omre H, Buland A (2010) Improved resolution in Bayesian lithology/fluid inversion from prestack seismic data and well observations: Part 2-Real case study. Geophysics 75(2):B73–B82. doi:10.1190/1.3335332

    Article  Google Scholar 

  • Vernengo L, Czeplowodzki R, Trinchero E, Sabaté A, Tsybulkina I, Morillo F (2014) Improvement of the reservoir characterization of fluvial sandstones with geostatistical inversion in Golfo San Jorge Basin, Argentina. Lead Edge 33(5):508–518. doi:10.1190/tle33050508.1

    Article  Google Scholar 

  • Wang GC, Carr TR (2012a) Methodology of organic-rich shale lithofacies identification and prediction: a case study from Marcellus Shale in the Appalachian Basin. Comput Geosci 49:151–163. doi:10.1016/j.cageo.2012.07.011

    Article  Google Scholar 

  • Wang GC, Carr TR (2012b) Marcellus Shale Lithofacies Prediction by Multiclass Neural Network Classification in the Appalachian Basin. Math Geosci 44(8):975–1004. doi:10.1007/s11004-012-9421-6

    Article  Google Scholar 

  • Wang GC, Carr TR (2013) Organic-rich marcellus shale lithofacies modeling and distribution pattern analysis in the appalachian basin. AAPG Bull 97(12):2173–2205

    Article  Google Scholar 

  • Wang YM, Dong DZ, Yang H, He L, Wang SQ, Huang JL, Pu BL, Wang SF (2013) Quantitative characterization of reservoir space in the Lower Silurian Longmaxi shale, southern Sichuan, China. Science China. Earth Sci 57(2):313–322. doi:10.1007/s11430-013-4645-y

    Google Scholar 

  • Wang GC, Ju YW, Can TR, Tian FQ (2015) The hierarchical decomposition method and its application in recognizing Marcellus Shale lithofacies through combining with neural network. J Pet Sci Eng 127:469–481. doi:10.1016/j.petrol.2015.02.006

    Article  Google Scholar 

  • Xu XS, Liu W, Zhou DK, Wang GS, Zhang HQ, Shi GS (2009) Sedimentary facies of the Lower Silurian in central and southeastern Guizhou Province. J Palaeogeogr 11(1):13–20 (Chinese with English abstract)

    Google Scholar 

  • Zhang R, Castagna J (2011) Seismic sparse-layer reflectivity inversion using basis pursuit decomposition. Geophysics 76(6):147. doi:10.1190/geo2011-0103.1

    Article  Google Scholar 

  • Zhang TW, Ellis GS, Ruppel SC, Milliken K, Yang R (2012) Effect of organic-matter type and thermal maturity on methane adsorption in shale-gas systems. Org Geochem 47(6):120–131. doi:10.1016/j.orggeochem.2012.03.012

    Article  Google Scholar 

  • Zhao LX, Geng JH, Cheng JB, Han DH, Guo TL (2014) Probabilistic lithofacies prediction from prestack seismic data in a heterogeneous carbonate reservoir. Geophysics 79(5):M25–M34. doi:10.1190/geo2013-0406.1

    Article  Google Scholar 

Download references

Acknowledgements

This study was funded by National Key Research Program of China (973 program) (2014CB239102), National Key Projects of Oil and Gas (2016ZX05034), National Natural Science Foundation of China (NSFC) programs (No. 41602147). Our special thanks are extended to Editor Roger Urgeles, as well as three anonymous reviewers, for many critical and constructive comments.

Author information

Authors and Affiliations

  1. Key Laboratory of Tectonics and Petroleum Resources of Ministry of Education, China University of Geosciences, Wuhan, 430074, China

    Xiaochen Liu, Yangbo Lu, Yongchao Lu & Yiquan Ma

  2. Faculty of Earth Resources, China University of Geosciences, Wuhan, 430074, China

    Xiaochen Liu, Yangbo Lu, Yongchao Lu & Yiquan Ma

  3. School of Geoscience and Technology, Southwest Petroleum University, Chengdu, 610500, China

    Lei Chen

  4. Petroleum Exploration and Development, Jianghan Oilfield Branch Company, Sinopec, Wuhan, 430223, China

    Chao Wang

Authors
  1. Xiaochen Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Yangbo Lu
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Yongchao Lu
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Lei Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Yiquan Ma
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Chao Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Yangbo Lu.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Liu, X., Lu, Y., Lu, Y. et al. The application of geostatistical inversion in shale lithofacies prediction: a case study of the Lower Silurian Longmaxi marine shale in Fuling area in the southeast Sichuan Basin, China. Mar Geophys Res 39, 421–439 (2018). https://doi.org/10.1007/s11001-017-9317-4

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11001-017-9317-4

Keywords

Search

Navigation