Abstract
Thrace Basin is one of the most significant coalfields due to the lignite reservoir in Turkey. A coal deposit was chosen as the study area in the Thrace coal basin, which is tertiary within Oligocene geological formation. The purpose of this study is to produce modeling of coal seams in the study area and to create spatial distribution maps for estimation of lignite coal resource characteristics using geostatistical methods with Geographic Information System (GIS) technology. Spatial continuity of the coal depth data was forecasted with an empirical variogram. The performance of six different models has been compared for ordinary kriging separately for both skewed data and transformed data according to the presence and absence of the trend. Spatial structure of the coal depth data was better explained using circular models. The nugget-sill ratio was indicated high spatial dependency with 0.002 and 0.009 for upper-lower surfaces of coal seams respectively. The estimations obtained for coal depth data were represented in a map. In the study area modeled with ordinary kriging method, it was estimated that there was a 17,516,997 m3 coal reserve as a result of the reserve calculation made with ArcGIS 10 software.
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Authors are thankful to “BKİ Batı Kömür İşletmeleri A.Ş” for providing exploration data, vital for conduct of this academic research.
References
Akbar DA (2012) Reserve estimation of central part of Choghart north anomaly iron ore deposit through ordinary kriging method. Int J Min Sci Technol 22(4):573–577
Arétouyap Z, Nouck PN, Nouayou R, Kemgang FEG, Toko ADP, Asfahani J (2016) Lessening the adverse effect of the semivariogram model selection on an interpolative survey using kriging technique. SpringerPlus 5(1):1–11
Boisvert JB, Manchuk JG, Deutsch CV (2009) Kriging in the presence of locally varying anisotropy using non-Euclidean distances. Math Geosci 41(5):585–601
Cichon J (2016) Using kriging to generate a potentiometric surface of the upper Floridan aquifer. Florida Scientist 79:257–226
Dursun AE (2020) Statistical analysis of methane explosions in Turkey’s underground coal mines and some recommendations for the prevention of these accidents: 2010-2017. Nat Hazards 104(1):329–351. https://doi.org/10.1007/s11069-020-04170-x
Ertunc G, Tercan AE, Hindistan MA, Unver B, Unal S, Atalay F, Kıllıoglu SY (2013) Geostatistical estimation of coal quality variables by using covariance matching constrained kriging. Int J Coal Geol 112:14–25. https://doi.org/10.1016/j.coal.2012.11.014
Falivene O, Cabrera L, Sáez A (2007) Optimum and robust 3D facies interpolation strategies in a heterogeneous coal zone (tertiary As Pontes basin, NW Spain). Int J Coal Geol 71:185–208. https://doi.org/10.1016/j.coal.2006.08.008
Falivene O, Cabrera L, Sáez A (2014) Forecasting coal resources and reserves in heterogeneous coal zones using 3D facies models (As Pontes Basin, NW Spain). Int J Coal Geol 130:8–26. https://doi.org/10.1016/j.coal.2014.05.001
Gaus I, Kinniburgh DG, Talbot JC, Webster R (2003) Geostatistical analysis of arsenic concentration in groundwater in Bangladesh using disjunctive kriging. Environ Geol 44(8):939–948. https://doi.org/10.1007/s00254-003-0837-7
Gharechelou S, Tateishi R, Sharma RC, Johnson BA (2016) Soil moisture mapping in an arid area using a land unit area (LUA) sampling approach and geostatistical interpolation techniques. ISPRS Int J Geo Inf 5(3):35
Hatton W, Fardell A (2012) New discoveries of coal in Mozambique-development of the coal resource estimation methodology for International Resource Reporting Standards. Int J Coal Geol 89(1):2–12. https://doi.org/10.1016/j.coal.2011.02.010
Heriawan MN, Koike K (2008a) Identifying spatial heterogeneity of coal resource quality in a multilayer coal deposit by multivariate geostatistics. Int J Coal Geol 73:307–330. https://doi.org/10.1016/j.coal.2007.07.005
Heriawan MN, Koike K (2008b) Uncertainty assessment of coal tonnage by spatial modeling of seam distribution and coal quality. Int J Coal Geol 76:217–226. https://doi.org/10.1016/j.coal.2008.07.014
Hindistan MA, Tercan AE, Ünver B (2010) Geostatistical coal quality control in longwall mining. Int J Coal Geol 81:139–150. https://doi.org/10.1016/j.coal.2009.12.014
Hohn ME, Britton JQ (2012) A geostatistical case study in West-Virginia: all coals are not the same. Int J Coal Geol 112:125–133. https://doi.org/10.1016/j.coal.2012.12.004
Husrevoglu M (2018) Visualization of precipitation maps by geostatistical analysis. MSc Thesis, The Graduate School of Natural and Applied Science of Selçuk University, Konya, Turkey, p 128 (in Turkish)
Kapageridis IK, Kolovos CJ (2009) Modelling and resource estimation of a thin layered lignite deposit. In: APCOM 2009 Proceedings. Vancouver, Canada, pp 95–103
Karacan O, Olea RA, Goodman G (2012) Geostatistical modeling of the gas emission zone and its in-place gas content for Pittsburgh-seam mines using sequential Gaussian simulation. Int J Coal Geol 90-91:50–71. https://doi.org/10.1016/j.coal.2011.10.010
Karami O, Fallah A, Shataei SH, Latifi H (2018) Assessment of geostatistical and interpolation methods for mapping forest dieback intensity in Zagros forests. Caspian J Environ Sci 16(1):71–84
Kisi O, Mohsenzadeh Karimi S, Shiri J, Keshavarzi A (2019) Modelling long term monthly rainfall using geographical inputs: assessing heuristic and geostatistical models. Meteorol Appl 26(4):698–710. https://doi.org/10.1002/met.1797
Matheron G (1963) Principles of geostatistics. Econ Geol 58:1246–1266. https://doi.org/10.2113/gsecongeo.58.8.1246
Moura O, Fernandes AC (2009) Kriging density estimates for the bluemouth rockfish, Helicolenus dactylopterus (Scorpaenidae) off the southern Portuguese coast. Fish Res 95(1):112–124
Olea RA, Luppens JA, Tewalt SJ (2011) Methodology for quantifying uncertainty in coal assessments with an application to a Texas lignite deposit. Int J Coal Geol 85:78–90. https://doi.org/10.1016/j.coal.2010.10.001
Panagopoulos T, Jesus J, Antunes MDC, Beltrao J (2006) Analysis of spatial interpolation for optimising management of a salinized field cultivated with lettuce. Eur J Agron 24(1):1–10
Pardo-Iguzquiza E, Dowd PA, Baltuille JM, Chica-Olmo M (2013) Geostatistical modelling of a coal seam for resource risk assessment. Int J Coal Geol 112:134–140. https://doi.org/10.1016/j.coal.2012.11.004
Perinçek D, Ataş N, Karatut Ş, Erensoy E (2015) Geological factors controlling potential of lignite beds within the Danişmen formation in the Thrace Basin. Bull Min Res Exp 150:77–108
Qin Q, Wang H, Lei X, Li X, Xie Y, Zheng Y (2020) Spatial variability in the amount of forest litter at the local scale in northeastern China: kriging and cokriging approaches to interpolation. Ecology and Evolution 10(2):778–790. https://doi.org/10.1002/ece3.5934
Ramirez-Davila JF, Porcayo-Camargo E, Sanchez-Pale JR, Vázquez-García LM (2012) Spatial behavior comparison of Bactericera cockerelli Sulc. (Hemiptera: Triozidae) in Mexico. Neotrop. Entomol 41(1):9–16. https://doi.org/10.1007/s13744-012-0019-y
Saikia K, Sarkar BC (2013) Coal exploration modelling using geostatistics in Jharia coalfield, India. Int J Coal Geol 112:36–52. https://doi.org/10.1016/j.coal.2012.11.012
Şengüler İ (2013) Geology and coal potential of Thrace Basin. Bull Min Res Exp 16:109–115 (In Turkish)
Shahbeik S, Afzal P, Moarefvand P, Qumarsy M (2014) Comparison between ordinary kriging (OK) and inverse distance weighted (IDW) based on estimation error. Case study: Dardevey iron ore deposit. NE Iran Arabian Journal of Geosciences 7(9):3693–3704
Shcherbakov MV, Brebels A, Shcherbakova NL, Tyukov AP, Janovsky TA, Kamaev VAE (2013) A survey of forecast error measures. World Appl Sci J 24(24):171–176
Siddiqui FI, Pathan AG, Ünver B, Tercan AE, Hindistan MA, Ertunç G, Atalay F, Ünal S, Kıllıoğlu Y (2015) Lignite resource estimations and seam modeling of Thar field, Pakistan. Int J Coal Geol 140:84–96. https://doi.org/10.1016/j.coal.2015.02.003
Tercan AE, Karayigit AI (2001) Estimation of lignite reserve in the Kalburcayiri field, Kangal basin, Sivas, Turkey. Int J Coal Geol 47:91–100. https://doi.org/10.1016/S0166-5162(01)00033-7
Tercan AE, Ünver B, Hindistan MA, Ertunç G, Atalay F, Ünal S, Kıllıoğlu Y (2013) Seam modeling and resource estimation in the coalfields of western Anatolia. Int J Coal Geol 112:94–106. https://doi.org/10.1016/j.coal.2012.10.006
Turkish Coal Enterprises TKI (2018) Annual Activity Report. http://www.tki.gov.tr/depo/file/faaliyet%20raporu/2018faaliyetraporu.pdf. (in Turkish).
Uyan M (2016) Determination of agricultural soil index using geostatistical analysis and GIS on land consolidation projects: a case study in Konya/Turkey. Comput Electr Agric 123:402–409. https://doi.org/10.1016/j.compag.2016.03.019
Uyan M, Cay T (2013) Spatial analyses of groundwater level differences using geostatistical modeling. Environ Ecol Stat 20(4):633–646. https://doi.org/10.1007/s10651-013-0238-3
Vasquez C, Nieto A (2004) A statistical means of modeling lignite quality from e-log and lab data. Paper presented at the SME Annual Meeting, Denver, Colorado, USA, February, In, pp 23–25
Watson WD, Ruppert LF, Bragg LJ, Tewalt SJ (2001) A geostatistical approach to predicting sulfur content in the Pittsburgh coal bed. Int J Coal Geol 48:1–22. https://doi.org/10.1016/S0166-5162(01)00035-0
Webber T, Costa L, Salvadoretti P (2013) Using borehole geophysical data as soft information in indicator kriging for coal quality estimation. Int J Coal Geol 112:67–75. https://doi.org/10.1016/j.coal.2012.11.005
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Uyan, M., Dursun, A.E. Determination and modeling of lignite reserve using geostatistical analysis and GIS. Arab J Geosci 14, 312 (2021). https://doi.org/10.1007/s12517-021-06633-2
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DOI: https://doi.org/10.1007/s12517-021-06633-2