Geostatistical Ore Body Modeling on Uranium Mineralization in Remaja Sector, Kalan Area, West Kalimantan

Roni Cahya Ciputra, Mohamad Nur Heriawan, Heri Syaeful, Dhatu Kamajati, Putri Rahmawati

DOI: http://dx.doi.org/10.55981/eksplorium.2022.6622

Abstract


Manual ore body modeling on Remaja Sector, Kalan, West Kalimantan generally takes a long time and is subjective. On the other hand, automatic modeling (implicit modeling) is faster, objective, and equipped with uncertainty factors. This study aimed to analyze the comparison between the geostatistical Sequential Indicator Simulation (SIS) ore body model to the manual ore body model. The lithology database was used as input for variogram analysis and SIS simulation. The directional variogram was used to construct an experimental variogram for the lithology with orientation data. The orientation of the lithologies corresponds to the anisotropy of their variogram map. The SIS was carried out in  Block A and Block B with block sizes of 6×6×6 m3 and 5×5×5 m3 respectively. The simulation results were processed to produce a lithology probability model. By using maximum probability as block lithology, simulation results were well validated by the composite database histogram, the lithologies along the tunnel on the geological map of level 450 masl of Eko Remaja Tunnel., and the lithologies along boreholes. The weakness of the geostatistical ore body model was the results depending on the input parameters. Meanwhile, several advantages of the geostatistical ore body model were a faster processing process, equipped with an uncertainty factor, and the block size of the model has taken into account the distance between grade data so that it can be used directly for grade estimation. Quantitatively, the geostatistical ore body model had a higher average percentage of conformity to the lithology of the mineralized zone along the borehole than the manual ore body model.


Keywords


Geological Modeling, Geostatistics, Sequential Indicator Simulation, Uranium, Kalan

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References


[1] S. Tjokrokardono, “Prospek Pengembangan Cebakan Uranium di Kalan, Kalimantan,” J. Nukl. Indones., vol. 1, no. 1, pp. 1–12, 1998.

[2] S. Tjokrokardono, D. Soetarno, M. Sapardi, L. Subiantoro, and R. Witjahyati, “Studi Geologi Regional dan Mineralisasi Uranium di Pegunungan Schwaner Kalimantan Barat dan Tengah,” in Prosiding Seminar Geologi Nuklir dan Sumber Daya Tambang, 2004, pp. 64–84.

[3] BATAN-CEA, “Prospect to Develop Uranium Deposits in Kalimantan Volume I and II, Introduction to General Reconnaissance,” Jakarta, 1977.

[4] H. Syaeful, F. D. Indrastomo, and M. B. Garwan, “Application of UNFC for the reassessment of uranium resources of the Eko Remaja and Rabau Sectors, Kalan Area, West Kalimantan, Indonesia,” in UNECE Energy Series 58 Application of the United Nations Framework Classification for Resources: Case Study, Geneva: United Nation Publication, 2019, pp. 137–147.

[5] R. Ciputra, S. Suharji, D. Kamajati, and H. Syaeful, “Application of geostatistics to complete uranium resources estimation of Rabau Hulu Sector, Kalan, West Kalimantan,” E3S Web Conf., vol. 200, 2020.

[6] H. Syaeful and Suharji, “Eksplorium Geostatistics Application on Uranium Resources Classification : Case Study of Rabau Hulu Sector , Kalan , West Kalimantan Aplikasi Geostatistik pada Klasifikasi Sumber Daya Uranium : Studi Kasus,” Eksplorium, vol. 39, no. 2, pp. 131–140, 2018.

[7] H. Syaeful, Suharji, and A. Sumaryanto, “Pemodelan Geologi dan Estimasi Sumber Daya Uranium di Sektor Lemajung, Kalan, Kalimantan Barat,” in Prosiding Seminar Nasional Teknologi Energi Nuklir, 2014, pp. 329–342.

[8] E. Cowan et al., “Practical Implicit Geological Modelling,” in 5th International Mining Geology Conference, 2003, pp. 89–99.

[9] M. Abzalov, Applied Mining Geology, Modern Approach in Solid Earth Sciences 12. Switzerland: Springer, 2016.

[10] M. E. Rossi and C. V. Deutsch, Mineral Resource Estimation. New York: Springer, 2014.

[11] K. Novak-Zelenika, “Theory of deterministical and stochastical indicator mapping methods and their applications in reservoir characterization, a case study of the Upper Miocene reservoir in the Sava Depression,” Rud. Geol. Naft. Zb., vol. 32, no. 3, pp. 45–53, 2017.

[12] M. Maleki, X. Emery, and N. Mery, “Indicator variograms as an aid for geological interpretation and modeling of ore deposits,” Minerals, vol. 7, no. 12, 2017.

[13] Y. He et al., “Sequential indicator simulation and indicator kriging estimation of 3-dimensional soil textures,” Aust. J. Soil Res., vol. 47, no. 6, pp. 622–631, 2009.

[14] H. Talebi, O. Asghari, and X. Emery, “Stochastic rock type modeling in a porphyry copper deposit and its application to copper grade evaluation,” J. Geochemical Explor., vol. 157, pp. 162–168, 2015.

[15] R. Gutierrez and J. Ortiz, “Sequential Indicator Simulation with Locally Varying Anisotropy – Simulating Mineralized Units in a Porphyry Copper Deposit.,” J. Min. Eng. Res., vol. 1, no. 1, pp. 1–7, 2019.

[16] O. Asghari, “Geostatistical simulation of dyke systems in Sungun porphyry copper deposit, Iran,” J. Min. Environ., vol. 6, no. 1, pp. 1–10, 2015.

[17] N. Remy, A. Boucher, and J. Wu, Applied Geostatistics with SGeMS: A user’s guide, vol. 9780521514. 2009.

[18] J. J. Gómez-Hernández and R. M. Srivastava, “One Step at a Time: The Origins of Sequential Simulation and Beyond,” Math. Geosci., vol. 53, no. 2, pp. 193–209, 2021.

[19] F. Zhou, D. Shields, S. Tyson, and J. Esterle, “Comparison of sequential indicator simulation, object modeling and multiple-point statistics in reproducing channel geometries and continuity in 2D with two different spaced conditional datasets,” J. Pet. Sci. Eng., vol. 166, no. February 2016, pp. 718–730, 2018.

[20] Y. Liu, Q. Xia, and E. J. M. Carranza, “Integrating sequential indicator simulation and singularity analysis to analyze the uncertainty of geochemical anomaly for exploration targeting of tungsten polymetallic mineralization, Nanling belt, South China,” J. Geochemical Explor., vol. 197, no. July 2018, pp. 143–158, 2019.

[21] M. Tokoglu, “Comparative Analysis of 3D Domain Modelling Alternatives: Implications for Mineral Resource Estimates,” Colorado School of Mines, 2018.

[22] F. G. Bastante, C. Ordóñez, J. Taboada, and J. M. Matías, “Comparison of indicator kriging , conditional indicator simulation and multiple-point statistics used to model slate deposits,” Eng. Geol., vol. 98, pp. 50–59, 2008.

[23] A. I. Xiao, S. Baitao, and C. Xiangzhao, “Integrated 3d modeling of quaternary sediments in the Beijing plain, based on a sequential indicator simulation,” Geol. Croat., vol. 72, no. Special Issue, pp. 3–17, 2019.

[24] S. Hajsadeghi, O. Asghari, M. Mirmohammadi, and S. A. Meshkani, “Indirect rock type modeling using geostatistical simulation of independent components in Nohkouhi volcanogenic massive sulfide deposit, Iran,” J. Geochemical Explor., vol. 168, pp. 137–149, 2016.

[25] H. T. Breitfeld et al., “Mesozoic Paleo-Pacific Subduction Beneath SW Borneo: U-Pb Geochronology of the Schwaner Granitoids and the Pinoh Metamorphic Group,” Front. Earth Sci., vol. 8, no. December 2020.

[26] J. Hennig, H. T. Breitfeld, R. Hall, and A. M. S. Nugraha, “The Mesozoic tectono-magmatic evolution at the Paleo-Pacific subduction zone in West Borneo,” Gondwana Res., vol. 48, pp. 292–310, 2017.

[27] L. Davies, R. Hall, and R. Armstrong, “Cretaceous Crust in South West Borneo: Petrological, Geochemical, and Geochronological Constraints from the Schwaner Mountains,” in Proceedings Indonesian Petroleum Association 38th Annual Convention & Exhibition, 2014.

[28] H. S. Karyono, “Temperatur Pembentukan Vein Mineralisasi di Bukit Eko, Kalan, Kalimantan Barat,” in Proceedings of The Indonesian Association of Geologist XXI Annual Scientific Meeting, 1992, p. 281.

[29] H. S. Karyono, “Analisis Kontrol Tektonik pada Vein Mineralisasi di Bukit Eko, Kalan, Kalimantan Barat,” in Proceedings of The Indonesian Association of Geologist XX Annual Scientific Meeting, 1991, pp. 115–128.

[30] A. G. Muhammad, R. C. Ciputra, and H. Syaeful, “Fracture Analysis of Uranium-Bearing Rock in Eko-Remaja Exploration Tunnel at Depth 50-200 Meters, Kalan, West Kalimantan,” J. Phys. Conf. Ser., vol. 1363, no. 1, 2019.

[31] H. S. Karyono, “Typolohie des structures mineralisees du bassin de la Kalan, Kalimantan de L’Ouest, Indonesia: Aspect tectonique et controle structural des mineralisations d’uranium,” L’Universute Louis Oasteur, 1989.

[32] R. C. Ciputra, A. G. Muhammad, and T. B. Adimedha, “Estimasi Sumber Daya Uranium Tipe Batupasir di Sektor Aloban , Sibolga , Tapanuli Tengah Uranium Resources Estimation of Sandstone-Type Deposit in Aloban Sector ,” Eksplorium, vol. 40, no. 1, pp. 1–10, 2019.

[33] D. Soetarno, “Geokronologi U-Pb pada Mineralisasi Uranium di Eko dan Rirang, Kalan, Kalimantan Barat,” in Proceedings of The Indonesian Association of Geologist XXI Annual Scientific Meeting, 1992, pp. 257–264.

[34] A. Ersoy and T. Y. Yünsel, “The assessment of soil contamination by heavy metals using geostatistical sequential Gaussian simulation method,” Hum. Ecol. Risk Assess., vol. 24, no. 8, pp. 2142–2161, 2018.


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