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All Journal Prosiding Seminar Nasional Rekayasa Teknologi Industri dan Informasi ReTII
Dhea Ameila Pratiwi
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Aerospace Engineering Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Materials Science & Nanotechnology Mechanical Engineering Physics Transportation

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Lithofacies Recurrence Analysis Using Markov Chain Method in Semilir Formation, Ngoro-Oro, Gunungkidul Dhea Ameila Pratiwi; Akhmad Zamroni; Ani Apriani
Retii 2024: Prosiding Seminar Nasional ReTII ke-19 (Edisi Penelitian)
Publisher : Institut Teknologi Nasional Yogyakarta

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Abstract

The Semilir Formation located in Ngoro-Oro, Gunungkidul, has significant lithofacies diversity, reflecting dynamic depositional conditions in the past and indicating a recurring depositional pattern. The limitations of stratigraphic and geostatistical information are the main reasons for this research. This study aims to identify the characteristics of lithofacies in the Semilir Formation, Ngoro-Oro, Gunungkidul, and analyze the relationship between facies through the chi-square statistical test. In addition, the pattern of lithofacies repetition and transition is evaluated using the Markov chain method to determine the probability of lithofacies repetition and predict the stratigraphic sequence at the research location. The research was conducted on ancient rock outcrops along the Prambanan-Wonosari alternative route located in Ngoro-Oro Village, Patuk District, Gunungkidul Regency, Daerah Istimewa Yogyakarta Province by conducting stratigraphic measurements with a thickness of 78 meters using Jacob stuff then continued with geostatistical analysis using the Markov chain method. This method will provide an understanding of the prediction of lithofacies transition patterns in the research area. The research results reveal that the lithofacies at the study location consist of lithology composed of sandstone interbedded with claystone and tuff, sandstone interbedded with claystone with siltstone inserts, and sandstone interbedded with siltstone with claystone inserts. The results of the Markov chain statistical calculation of lithology or lithofacies have a non-random transition pattern
Co-Authors Akhmad Zamroni Ani Apriani