Research of the depositional environment using geological mapping, petrography, gamma-ray (GR) log, palynology, and foraminifera fossils of the Bojongmanik Formation has led to the formation of several different conclusions about the transition to the marine environment, which are attractive to revisit. The expected results of this research are to determine the paleoenvironment of the Bojongmanik and Serpong Formations based on elemental geochemistry, the development of paleoenvironment proxies based on portable X-ray fluorescence (pXRF) in fluvial to transitional environments studies, and the contribution of paleoenvironment analysis to GR-log facies interpretation. The research methodology starts with GR-log facies analysis, Pearson’s correlation, paleoenvironment analysis based on elemental affinity and elemental ratio, and comparing the paleoenvironment with GR-log-based facies. The paleoenvironment analysis based on elemental geochemistry resulted in the Bojongmanik Formation in the research area deposited at the tidal point bar, lagoon, and shoreface, while the Serpong Formation was deposited at the fluvial point bar and floodplain. Compared to previous research, the Bojongmanik Formation in the research area could be stratigraphically related to the upper Bojongmanik Formation. Proxies based on elemental geochemical affinities of carbonate-associated, carbonate-productivity, terrigenous-associated elements, and redox-sensitive trace elements show contrast changes between facies. Proxies based on the specific ratio show a detailed paleoenvironment for paleoclimate (Sr/Cu), paleosalinity (Sr/Ba), paleoredox (Cu/Zn), paleo-hydrodynamics and water depth (Zr/Rb and Fe/Mn), sediment provenance (Cr/Zr), and siliciclastic-dominated (Zr + Rb)/Sr. Adding a geochemistry element-based paleoenvironment analysis benefits from a more specific justification for GR-log facies interpretation.

DOI:10.17014/ijog.9.3.291-302 The methodology of facies analysis may include statistical examination to establish a local facies model. Without such examination, it is very difficult to predict the facies succession and to interpret the changes in depositional conditions from thick or complex stratigraphic sections. Based on the survey of sedimentary geologic literature in Indonesia, it is suggested that the aforementioned statistical method has relatively seldom been used in Indonesia. Such a situation may reflect a gap in information on the methodology and, accordingly, it seems imperative that there should be a re-exposition of the method. This paper presents a concise exposition of the combination of the embedded Markov Chain and binomial probability as one of the most successful statistical methods which are used in facies analysis. The results of previous studies of The Citalang Formation are used as a case study to illustrate its applications to the real geologic world.

Coal quality is one of the key factors in determining the effectiveness of processing and utilization. Coal quality assessment involves analyzing physical and chemical aspects to determine its characteristics. Coal quality is also influenced by geological conditions at the mining site, which affect the quality and amount of carbon in the coal. To ensure consistency, it is necessary to implement coal quality control based on physical and chemical parameters from the mining process in the pit to storage in the stockpile. Analysis of the effect of total moisture and ash on the calorific value of coal is the purpose of this study. The method used is a ROM (Run of Mine) coal sample located at the stockpile location. The relationship between Total Moisture and the calorific value of coal shows a negative linear correlation where the influence value for a 1% increase in Total Moisture is -71.343 kcal/kg and so is between Ash and the calorific value of coal 1% increase in Ash is -82.588 kcal/kg, which shows a negative linear correlation. Total Moisture increases by 1%, reducing the calorific value of coal by 71 kcal/kg, and increasing Ash content by 1% reduces the calorific value of coal by 83 kcal/kg.