JGEET Journal of Geoscience Engineering Environment and Technology最新文献

{"title":"Trace Fossils Of The Selorejo Formation, Rembang Zone, North East Java Basin, Indonesia","authors":"Yody Rizkianto, Siti Umiyatun Choiriah, Achmad Subandrio, Intan Paramita Haty, Desi Kumala Isnani, Nanda Ajeng Nurwantari, Muhammad Ardiyan Syah Darmawa, Hendry Wirandoko","doi":"10.25299/jgeet.2023.8.3.10454","DOIUrl":"https://doi.org/10.25299/jgeet.2023.8.3.10454","url":null,"abstract":"The Rembang Zone of the North East Java Basin is a zone that develops as a petroleum system and is one of the areas with Indonesia’s largest oil reserves. One of the lithologies in the Rembang Zone is a sedimentary rock carbonated as a marker of marine sediments. The outcrop is continuous and rich in trace fossils, especially in the Ledok and Selorejo Formations. The existence of trace fossil outcrops is crucial for the learning process of earth science, biology, and other sciences, but recently these outcrops have been closed and have become damaged. Their numbers are decreasing due to community mining activities, so unique research on trace fossils in the Rembang Zone must be done immediately. This research aims to discover the variation of trace fossils found in the Selorejo Formation. The methods used are field mapping, measured stratigraphic measurements, rock sampling, and laboratory analysis (sedimentology, petrography, and paleontology). The research shows trace fossils in Planolites, Helminthopsis, Thalassinoides, Conichnus, Chondrites, Macaronichnus, Bergauria, Ophiomorpha, Skolithos, Terebellina, Palaeophycus, and Asterosoma.","PeriodicalId":31931,"journal":{"name":"JGEET Journal of Geoscience Engineering Environment and Technology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136240876","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Analysis of Water Availability in the Upper Siak Basin Using the GR2M Model Application","authors":"None Harmiyati, A. Sulistio Fuaji","doi":"10.25299/jgeet.2023.8.3.11559","DOIUrl":"https://doi.org/10.25299/jgeet.2023.8.3.11559","url":null,"abstract":"The Siak watershed is one of the critical watersheds, where natural disasters such as floods, landslides and erosion often occur in this area. The Siak watershed has 4 main sub-watersheds, namely the Tapung Kanan sub-watershed, the Tapung Kiri sub-watershed, the Mandau sub-watershed and the Siak Hilir sub-watershed. The existence of these 4 sub-watersheds is also not able to meet the water needs of the community due to the rapid development of the region which will then cause the demand for water to continue to increase in line with the rate of population growth, especially in the Siak watershed area. Fulfillment of food needs and population activities is always closely related to the need for water. These demands cannot be avoided, but must be predicted and planned for the best possible use. The purpose of this study is to describe the application of the GR2M modeling and the amount of raw water availability in the Upper Siak Watershed.
 The research method used is descriptive quantitative with data collection techniques in the form of map data, rain data, climatology data and field discharge data. And the research location is in the Upper Siak Watershed, namely the Tapung Kiri Sub-watershed.
 The results of the study show that 1) GR2M modeling can be applied to the Tapung Kiri Sub-watershed with an R2 performance of 0.41 with a satisfactory interpretation, a correlation coefficient (R) of 0.67 with a strong interpretation, and an efficiency coefficient (CE) of 0.59 with sufficient optimization interpretation. The reliable discharge obtained based on the GR2M modeling data for the availability of drinking water (Q99%) in the Siak Hulu watershed is 15.69 m3/second.","PeriodicalId":31931,"journal":{"name":"JGEET Journal of Geoscience Engineering Environment and Technology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136240879","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"1D Geomechanical Model For Wellbore Stability in Z Field, Y Well Sanga Sanga Working Area, Kutai Basin","authors":"Navrianta Tappi, J. R. Cherdasa","doi":"10.25299/jgeet.2023.8.02-2.13871","DOIUrl":"https://doi.org/10.25299/jgeet.2023.8.02-2.13871","url":null,"abstract":"This research is about 1D geomechanical model for wellbore stability in Z Field, Y Well Sanga Sanga Working Area, Kutai Basin where wells have been drilled. The Purpose of this Research is to analyze the stability of the well starting from knowing the stress regime that occurs, predicting the occurrence of wellbore failure, and determining safe mud weight window for next drilling. The method use in this Research is a numerical modelling method using log data and drilling data that has been obtained and then managed using Techlog Software. The result of this Research show the magnitude of mechanical properties of the rock that have been obtained, then in general the stress regime that occurs in the Z Field formation is the normal regime even though the strike slip and reverse regime are inserted at a certain depth, then based on the prediction results of failure in this well is wide breakout, which in general occurs in lithology with sandstone, finaly safe mud weight window can be estimated properly, so that it can be used for further well drilling. This research is about 1D geomechanical model for wellbore stability in Z Field, Y Well Sanga Sanga Working Area, Kutai Basin where wells have been drilled. The Purpose of this Research is to analyze the stability of the well starting from knowing the value of the mechanical properties of the formation, the stress regime that occurs, predicting the occurrence of wellbore failure, and determining safe mud weight window for next drilling. The method use in this Research is a numerical modelling method using log data and drilling data that has been obtained and then managed using Techlog Software. The result of this Research show the magnitude of mechanical properties of the rock that have been obtained, then in general the stress regime that occurs in the Z Field formation is the normal regime even though the strike slip and reverse regime are inserted at a certain depth, then based on the prediction results of failure in this well is wide breakout, which in general occurs in lithology with sandstone, finaly safe mud weight window can be estimated properly, so that it can be used for further well drilling.","PeriodicalId":31931,"journal":{"name":"JGEET Journal of Geoscience Engineering Environment and Technology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84545707","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Stress Analysis of Existing Underground Gas Pipeline due to New Road Crossing with ODOL Transportation","authors":"Taqiya Tsamara, IGN Wiratmaja Puja","doi":"10.25299/jgeet.2023.8.02-2.13882","DOIUrl":"https://doi.org/10.25299/jgeet.2023.8.02-2.13882","url":null,"abstract":"Pipelines are the main choice for transport oil and gas due to its resilience, reliability, safety, and lower cost. Most road crossing pipelines are located underground where protections from the loads can be used such as additional pavement. Underground road crossing pipelines withstand stresses caused by the internal load, earth load, and live load. These loads are affected by the pipe and fluid specifications, soil and environment data, and also the vehicle data. Over dimension and over loading (ODOL) vehicles are a very common problem found in Indonesia. Hence, a stress analysis towards the underground road crossing pipeline being crossed by ODOL vehicles are relevant. A manual calculation of the stress analysis can be done by using API RP 1102: “Steel Pipelines Crossing Railroads and Highways”. A stress analysis using the finite element method (FEM) is conducted using a computer software, namely Abaqus, which also shows the displacement of the pipeline. The case study is an underground road crossing pipeline with depth of 8 feet and uses rigid pavement. The use of rigid pavements over the soil decreases the stress experienced by the pipeline. The results of the total effective stress show a value of 4,785 psi which is still within the allowable range. The stress is found to be directly proportional to the displacement value obtained using FEA. By conducting parametric studies, it is also found that the total effective stress decreases as the burial depth of the pipe is larger.","PeriodicalId":31931,"journal":{"name":"JGEET Journal of Geoscience Engineering Environment and Technology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135314841","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Possibilities Study of a Non-condensable Gas Exhaust System through the Condensate Injection Pipe at PLTP Wayang Windu","authors":"Annisa Nurlatifah, Anton Purwakusumah","doi":"10.25299/jgeet.2023.8.02-2.13878","DOIUrl":"https://doi.org/10.25299/jgeet.2023.8.02-2.13878","url":null,"abstract":"Wayang Windu Geothermal Power Plant, located in Pangalengan, Bandung regency, West Java with an installed capacity of 227 MWe has two units to generate electricity and deliver to the Jawa, Madura, and Bali grid. The steam extracted from the reservoir contains non-condensable gas of about 1-1.2% of total steam extracted, with the gas composition is CO2 92%, H2S 2%, NH3 0.1%, and residual gasses 4.9%. Possibilities study of a non-condensable gas exhaust through the condensate injection pipe was created as the efforts in the environmental conservation aspect for reducing carbon released to the atmosphere and reinjected back into the reservoir. This study was simulated in Wayang Windu Unit 2 by calculating the non-condensable gas flow rate from the gas removal system into the condensate injection pipe near of cooling tower blowdown power station area. The analysis result of this study indicates that the non-condensable gas requires a higher flow rate of condensate to dissolve the entire non-condensable gas, and may cause the slug flow pattern which would endanger the condensate pipeline system also destabilize the non-condensable gas exhaust operation process from the condenser through the gas removal system. To deal with this problem, the possibility of exhausting the non-condensable gas produced by the gas removal system can be alternated by flowing its non-condensable gas into a flash absorber system and converting its non-condensable gas into other eco-friendly products and power plant safe.","PeriodicalId":31931,"journal":{"name":"JGEET Journal of Geoscience Engineering Environment and Technology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135314843","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Machine Learning Application of Two-Dimensional Fracture Properties Estimation","authors":"Ardian Nurcahya, Aldenia Alexandra, Satria Zidane Zainuddin, Fatimah Az-Zahra, M. I. Khoirul Haq, Irwan Ary Dharmawan","doi":"10.25299/jgeet.2023.8.02-2.13874","DOIUrl":"https://doi.org/10.25299/jgeet.2023.8.02-2.13874","url":null,"abstract":"Fractures are substantial contributors to solute transport sedimentary systems that form pathways. The pathway formed in a fracture has two physical parameters, there are mean aperture and surface roughness. Mean aperture is the thickness of the pathway that the fluid will pass through, and surface roughness is the roughness of the fracture pathway. The two physical parameters of the fracture are important to determine since they affect the permeability value in petroleum reservoir analysis. We developed a machine learning algorithm based on the Convolutional Neural Network (CNN) to predict those two parameters. Furthermore, image processing analysis is performed to generate the datasets. The results show that the CNN algorithm shows good agreement with the reference results. In addition, the algorithms showed efficient performance in terms of computational time. CNN is a type of deep neural designed to perform analysis on multi-channel images that can classify fracture geometry. The best model was determined using a benchmark dataset with a CNN model provided by Keras. The results of experiments conducted on fracture geometry images show that the machine learning model created is able to predict the mean aperture and surface roughness values.","PeriodicalId":31931,"journal":{"name":"JGEET Journal of Geoscience Engineering Environment and Technology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135314840","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Machine learning prediction of tortuosity in digital rock","authors":"Fadhillah Akmal, M. Cisco Ramadhan Dzulizar, Muhammad Faizal Rafli, Fatimah Az-Zahra, M. I. Khoirul Haq, Irwan Ary Dharmawan","doi":"10.25299/jgeet.2023.8.02-2.13875","DOIUrl":"https://doi.org/10.25299/jgeet.2023.8.02-2.13875","url":null,"abstract":"Physical rock property measurement is an important stage in energy exploration, both for hydrocarbons and geothermal sources. The value of physical rock properties can provide information about reservoir quality, and one of these properties is tortuosity. Tortuosity is an intrinsic property of porous materials that describes the level of complexity of the porous arrangement when a fluid passes through it. Conventionally, tortuosity values are measured through laboratory analysis and numerical simulation, but these measurements can take a long time. An alternative method for measuring tortuosity is using machine learning with a convolutional neural network (CNN). A CNN is a type of deep neural network designed to analyze multi-channel images and has been applied successfully to classification and non-linear regression problems. By training a CNN on a dataset of digital rock samples that have been simulated using numerical computation to obtain their tortuosity values, it is possible to demonstrate that CNNs can accurately predict the tortuosity of digital rock. The result is that the CNN model can predict tortuosity values with the Xception model being the most accurate with the lowest RMSE value of 0.90962.","PeriodicalId":31931,"journal":{"name":"JGEET Journal of Geoscience Engineering Environment and Technology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135314835","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Seismic Vulnerability Analysis Using the Horizontal to Vertical Spectral Ratio (HVSR) Method on the West Palu Bay Coastline","authors":"None Amirudin, Iktri Madrinovella, None Sofian","doi":"10.25299/jgeet.2023.8.02-2.13879","DOIUrl":"https://doi.org/10.25299/jgeet.2023.8.02-2.13879","url":null,"abstract":"This research was carried out to make a map of the dominant frequency (f0), amplification factor (A0), seismic susceptibility index (Kg), Vs30, Sediment Layer Thickness (H) and Peak ground acceleration (PGA). Microtremor measurements were carried out with a three-component seismometer of the TDL-303S type as many as 27 measurement points. The data was analyzed by the Horizontal to Vertical Spectral Ratio (HVSR) method. The PGA calculation was carried out using the Kanai equation with a reference to the Palu-Donggala earthquake on September 28, 2018. The results showed that the distribution of the dominant frequency value (f0) ranged from 0.4149 Hz-0.8869 Hz, the soil amplification factor (A0) ranged from 2,199–4,884, the seismic vulnerability index (Kg) ranged from 8.79 s2/cm-41.41 s2/cm, the shear wave velocity to a depth of 30 meters ( Vs30) ranged from Vs30 197.7 m/s-320.2 m/s , the thickness of the sedimentary layer ranges from 260.3 m-291.1 m and the peak ground acceleration (PGA) of Kanai ranges from 137.3 gal – 234.2 gal by using Mw 7.4 earthquakes with an intensity scale (MMI) VI to VII. The coastal area of West Palu bay has an intermediate seismic vulnerability II to a high seismic vulnerability IV so that it will be vulnerable in the event of an earthquake disaster. Areas that have a very high vulnerability index are in the upper western and easternmost regions while those with a lower level tend to have a lower vulnerability index value.","PeriodicalId":31931,"journal":{"name":"JGEET Journal of Geoscience Engineering Environment and Technology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135314842","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Analysis of Petrophysical Parameter on Shaly Sand Reservoir by Comparing Conventional Method and Shaly Sand Method in Vulcan Subbasin, Northwest Australia","authors":"Ulrike Johanna, Epo Prasetya Kusumah","doi":"10.25299/jgeet.2023.8.02-2.13880","DOIUrl":"https://doi.org/10.25299/jgeet.2023.8.02-2.13880","url":null,"abstract":"Vulcan Subbasin is an area with a lot of oil and gas exploration where is located in the Bonaparte Basin, Northwest Australia. There is some formation identified as sandstone reservoir with clay content which is usually called shaly sand based on the screening between resistivity log and density log. Clay content caused lower resistivity log readings so the shaly sand reservoir is considered as non-reservoir. To overcome this, a method besides the conventional method was applied to analyze the petrophysical parameters of shaly sand reservoir, it was shaly sand method. Petrophysical analysis is an analysis of rock physical parameters such as shale volume, porosity, and water saturation based on well log data. In this study, petrophysical analysis was carried out in the Vulcan Subbasin using 35 well log data, including gamma ray log, resistivity log, neutron log, and density log for the conventional method and shaly sand method involved Stieber equation and Thomas Stieber plot. The results obtained from this study are the comparison of petrophysical parameter values and pay summary between the conventional method and the shaly sand method, also its relation to the shale distribution type. By applying the shaly sand method, the average shale volume has decreased, the average porosity has increased, the average water saturation has increased, the average net to gross has increased, the average net thickness has increased, and the average net pay has increased. Changes in the average value were caused by laminated-dispersed shale distribution type which is influenced by diagenesis and the depositional environment of the formation.","PeriodicalId":31931,"journal":{"name":"JGEET Journal of Geoscience Engineering Environment and Technology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135314847","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Investigation of Geological Structure Using Magnetotelluric and Gravity Data Optimization on Non Volcanic Geothermal, Bora, Centre of Sulawesi","authors":"Tiaraningtias Bagus Pertiwi, Yunus Daud, Fikri Fahmi","doi":"10.25299/jgeet.2023.8.02-2.13876","DOIUrl":"https://doi.org/10.25299/jgeet.2023.8.02-2.13876","url":null,"abstract":"The existence of geological structures is one of the important parameters in determining the permeability zone in a geothermal system. This research was conducted in a non-volcanic geothermal field, Bora, located in the province of Central Sulawesi, aiming to identify the subsurface features, especially geological structures related to permeability zones by optimizing geophysical data. Magnetotelluric (MT) 3D inversion modelling is some of the latest methods to identify geological structural patterns in geothermal systems. The results of the MT model and analysis its parameters can find variations in the distribution of subsurface resistivity, orientation of the direction of the prospect area, and indications of geological structure zones. The type and geometry of the geological structure associated with the high permeability zone can be complemented by determining the contrast of gravity values ​​and analysis of the maximum First Horizontal Derivative (FHD) and zero of the Second Vertical Derivative (SVD). Based on the analysis of geophysical data, it is possible to identify the permeability zone associated with the main structure, namely the Palu-Koro fault, delineate the geothermal reservoir at a depth of 1500-2000 meters and determine the location of well drilling. To visualize the geothermal system comprehensively, a conceptual model is developed by integrating the geophysical model with geological and geochemical data that are correlated with each other, therefore it can assist in determining the location of production well development.","PeriodicalId":31931,"journal":{"name":"JGEET Journal of Geoscience Engineering Environment and Technology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135314911","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}