cover
Article Per Year (5 Year)
All
Home Page
OAI Link
Editorial Team
Contact
Reviewer
Google Scholar
Contact Name
Adi Suryadi
Contact Email
adisuryadi@eng.uir.ac.id
Phone
+62822 8389 6947
Journal Mail Official
jgeet@journal.uir.ac.id
Editorial Address
Jl. Kaharuddin Nasution No 113 Perhentian Marpoyan, Pekanbaru, Riau 28284
Location
Kota pekanbaru,
Riau
INDONESIA
Journal of Geoscience, Engineering, Environment, and Technology
Published by Universitas Islam Riau
ISSN : 2503216X     EISSN : 25415794     DOI : 10.25299
Core Subject : Science, Social, Engineering,
Earth & Planetary Sciences Engineering Environmental Science Physics
JGEET (Journal of Geoscience, Engineering, Environment and Technology) published the original research papers or reviews about the earth and planetary science, engineering, environment, and development of Technology related to geoscience. The objective of this journal is to disseminate the results of research and scientific studies which contribute to the understanding, development theories, and concepts of science and its application to the earth science or geoscience field. Terms of publishing the manuscript were never published or not being filed in other journals, manuscripts originating from local and International. JGEET (Journal of Geoscience, Engineering, Environment and Technology) managed by the Department of Geological Engineering, Faculty of Engineering, Universitas Islam Riau.
Arjuna Subject : -
Articles 551 Documents
 37   38   39   40   41 
1D Geomechanical Model For Wellbore Stability in Z Field, Y Well Sanga Sanga Working Area, Kutai Basin Tappi, Navrianta; Cherdasa, Jeres Rorym
Journal of Geoscience, Engineering, Environment, and Technology Vol. 8 No. 02-2 (2023): Special Issue from The 1st International Conference on Upstream Energy Techn
Publisher : UIR PRESS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25299/jgeet.2023.8.02-2.13871

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.
Machine Learning Application of Two-Dimensional Fracture Properties Estimation Nurcahya, Ardian; Alexandra, Aldenia; Zainuddin, Satria Zidane; Az-Zahra, Fatimah; Haq, M. I. Khoirul; Dharmawan, Irwan Ary
Journal of Geoscience, Engineering, Environment, and Technology Vol. 8 No. 02-2 (2023): Special Issue from The 1st International Conference on Upstream Energy Techn
Publisher : UIR PRESS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25299/jgeet.2023.8.02-2.13874

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.
Machine learning prediction of tortuosity in digital rock Akmal, Fadhillah; Dzulizar, M. Cisco Ramadhan; Rafli, Muhammad Faizal; Az-Zahra, Fatimah; Haq, M. I. Khoirul; Dharmawan, Irwan Ary
Journal of Geoscience, Engineering, Environment, and Technology Vol. 8 No. 02-2 (2023): Special Issue from The 1st International Conference on Upstream Energy Techn
Publisher : UIR PRESS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25299/jgeet.2023.8.02-2.13875

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.
Investigation of Geological Structure Using Magnetotelluric and Gravity Data Optimization on Non Volcanic Geothermal, Bora, Centre of Sulawesi Pertiwi, Tiaraningtias Bagus; Daud, Yunus; Fahmi, Fikri
Journal of Geoscience, Engineering, Environment, and Technology Vol. 8 No. 02-2 (2023): Special Issue from The 1st International Conference on Upstream Energy Techn
Publisher : UIR PRESS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25299/jgeet.2023.8.02-2.13876

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.
Possibilities Study of a Non-condensable Gas Exhaust System through the Condensate Injection Pipe at PLTP Wayang Windu Nurlatifah, Annisa; Purwakusumah, Anton
Journal of Geoscience, Engineering, Environment, and Technology Vol. 8 No. 02-2 (2023): Special Issue from The 1st International Conference on Upstream Energy Techn
Publisher : UIR PRESS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25299/jgeet.2023.8.02-2.13878

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.
Seismic Vulnerability Analysis Using the Horizontal to Vertical Spectral Ratio (HVSR) Method on the West Palu Bay Coastline Amirudin; Madrinovella, Iktri; Sofian
Journal of Geoscience, Engineering, Environment, and Technology Vol. 8 No. 02-2 (2023): Special Issue from The 1st International Conference on Upstream Energy Techn
Publisher : UIR PRESS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25299/jgeet.2023.8.02-2.13879

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.
Analysis of Petrophysical Parameter on Shaly Sand Reservoir by Comparing Conventional Method and Shaly Sand Method in Vulcan Subbasin, Northwest Australia Johanna, Ulrike; Kusumah, Epo Prasetya
Journal of Geoscience, Engineering, Environment, and Technology Vol. 8 No. 02-2 (2023): Special Issue from The 1st International Conference on Upstream Energy Techn
Publisher : UIR PRESS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25299/jgeet.2023.8.02-2.13880

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.
Field Development with Scenario Reactivation of Non-Active Zones Through Reservoir Simulation: A Case Study of The Kappa Offshore Field, West Natuna Budi, Iwan Setya; Sumolang, Christianov Agassi Batistuta
Journal of Geoscience, Engineering, Environment, and Technology Vol. 8 No. 02-2 (2023): Special Issue from The 1st International Conference on Upstream Energy Techn
Publisher : UIR PRESS

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

This research provides the scenario of a field development plant with the primary goal of acknowledging the reservoir model of Kappa Field in determining the optimum field development scenario to increase the recovery factor. In this research, field development will be carried out by creating scenarios that differentiate certain parameters to see the differences from these scenarios. The main problem in this field is to find out the feasibility of a field that has a history of production from 1986 to 2022 or for 33 years. In addition, the main objective of this research is to determine the reservoir driving mechanism of the Pasir RH-7 layer and determine the best field development scenario to optimize production in the Kappa field. The method used in this study is the reservoir modeling method using production data and reservoir data that has been obtained from the company and then managed using the Petrel Software assisted by Eclipse and MatBal. Before developing field development scenarios, an analysis is carried out using several different methods, including analysis with the decline curve analysis method in determining the remaining recoverable reserves as the validation of Kappa Field's feasibility, identify the driving mechanism of the reservoir, and history matching between history production data with simulation results. Sensitivity analysis of the field development is also conducted through various scenarios, including adding or adjusting well perforation interval, infill well adding, five water injection wells, and four gas injection wells. Other than that, injection gas and water rates in injection wells are also being exercised during the sensitivity analysis. Simulation results show the best scenario of Kappa Field is ten infill wells and four injection wells with a water injection rate of 1000 BWPD and gas injection rate of 1 MMSCF/d, giving the optimum recovery factor result of 39.33% from oil reserves. The results of this research will have a positive impact on the development of the Kappa field in order to increase production from fields that have been producing since 1986 and stopped production in 2019.
Stress Analysis of Existing Underground Gas Pipeline due to New Road Crossing with ODOL Transportation Tsamara, Taqiya; Puja, IGN Wiratmaja
Journal of Geoscience, Engineering, Environment, and Technology Vol. 8 No. 02-2 (2023): Special Issue from The 1st International Conference on Upstream Energy Techn
Publisher : UIR PRESS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25299/jgeet.2023.8.02-2.13882

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.
Ambient Noise Data Processing to Obtain Group Velocity for Subsurface Structure Identification: Preliminary Research in Hululais Geothermal Field, Sumatra, Indonesia Tavip Dwikorianto; Daud, Yunus; Agustya Adi Martha; Aditya A Juanda
Journal of Geoscience, Engineering, Environment, and Technology Vol. 8 No. 02-2 (2023): Special Issue from The 1st International Conference on Upstream Energy Techn
Publisher : UIR PRESS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25299/jgeet.2023.8.02-2.13883

Abstract

Hululais area lies in the pull-apart basins of the Ketaun Segment and Musi Segment fault as a part of the Sumatra Fault Zone (SFZ). The boundary normal faults of pull-apart basins play an important role as major discharge zones for geothermal fluid because the extensional stress is concentrated in the boundary normal faults. In order to identify the geothermal reservoir structure in Hululais Geothermal Field (HGF), we introduce the local-scale study of the Rayleigh wave group velocity structure using ambient noise tomography (ANT). The ANT studies were collected using 18 seismometers inside 12 km2 area with a spacing of 125 – 500 meters, deployed across the fault structure for 1 month. More than two thousand Rayleigh Green’s Functions are extracted by cross-correlation at available station pairs. Using the estimated green function in this preliminary research, the group velocity as a function of the period can measure the dispersion curve by using multiple filter technique (MFT) and fast marching surface tomography (FMST) scheme to obtain group velocity images. The tomography result as group velocity image shows the subsurface Rayleigh wave structure variation. The NW-SE main structure is reflected by the contrast velocity structure between the central part and the north eastern-south western sides. The central part shows the low periods which are associated with low wave velocity However the margin of the central part shows the high velocity in all periods. The ANT studies have been efficient in time and cost, however useful in subsurface structure interpretation in Hululais Geothermal Field.

Page 39 of 56 | Total Record : 551

 37   38   39   40   41 

Filter by Year

2016 2025


Reset
Filter By Issues
All Issue Vol. 10 No. 02 (2025): JGEET Vol 10 No 02 : June (2025) Vol. 10 No. 3 (2025): JGEET Vol 10 No 03 : September (2025) Vol. 10 No. 1 (2025): JGEET Vol 10 No 01 : March (2025) Vol. 9 No. 04 (2024): JGEET Vol 09 No 04 : December (2024) Vol. 9 No. 3 (2024): JGEET Vol 09 No 03 : September (2024) Vol. 9 No. 2 (2024): JGEET Vol 09 No 02 : June (2024) Vol. 9 No. 1 (2024): JGEET Vol 09 No 01 : March (2024) Vol. 8 No. 4 (2023): JGEET Vol 08 No 04 : December (2023) Vol. 8 No. 3 (2023): JGEET Vol 08 No 03 : September (2023) Vol. 8 No. 2 (2023): JGEET Vol 08 No 02 : June (2023) Vol. 8 No. 1 (2023): JGEET Vol 08 No 01 : March (2023) Vol. 8 No. 02-2 (2023): Special Issue from The 1st International Conference on Upstream Energy Techn Vol. 7 No. 4 (2022): JGEET Vol 07 No 04 : December (2022) Vol. 7 No. 3 (2022): JGEET Vol 07 No 03 : September (2022) Vol. 7 No. 2 (2022): JGEET Vol 07 No 02 : June (2022) Vol. 7 No. 1 (2022): JGEET Vol 07 No 01 : March (2022) Vol. 6 No. 4 (2021): JGEET Vol 06 No 04 : December (2021) Vol. 6 No. 3 (2021): JGEET Vol 06 No 03 : September (2021) Vol. 6 No. 2 (2021): JGEET Vol 06 No 02 : June (2021) Vol. 6 No. 1 (2021): JGEET Vol 06 No 01 : March (2021) Vol. 5 No. 4 (2020): JGEET Vol 05 No 04: December 2020 Vol. 5 No. 3 (2020): JGEET Vol 05 No 03 : September (2020) Vol. 5 No. 2 (2020): JGEET Vol 05 No 02 : June (2020) Vol. 5 No. 1 (2020): JGEET Vol 05 No 01: March 2020 Vol. 4 No. 4 (2019): JGEET Vol 04 No 04: December 2019 Vol. 4 No. 3 (2019): JGEET Vol 04 No 03 : September (2019) Vol. 4 No. 2 (2019): JGEET Vol 04 No 02 : June (2019) Vol. 4 No. 1 (2019): JGEET Vol 04 No 01 : March (2019) Vol 4 No 1 (2019): JGEET Vol 04 No 01 : March (2019) Vol. 4 No. 2-2 (2019): Special Edition (Geology, Geomorphology and Tectonics of India) Vol. 3 No. 4 (2018): JGEET Vol 03 No 04 : December (2018) Vol 3 No 4 (2018): JGEET Vol 03 No 04 : December (2018) Vol 3 No 3 (2018): JGEET Vol 03 No 03 : September (2018) Vol. 3 No. 3 (2018): JGEET Vol 03 No 03 : September (2018) Vol 3 No 2 (2018): JGEET Vol 03 No 02 : June (2018) Vol. 3 No. 2 (2018): JGEET Vol 03 No 02 : June (2018) Vol 3 No 1 (2018): JGEET Vol 03 No 01 : March (2018) Vol. 3 No. 1 (2018): JGEET Vol 03 No 01 : March (2018) Vol. 2 No. 4 (2017): JGEET Vol 02 No 04 : December (2017) Vol 2 No 4 (2017): JGEET Vol 02 No 04 : December (2017) Vol. 2 No. 3 (2017): JGEET Vol 02 No 03 : September (2017) Vol 2 No 3 (2017): JGEET Vol 02 No 03 : September (2017) Vol. 2 No. 2 (2017): JGEET Vol 02 No 02 : June (2017) Vol 2 No 2 (2017): JGEET Vol 02 No 02 : June (2017) Vol 2 No 1 (2017): JGEET Vol 02 No 01 : March (2017) Vol. 2 No. 1 (2017): JGEET Vol 02 No 01 : March (2017) Vol. 1 No. 1 (2016): JGEET Vol 01 No 01 : December (2016) Vol 1 No 1 (2016): JGEET Vol 01 No 01 : December (2016) More Issue