Implementasi Seabed Survey Data Model (SSDM) dalam Identifikasi Potensi Geohazard pada Proses Instalasi Bawah Laut Menggunakan Data Hidro-Akustik

Azizah, Fadilah Narlika Nurul Azizah (2025) Implementasi Seabed Survey Data Model (SSDM) dalam Identifikasi Potensi Geohazard pada Proses Instalasi Bawah Laut Menggunakan Data Hidro-Akustik. Other thesis, Institut Teknologi Sepuluh Nopember.

Text 5016211064-Undergraduate_Thesis.pdf Restricted to Repository staff only Download (5MB) | Request a copy

Abstract

Pertumbuhan populasi dan meningkatnya aktivitas ekonomi digital mendorong kebutuhan akan energi dan jaringan komunikasi global yang semakin tinggi. Berdasarkan laporan dari Kementrian Energi dan Sumber Daya Mineral (ESDM), konsumsi minyak dan gas bumi di Indonesia meningkat signifikan dari 465 juta barel pada 2018 menjadi 505 juta barel pada 2023. Di sisi lain, jumlah pengguna internet di Indonesia mencapai 221 juta orang pada 2024, sehingga kebutuhan pembangunan infrastruktur bawah laut seperti pipa dan kabel komunikasi juga meningkat. Namun, proses instalasi infrastruktur bawah laut menghadapi tantangan besar akibat kondisi fisik dan geologi dasar laut, seperti morfologi yang tidak rata, arus kuat, serta potensi geohazard yang dapat berdampak pada kerusakan struktur dan lingkungan. Penelitian ini bertujuan untuk mendeteksi kondisi topografi dasar laut, mengidentifikasi jenis-jenis sedimen, serta menganalisis fitur dasar laut yang berpotensi menjadi geohazard. Selain itu, penelitian ini juga bertujuan untuk mengimplementasikan Seabed Survey Data Model (SSDM) sebagai sistem pengelolaan data survei dasar laut yang sesuai dengan standar International Association Oil and Gas Producers (IOGP). Hasil penelitian menunjukkan bahwa kedalaman area survei berkisar antara -7,67 hingga -200,32 meter dengan variasi morfologi mulai dari datar hingga kemiringan curam di atas 30%, terutama pada area sea channel. Analisis mosaik backscatter dengan rentang -36 hingga -61 dB menghasilkan klasifikasi tujuh jenis sedimen utama, yaitu coarse silt, sandy silt, fine silt, sandy clay, very fine silt, silty clay, dan clay dengan dominasi sedimen clay sebesar 65,2% dari total area survei. Data Sub-Bottom Profiler (SBP) menunjukkan bahwa lapisan sedimen hanya terdiri dari satu lapisan utama tanpa adanya struktur sub-seabed yang berbeda, ditandai dengan munculnya sinyal pantulan ganda (multiple). Selain itu, identifikasi fitur dasar laut berhasil mendeteksi adanya sea channel, mound, escarpment, reef, sediment wave, dan furrow yang berpotensi menjadi geohazard. Seluruh data survei diintegrasikan ke dalam SSDM berbasis Geographic Information System (GIS) yang tersusun atas empat layer utama, yaitu Bathymetry Contours, Survey Navigation Tracklines, Environmental Samples, dan Seabed Features, yang mencakup 84 lintasan Multibeam Echosounder (MBES), 49 lintasan SBP, 13 titik sampel sedimen, dan 3 titik sampel sound velocity.
=====================================================================================================================================
Population growth and the rise of digital economic activities have significantly increased the demand for energy and global communication networks. According to a report by the Ministry of Energy and Mineral Resources (ESDM), Indonesia’s oil and gas consumption rose significantly from 465 million barrels in 2018 to 505 million barrels in 2023. On the other hand, the number of internet users in Indonesia reached 221 million in 2024, driving the need for the development of subsea infrastructure such as pipelines and communication cables. However, the installation of subsea infrastructure faces major challenges due to seabed physical and geological conditions, including uneven morphology, strong currents, and potential geohazards that could lead to structural damage and environmental impacts. This study aims to detect seabed topographic conditions, identify sediment types, and analyze seafloor features with geohazard potential. In addition, it aims to implement the Seabed Survey Data Model (SSDM) as a seabed survey data management system aligned with International Association Oil and Gas Producers (IOGP) standards. The results show that the depth of the surveyed area ranges from -7.67 to -200.32 meters, with morphological variation from flat terrain to steep slopes exceeding 30%, particularly around the sea channel area. Backscatter mosaic analysis, with a range between -36 and -61 dB, led to the classification of seven main sediment types: coarse silt, sandy silt, fine silt, sandy clay, very fine silt, silty clay, and clay, which clay dominates 65.2% of the total surveyed area. SBP data indicates that the sediment consists of only a single main layer, with no distinguishable sub-seabed structure, as confirmed by the presence of multiple reflections. Furthermore, the identification of seafloor features revealed sea channels, mounds, escarpments, reefs, sediment waves, and furrows as potential geohazards. All survey data were integrated into a Geographic Information System (GIS)-based SSDM structured into four main layers: Bathymetry Contours, Survey Navigation Tracklines, Environmental Samples, and Seabed Features—comprising 84 Multibeam Echosounder (MBES) tracklines, 49 SBP tracklines, 13 sediment sampling points, and 3 sound velocity stations.

Item Type:	Thesis (Other)
Uncontrolled Keywords:	Seabed Survey Data Model, Instalasi Bawah Laut, Marine Geohazard, Survei Batimetri, Life Below Water Seabed Survey Data Model, Subsea Installation, Marine Geohazard, Bathymetry Survey, Life Below Water
Subjects:	G Geography. Anthropology. Recreation > G Geography (General) > G70.212 ArcGIS. Geographic information systems. G Geography. Anthropology. Recreation > G Geography (General) > G70.217 Geospatial data T Technology > TA Engineering (General). Civil engineering (General) > TA169.5 Failure analysis
Divisions:	Faculty of Civil Engineering and Planning > Geomatics Engineering > 29202-(S1) Undergraduate Thesis
Depositing User:	Fadilah Narlika Nurul Azizah
Date Deposited:	24 Jul 2025 05:50
Last Modified:	24 Jul 2025 05:50
URI:	http://repository.its.ac.id/id/eprint/120791

Actions (login required)

View Item