URNADA, DITA SYIVA (2025) ANALISIS INVERSI ACOUSTIC IMPEDANCE (AI) DAN MULTIATRIBUT PROBABILISTIC NEURAL NETWORK (PNN) UNTUK KARAKTERISASI RESERVOIR PADA LAPANGAN “ULTRAMAN”. Skripsi thesis, UPN Veteran Yogyakarta.
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Abstract
ABSTRAK
ANALISIS INVERSI ACOUSTIC IMPEDANCE (AI) DAN
MULTIATRIBUT PROBABILISTIC NEURAL NETWORK (PNN)
UNTUK KARAKTERISASI RESERVOIR PADA LAPANGAN
“ULTRAMAN”
Oleh
Dita Syiva Urnada
NIM: 115210013
(Program Studi Sarjana Teknik Geofisika)
Lapangan “Ultraman” merupakan salah satu lapangan gas di Cekungan Jawa Timur
yang memiliki reservoir utama pada Globigerina Limestone di Formasi Mundu dan
Paciran. Penelitian ini bertujuan untuk mengidentifikasi persebaran litologi,
porositas, dan fluida hidrokarbon dalam reservoir menggunakan pendekatan inversi
Acoustic Impedance (AI) berbasis model dan prediksi multiatribut berbasis
Probabilistic Neural Network (PNN). Data yang digunakan meliputi seismik 3D
hasil Post-Stack Time Migration (PSTM) dan empat data sumur. Interpretasi
seismik mengungkap keberadaan antiklin asimetris berorientasi barat–timur yang
dipotong oleh sesar normal, dengan zona puncaknya diduga sebagai lokasi
akumulasi gas biogenik.
Hasil inversi AI dan prediksi PNN berhasil memetakan distribusi properti bawah
permukaan, yaitu AI, volume clay (VCL), dan porositas efektif (PHIE), secara
spasial. Distribusi VCL menunjukkan dominasi Globigerina Limestone berpori
pada interval T60U dan Globigerina Limestone padat (tight) pada T60L, sementara
interval T65 didominasi oleh shale pelagik yang berfungsi sebagai segel regional.
Zona prospek pada T60U ditandai dengan nilai AI 3000–4000 g.m/cm³.s, VCL 0
15%, PHIE 0.38–0.50 ft³/ft³, serta saturasi air (SW) 0–0.2, menunjukkan indikasi
kuat kehadiran gas biogenik di kedua puncak antiklin. Adapun interval T60L
memperlihatkan indikasi gas hanya di antiklin barat, dengan nilai AI 4000–5000
g.m/cm³.s, VCL 0–5%, dan PHIE 0.4–0.45 ft³/ft³. Integrasi seluruh metode ini
menunjukkan efektivitas kombinasi inversi dan PNN dalam karakterisasi reservoir
karbonat di lingkungan geologi kompleks.
Kata kunci: Batugamping Globigerina, Gas Biogenik, Inversi AI, Multiatribut PNN
vi
ABSTRACT
ANALYSIS OF ACOUSTIC IMPEDANCE (AI) INVERSION AND
PROBABILISTIC NEURAL NETWORK (PNN) BASED MULTI
ATTRIBUTE APPROACH FOR RESERVOIR
CHARACTERIZATION IN THE “ULTRAMAN” FIELD
By
Dita Syiva Urnada
NIM: 115210103
(Geophysical Engineering Undergraduated Program)
The “Ultraman” Field is one of the gas-bearing fields located in the East Java
Basin, with its main reservoirs found in the Globigerina Limestone of the Mundu
and Paciran Sequences. This study aims to identify the distribution of lithology,
porosity, and hydrocarbon presence in the Globigerina limestone reservoir using
model-based Acoustic Impedance (AI) inversion and multi-attribute Probabilistic
Neural Network (PNN) prediction. The data used includes 3D marine seismic data
processed with Post-Stack Time Migration (PSTM) and four well logs. Seismic
interpretation reveals an asymmetrical anticline structure trending west–east, cut
by several normal faults, where the crest zones are interpreted as the main biogenic
gas accumulation sites.
The AI inversion and PNN multi-attribute predictions successfully provided spatial
estimations of subsurface physical properties such as AI, VCL (volume of clay), and
PHIE (effective porosity). Lithological distribution from the VCL model indicates
a dominance of porous Globigerina Limestone in the upper reservoir zone (T60U)
and tight limestone in the lower zone (T60L), while thick pelagic shale in the T65
interval acts as an effective regional seal. The prospect zone in T60U is
characterized by AI values from 3000 to 4000 g.m/cm³.s, VCL between 0 and 15%,
PHIE starting from 0.38 to 0.50 ft³/ft³, and SW between 0 and 0.2, indicating
biogenic gas presence at both anticline crests. In contrast, T60L shows gas
indication only in the western anticline with AI values from 4000 to 5000 g.m/cm³.s,
VCL less than 5%, and PHIE between 0.4 and 0.45 ft³/ft³. The integration of AI
inversion and PNN modeling demonstrates high effectiveness in reservoir
characterization within a structurally complex carbonate setting.
Keywords: Globigerina Limestone, Biogenic Gas, AI Inversion, Multiattribute PNN
vii
| Item Type: | Tugas Akhir (Skripsi) |
|---|---|
| Uncontrolled Keywords: | Globigerina Limestone, Biogenic Gas, AI Inversion, Multiattribute PNN |
| Subjek: | Q Science > QE Geology |
| Divisions: | Fakultas Teknologi Mineral dan Energi > (S1) Teknik Geofisika |
| Depositing User: | Eko Yuli |
| Date Deposited: | 13 Oct 2025 04:29 |
| Last Modified: | 13 Oct 2025 04:29 |
| URI: | http://eprints.upnyk.ac.id/id/eprint/44264 |
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