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"Penelitian mengenai tekanan pori dilakukan pada Formasi Talang Akar dan Baturaja, Sub-Cekungan Jambi, Cekungan Sumatera Selatan. Cakupan penelitian berfokuskan pada wilayah yang mengalami overpressure atau tekanan pori melebihi normal. Analisis mengenai tekanan pori dilakukan sebagai upaya mengoptimalkan proses pengeboran di wilayah yang akan dilakukan pengembangan sumur. Pengolahan data terbagi menjadi dua, yaitu pengolahan tekanan pori pada data sumur dan penyebarannya menggunakan data seismik. Dalam melakukan estimasi nilai tekanan pori pada sumur, digunakan metode dasar tekanan pori, yaitu metode Eaton. Selanjutnya, dilakukan penyebaran tekanan pori pada data seismik menggunakan neural network dengan data masukan berupa kecepatan gelombang P dan inversi impedansi elastik. Penggunaan data tersebut dipilih karena cukup efektif dalam melakukan estimasi persebaran tekanan pori yang dikontrol oleh keberadaan litologi dan fluida. Selain itu, dilakukan pemodelan substitusi fluida guna menguatkan analisis persebaran gas pasiran.Dari pengolahan data didapatkan bahwa terdapat zona overpressure di Formasi Talang Akar dengan kedalaman 6030.184 ft - 6368.5 ft. Sedangkan pada Formasi Batu Raja tidak terlihat anomali tekanan pori yang signifikan. Keberadaan fluida hidrokarbon berupa gas pasiran di antara litologi shale dan keberadaan struktur patahan diduga menjadi penyebab terjadinya anomali berupa overpressure.

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Research on pore pressure was carried out in the Talang Akar and the Batu raja Formation, Jambi Sub-Basin, South Sumatra Basin. The scope of research focuses on areas that experience overpressure or the pore pressure exceeds normal. Analysis of pore pressure is carried out as an effort to optimize the drilling process in areas where well development will be carried out. The data processing is divided into two, namely the processing of pore pressure in the well data and its distribution using seismic data. In estimating the value of pore pressure in drilling wells, the basic method for calculating pore pressure is used, namely the Eaton method. Next, the distribution of pore pressure estimates on seismic data is carried out using a neural network with input data in the form of P wave velocity and elastic impedance inversion. The use of input data was chosen because it is quite effective in estimating the pore pressure distribution which is controlled by the presence of lithology and fluids. In addition, fluid substitution modeling was carried out to strengthen the analysis of the distribution of sandy gas.

From the data processing carried out, it was found that there are zones overpressure in the Talang Akar Formation with a depth of 6030.184 ft to 6368.5 ft. Whereas in the Batu Raja Formation there is no significant pore pressure anomaly. The presence of hydrocarbon fluids in the form of sandy gas between lithology shale and the existence of a fault structure is thought to be the cause of the anomaly in the form of overpressure."

"Cekungan Banggai memiliki potensi hidrokarbon yang terakumulasi pada reservoir karbonat dengan porositas ganda – porositas primer dan sekunder akibat diagenesis. Hal tersebut menyebabkan variasi nilai porositas secara vertikal maupun lateral sehingga menyulitkan identifikasi zona hidrokarbon yang potensial. Untuk mengidentifikasi zona reservoir karbonat dengan porositas ganda, penelitian ini mengintegrasikan metode inversi seismik, multiatribut seismik, dan Probabilistic Neural Network (PNN), yang bertujuan untuk meningkatkan akurasi dalam pemodelan karakteristik reservoir. Hasil penelitian menunjukkan bahwa karbonat build-up Formasi Mantawa memiliki impedansi akustik rendah (6200–10000 m/s*g/cc), porositas tinggi (21%–28%), dan saturasi air rendah (30%–47%), yang mengindikasikan adanya batuan berpori yang mengandung hidrokarbon. Diharapkan dengan penerapan integrasi metode tersebut, distribusi reservoir, porositas, dan saturasi air dapat dipetakan dengan lebih akurat berdasarkan hasil dari prediksi Probabilistic Neural Network (PNN) dan membuka peluang eksplorasi lebih lanjut di zona prospektif Lapangan ZENA.

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The Banggai Basin has hydrocarbon potential accumulated in carbonate reservoirs with dual porosity – primary and secondary porosity due to diagenesis. This causes variations in porosity values both vertically and laterally, making it difficult to identify potential hydrocarbon zones. To identify carbonate reservoir zones with dual porosity, this study integrates seismic inversion methods, multi-attribute seismic analysis, and Probabilistic Neural Network (PNN), aimed at improving the accuracy of reservoir characteristic modeling. The results show that the carbonate build-up of the Mantawa Formation has low acoustic impedance (6200–10000 m/s*g/cc), high porosity (21%–28%), and low water saturation (30%–47%), indicating the presence of porous rocks containing hydrocarbons. It is expected that with the application of the integration of these methods, the distribution of the reservoir, porosity, and water saturation can be mapped more accurately based on the results from the predictions of the Probabilistic Neural Network (PNN), thus opening up further exploration opportunities in the prospective zones of the ZENA Field."

"Cekungan Banggai memiliki potensi hidrokarbon yang terakumulasi pada reservoir karbonat dengan porositas ganda – porositas primer dan sekunder akibat diagenesis. Hal tersebut menyebabkan variasi nilai porositas secara vertikal maupun lateral sehingga menyulitkan identifikasi zona hidrokarbon yang potensial. Untuk mengidentifikasi zona reservoir karbonat dengan porositas ganda, penelitian ini mengintegrasikan metode inversi seismik, multiatribut seismik, dan Probabilistic Neural Network (PNN), yang bertujuan untuk meningkatkan akurasi dalam pemodelan karakteristik reservoir. Hasil penelitian menunjukkan bahwa karbonat build-up Formasi Mantawa memiliki impedansi akustik rendah (6200–10000 m/s*g/cc), porositas tinggi (21%–28%), dan saturasi air rendah (30%–47%), yang mengindikasikan adanya batuan berpori yang mengandung hidrokarbon. Diharapkan dengan penerapan integrasi metode tersebut, distribusi reservoir, porositas, dan saturasi air dapat dipetakan dengan lebih akurat berdasarkan hasil dari prediksi Probabilistic Neural Network (PNN) dan membuka peluang eksplorasi lebih lanjut di zona prospektif Lapangan ZENA.

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The Banggai Basin has hydrocarbon potential accumulated in carbonate reservoirs with dual porosity – primary and secondary porosity due to diagenesis. This causes variations in porosity values both vertically and laterally, making it difficult to identify potential hydrocarbon zones. To identify carbonate reservoir zones with dual porosity, this study integrates seismic inversion methods, multi-attribute seismic analysis, and Probabilistic Neural Network (PNN), aimed at improving the accuracy of reservoir characteristic modeling. The results show that the carbonate build-up of the Mantawa Formation has low acoustic impedance (6200–10000 m/s*g/cc), high porosity (21%–28%), and low water saturation (30%–47%), indicating the presence of porous rocks containing hydrocarbons. It is expected that with the application of the integration of these methods, the distribution of the reservoir, porosity, and water saturation can be mapped more accurately based on the results from the predictions of the Probabilistic Neural Network (PNN), thus opening up further exploration opportunities in the prospective zones of the ZENA Field."

"Lebong, Bengkulu merupakan salah satu zona prospek panas bumi yang dilalui oleh sesar aktif, yaitu Sesar Sumatera, yang berperan penting dalam mengontrol sistem panas bumi di wilayah tersebut. Informasi terkait distribusi densitas batuan bawah permukaan di zona ini masih terbatas, terlepas dari pentingnya karakteristik densitas dalam mengidentifikasi jalur migrasi fluida panas bumi dan zona reservoir. Penelitian ini bertujuan untuk mengidentifikasi distribusi densitas bawah permukaan di daerah prospek panas bumi Lebong melalui pemodelan inversi 3D data gravitasi. Pengukuran gravitasi dilakukan dengan jarak antar titik 250 meter pada area seluas 12 × 10 km. Data yang diperoleh dikoreksi menggunakan koreksi udara bebas, Bouguer (dengan densitas rata-rata 2,5 gr/cc berdasarkan metode Parasnis dan Nettleton), serta koreksi medan, hingga dihasilkan peta anomali Bouguer lengkap. Pemodelan dilakukan dengan pendekatan unconstrained dan constrained inversion yang memanfaatkan pendekatan Cartesian Cut Cell (CCC) dan algoritma Iterative Reweighting Inversion (IRI) Interpretasi hasil pemodelan dikorelasikan dengan data magnetotellurik (MT) dan peta geologi. Hasil analisis menunjukkan adanya zona densitas rendah yang memanjang searah struktur sesar dan terpusat di area graben, yang diinterpretasikan sebagai jalur utama migrasi fluida panas bumi pada zona prospek Lebong.

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Lebong, Bengkulu is one of the geothermal prospect zones traversed by an active fault, the Sumatra Fault, which plays a significant role in controlling the geothermal system in the area. However, information related to the subsurface rock density distribution in this zone remains limited, despite the importance of density characteristics in identifying fluid migration pathways and reservoir zones. This study aims to identify the subsurface density distribution in the Lebong geothermal prospect area through 3D gravity inversion modeling. Gravity measurements were conducted with a 250-meter station spacing across an area of 12 × 10 km. The acquired data were corrected using free-air correction, Bouguer correction (with an average density of 2.5 g/cc based on the Parasnis and Nettleton methods), and terrain correction, resulting in a complete Bouguer anomaly (CBA) map. Inversion modeling was performed using both unconstrained and constrained, which utilizes the Cartesian Cut Cell (CCC) method and the Iterative Reweighting Inversion (IRI) algorithm). Interpretation of the modeling results was supported by magnetotelluric (MT) and geological data. The analysis revealed a low-density zone trending parallel to the fault structure and centered in the graben area, which is interpreted as the main fluid migration pathway in the Lebong geothermal prospect zone."