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"Inversi seismik deterministik sudah banyak digunakan dalam lapangan eksplorasi dan pengembangan. Metode ini digunakan sebagai salah satu cara untuk karakterisasi reservoir dengan menghilangkan efek wavelet sehingga dapat membantu interpreter untuk memetakan struktur bawa permukaan dengan lebih baik. Akan tetapi, metode ini memiliki limitasi karena menggunakan impedansi rata-rata dari layer seismik dimana pada umumnmya nilai impendansi lebih kecil daripada impedansi data sumur sehingga dihasilkan model inversi yang tidak sesuai. Metode inversi stokastik menggunakan konsep geostatistikal, dimana variogram berperan penting dalam menghasilkan output yang sesuai. Pada inversi stokastik dihasilkan banyak realisasi inversi yang digunakan sebagai basis dalam analisis uncertainty, tiap realisasi akan sama pada tiap lokasi sumur yang digunakan namun akan berubah seiring dengan bertambahnya jarak spasial dari lokasi sumur. Metode inversi stokastik akan diaplikasikan pada lapangan gas “K” yang terletak di lepas pantai cekungan Bonaparte, Indoensia Timur. Data yang tersedia antara lain, sebagian dari 3D PSTM angle gather dengan luasan 1,300 km2, 3 sumur dengan data P-Sonic, S-Sonic, densitas, Gamma Ray, dan log resistivitas. Tambahan data berupa report komplesi dan report well testing tersedia untuk beberapa sumur. Lapangan gas “K” terletak pada undeformed continental margin Australia yang melampar kearah lndonesia, dimana secara geologi lapangan “K” terletak pada area Timur dari Sahul Platform dan memiliki struktur berupa tiltef fault block. Lapangan ini memiliki reservoir batupasir formasi Plover yang tersaturasi gas dengan hidrokarbon kolom cukup signifikan, dimana reservoir terdeposisi pada lingkungan shallow marine pada umur Middle Jurasic. Target utama pada lapangan gas “K” merupakan strukutural trap berupa horst block, tilted fault block yang berada dibawah sub-unconformity di umur Palaezoic. Penerapan metode inversi stokastik pada lapangan gas “K” menghasilkan kelebihan yang cukup signifikan dibandingkan dengan inversi deterministik. Reservoir pada lapangan gas “K” terdiri dari batupasir dengan persilangan shale tipis. Metode inversi stokastik dapat membedakan antara batupasir yang tersaturasi gas dengan intraformational shale tipis yang tidak teresolusi oleh seismik dan inversi deterministik. Hasil realisasi dapat digunakan untuk analisis uncertainty dengan probabilitas P10, P50, dan P90 dari facies yang dihasilkan.

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Deterministic seismik inversion method has been successfully used in various projects in exploration and development. This method enables the interpreter to get better understanding of subsurface by omitting the wavelet and tuning effects therefore quantitative reservoir properties can be generated. However, this method has significant limitation by generating average impedances of each layer, and the range of values is smaller than the impedance from the wells therefore the inversion will not produce results that are not within the calibration range. Stochastic seismik inversion is done by conditioning well data and reproducing spatially varying statistics using variogram which could overcome the deterministic limitation. This method generates multiple realizations of high-frequency elastic properties that are consistent with both seismik amplitude and well data. In such instances, stochastic seismik inversion method could provide the uncertainties associated with the models that have been generated. The proposed method is applied in “K” gas field which located in the offshore Bonaparte Basin, Eastern Indonesia. The available dataset for this work includes : part of PSTM 3D which cover 1,300 km2 in angle gather, and 3 wells with compressional sonic, shear sonic, density, gamma ray, and resistivity logs. Additional well completion and well testing reports are available for some wells. Geologically, the “K” field is located within relatively undeformed Australian continental margin that extends into Indonesian waters. It lies on the eastern extremity of the Sahul Platform and occupies a large tilted fault block bounded to the east and south by the Calder-Malita Grabens. This field contains a significant gas column, reservoired within shallow marine, highly mature, quartzose sandstone of the Middle Jurassic Plover Formation. Potential targets in the area may be large folds, horst blocks, tilted fault blocks ad sub-unconformity traps in the Palaeozoic section. The application of stochastic seismik inversion showed significant benefits compared to deterministic especially in “K” gas field where the reservoirs are stacked sandstone with intraformational shale. Some of the reservoir and all the intraformational shales are below seismik resolution. Stochastic seismic inversion able to distinguish those features, in addition the inverted volumes with multiple realizations with ranking criteria for P10, P50, and P90 of facies could be utilized to reduce the risk associated with exploration plan and field development."

"Inversi seismik deterministik sudah banyak digunakan dalam lapangan eksplorasi dan pengembangan. Metode ini digunakan sebagai salah satu cara untuk karakterisasi reservoir dengan menghilangkan efek wavelet sehingga dapat membantu interpreter untuk memetakan struktur bawah permukaan dengan lebih baik. Akan tetapi, metode ini memiliki limitasi karena menggunakan impedansi rata-rata dari layer seismik dimana pada umumnmya nilai impendansi lebih kecil daripada impedansi data sumur sehingga dihasilkan model inversi yang tidak sesuai. Metode inversi stokastik menggunakan konsep geostatistikal, dimana variogram berperan penting dalam menghasilkan output yang sesuai. Pada inversi stokastik dihasilkan banyak realisasi inversi yang digunakan sebagai basis dalam analisis uncertainty, tiap realisasi akan sama pada tiap lokasi sumur yang digunakan namun akan berubah seiring dengan bertambahnya jarak spasial dari lokasi sumur. Metode inversi stokastik akan diaplikasikan pada lapangan gas K yang terletak di lepas pantai cekungan Bonaparte, Indoensia Timur. Data yang tersedia antara lain, sebagian dari 3D PSTM angle gather dengan luasan 1,300 km2, 3 sumur dengan data P-Sonic, S-Sonic, densitas, Gamma Ray, dan log resistivitas. Tambahan data berupa report komplesi dan report well testing tersedia untuk beberapa sumur. Lapangan gas K terletak pada undeformed continental margin Australia yang melampar kearah lndonesia, dimana secara geologi lapangan K terletak pada area Timur dari Sahul Platform dan memiliki struktur berupa tilted fault block. Lapangan ini memiliki reservoir batupasir formasi Plover yang tersaturasi gas dengan hidrokarbon kolom cukup signifikan, dimana reservoir terdeposisi pada lingkungan shallow marine pada umur Middle Jurasic. Target utama pada lapangan gas K merupakan struktural trap berupa horst block, tilted fault block yang berada dibawah sub-unconformity di umur Palaezoic. Penerapan metode inversi stokastik pada lapangan gas K menghasilkan kelebihan yang cukup signifikan dibandingkan dengan inversi deterministik. Reservoir pada lapangan gas K terdiri dari batupasir dengan persilangan shale tipis. Metode inversi stokastik dapat membedakan antara batupasir yang tersaturasi gas dengan intraformational shale tipis yang tidak teresolusi oleh seismik dan inversi deterministik. Hasil realisasi dapat digunakan untuk analisis uncertainty dengan probabilitas P10, P50, dan P90 dari facies yang dihasilkan.

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Deterministic seismic inversion method has been successfully used in various projects in exploration and development. This method enables the interpreter to get better understanding of subsurface by omitting the wavelet and tuning effects therefore quantitative reservoir properties can be generated. However, this method has significant limitation by generating average impedances of each layer, and the range of values is smaller than the impedance from the wells therefore the inversion will not produce results that are not within the calibration range. Stochastic seismic inversion is done by conditioning well data and reproducing spatially varying statistics using variogram which could overcome the deterministic limitation. This method generates multiple realizations of high-frequency elastic properties that are consistent with both seismic amplitude and well data. In such instances, stochastic seismic inversion method could provide the uncertainties associated with the models that have been generated. The proposed method is applied in K gas field which located in the offshore Bonaparte Basin, Eastern Indonesia. The available dataset for this work includes : part of PSTM 3D which cover 1,300 km2 in angle gather, and 3 wells with compressional sonic, shear sonic, density, gamma ray, and resistivity logs. Additional well completion and well testing reports are available for some wells. Geologically, the K field is located within relatively undeformed Australian continental margin that extends into Indonesian waters. It lies on the eastern extremity of the Sahul Platform and occupies a large tilted fault block bounded to the east and south by the Calder-Malita Grabens. This field contains a significant gas column, reservoired within shallow marine, highly mature, quartzose sandstone of the Middle Jurassic Plover Formation. Potential targets in the area may be large folds, horst blocks, tilted fault blocks ad sub-unconformity traps in the Palaeozoic section. The application of stochastic seismic inversion showed significant benefits compared to deterministic especially in K gas field where the reservoirs are stacked sandstone with intra-formational shale. Some of the reservoir and all the intraformational shales are below seismic resolution. Stochastic seismic inversion able to distinguish those features, in addition the inverted volumes with multiple realizations with ranking criteria for P10, P50, and P90 of facies could be utilized to reduce the risk associated with exploration plan and field development."

"Reservoir batupasir pada Lapangan OA terletak pada Cekungan Northern Bonaparte merupakan batupasir yang tersaturasi gas, diagenesis mineral menyebabkan beberapa daerah zona reservoir menjadi tight sandstone. Metode inversi menggunakan impedansi akustik (AI) kurang sensitif dalam membedakan litologi batupasir dan batu lempung karena memiliki nilai impedansi yang hampir sama. Simultaneous Inversion mengatasi masalah tersebut dengan melakukan inversi secara bersamaan melalui data partial angle (near, mid, far) untuk mendapatkan parameter fisis selain impedansi akustik yang diharapkan lebih sensitif dalam membedakan litologi maupun memprediksi keberadaan fluida gas seperti impedansi shear (SI) dan densitas. Ketiga parameter tersebut dapat diturunkan menjadi parameter Lame(LMR). Analisa crossplot menunjukan parameter fisis yang sensitif untuk memprediksi persebaran litologi maupun keberadaan fluida gas. Parameter densitas cukup sensitif dalam membedakan litologi yang kemudian dilakukan inversi dengan nilai cut off clean sandstone adalah 2.3-2.5 (g/cc), tight sandstone dengan cutoff 2.5-2.625 (g/cc) dan shaledengan cutoff2.625-2.8(g/cc). Keberadaan fluida gas diprediksi dengan melakukan inversi parameter Vp/Vsyang memiliki cutoff ±1.6 dan Lambda-rho dengan cut off ±25. Analisa peta persebaran parameter tersebut menunjukan persebaran batupasir dan keberadaan fluida gas dominan berada di daerah utara zona penelitian dengan karakter batupasir yang relatif memiliki porositas yang lebih baik (clean sandstone) dibandingkan dengan daerah yang relatif lebih selatan.

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The sandstone reservoir in the OA Field is located in the Northern Bonaparte Basin, which is gas-saturated sandstone, mineral diagenesis causing several reservoir zone areas to become tight sand. The inversion method using acoustic impedance (AI) is less sensitive in distinguishing sandstone and clay rock lithology because it has almost the same impedance value. Simultaneous Inversion overcomes this problem by simultaneously inversingpartial angle data (near, mid, far) to obtain physical parameters besides acoustic impedance which are expected to be more sensitive in distinguishing lithology and predicting the presence of gas fluids such as shear impedance (SI) and density. These three parameters can be derived as Lame(LMR) parameters.

Crossplot analysis shows sensitive physical parameters to predict the distribution of lithology and the presence of gas fluid. Density sensitive in distinguishing lithology which is then inversed,obtaining clean sandstone cutoff values are 2.3-2.5 (g/cc), tight sandstonewith cutoff 2.5-2.625 (g/cc) and clay stones with cutoff2.625-2.8(g/cc). The presence of gas fluid is predicted by inversing the parameter Vp/Vswhich has a ± 1.6 and Lambda-rho cutoff of ± 25 cutoff. Analysis of the parameter distribution map shows the distribution of sandstones and the presence of dominant gas fluids in the northern area of the research zone with relatively clean sandstone characteristics, compared to relatively more southern regions."

"Lapangan “DEWI”, yang berlokasi di Cekungan Bonaparte Maluku Tenggara merupakan lapangan gas dengan reservoir utama yang terletak pada Formasi Plover, yang didominasi oleh batu pasir. Berdasarkan analisa struktur didapatkan bahwa lapangan ini memiliki satu sesar utama yang membagi blok utara dan blok selatan. Berdasarkan analisis petrofisika didapatkan bahwa zona prospek hidrokarbon dari lapangan ini terletak di formasi Plover dan Zona A. Penelitian ini bertujuan untuk menganalisis distribusi parameter petrofisika seperti porositas, volume shale, dan saturasi air yang penting dalam karakterisasi reservoir. Penelitian ini menggunakan analisis seismik multiatribut dan probabilistic neural network untuk memprediksi parameter petrofisika berdasarkan atribut dari data seismik. Hasil menunjukkan bahwa pada penelitian ini probabilistic neural network memiliki keunggulan dalam memprediksi parameter petrofisika untuk karakterisasi reservoir dibanding multiatribut konvensional. Berdasarkan hasil dari pemetaannya ditemukan variasi yang menarik dalam persebaran parameter petrofisika pada formasi Plover dan Zona A. Hasil dari penelitian ini dapat digunakan untuk menyediakan pemahaman baru dalam karakterisasi daerah berpotensi hidrokarbon di Lapangan “DEWI”.

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The “DEWI” field, which is located in the Bonaparte Basin, Southeast Maluku, is a gas field with the main reservoir located in the Plover Formation, which is dominated by sandstone. Based on structural analysis, it was found that this field has one main fault that divides the northern block and the southern block. Based on petrophysical analysis, it was found that the hydrocarbon prospect zone of this field is located in The Plover Formation and Zone A. This research aims to analyze the distribution of petrophysical parameters such as porosity, shale volume, and water saturation which are important in reservoir characterization. This research uses multi-attribute seismic analysis and probabilistic neural networks to predict petrophysical parameters based on attributes from seismic data. The results show that in this study the probabilistic neural network has advantages in predicting petrophysical parameters for reservoir characterization compared to conventional multi-attributes. Based on the results of the mapping, enticing variations were found in the distribution of petrophysical parameters in The Plover Formation and Zone A. The results of this research can be used to provide new insights into the characterization of potential hydrocarbon areas in the "DEWI" Field."

"Lapangan "IM" merupakan salah satu lapangan eksplorasi minyak dan gas bumi yang berada di Cekungan Sumatera Utara. Telah teridentifikasi sebelumnya bahwa pada lapangan ini ditemukan hidrokarbon berupa gas condensate. Penelitian ini bertujuan untuk mengarakterisasi reservoir dalam hal persebaran litologi dan kandungan fluidanya. Penelitian mencakup target reservoir karbonat yang berada pada Middle Miocene Malacca Limestone. Data yang digunakan dalam penelitian ini, yaitu data seismik 3D dan dua data sumur. Metode inversi simultan diterapkan untuk mengolah data agar tujuan penelitian dapat tercapai. Metode inversi simultan menghasilkan model Impedansi P (Zp), Impedansi S (Zs), dan Densitas. Didapatkan hasil pada reservoir gas nilai impedansi P (Zp) sekitar 16542-18917 (ft/s*g/cc) dan impedansi S (Zs) sekitar 8375 (ft/s*g/cc) sedangkan pada reservoir air nilai impedansi P (Zp) sebesar 21292-23667 (ft/s*g/cc) dan impedansi S (Zs) sekitar 18500-20525 (ft/s*g/cc). Hasil tersebut kemudian ditransformasi menjadi parameter Lame. Parameter Lame merupakan parameter elastik yang terdiri dari Lambda-Rho dan Mu-Rho. Masing-masing parameter tersebut menjelaskan mengenai sifat inkompressibilitas fluida dan kekakuan batuan. Hasil penelitian menunjukkan persebaran reservoir yang memiliki arah orientasi Barat Laut-Tenggara.

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The "IM" field is an oil and gas exploration field located in the North Sumatra Basin. It was previously identified that in this field hydrocarbons were found in the form of gas condensate. This study aims to characterize the reservoir in terms of lithological distribution and fluid content. The research includes carbonate reservoir targets located in Middle Miocene Malacca Limestone. The data used in this study are 3D seismic data and two well data. Simultaneous inversion method is applied to process data so that research objectives can be achieved. The simultaneous inversion method produces P-Impedance (Zp), S-Impedance (Zs), and Density models. The results show that in the gas reservoir the P (Zp) impedance value is around 16542-18917 (ft/s*g/cc) and the S (Zs) impedance is around 8375 (ft/s*g/cc) while in the water reservoir the P impedance value (Zp ) of 21292-23667 (ft/s*g/cc) and the impedance S (Zs) is around 18500-20525 (ft/s*g/cc). The results are then transformed into the Lame parameter. The Lame parameter is an elastic parameter consisting of Lambda-Rho and Mu-Rho. Each of these parameters explains the fluid incompressibility and rock stiffness. The results showed that the reservoir distribution had an North West-South East orientation."

"Metode seismik merupakan suatu metode geofisika yang hingga saat ini merupakan metode dipercaya dapat memberikan gambaran bawah permukaan dari suatu lapangan. Seismik inversi adalah salah satu dari banyak metode yang digunakan untuk karakterisasi reservoar. Dengan menggunakan inversi seismik simultan mampu mendapatkan jawaban yang lebih pasti dengan cara menganalisa impedansi P, impedansi S dan densitas. Lapangan X, pada zona dangkal merupakan zona produksi yang cukup menjanjikan. Sehingga, pengembangan pada zona ini cukup gencar. Namun, beberapa kali prediksi reservoar meleset dikarenakan lapisan coal yang melimpah. Sebelum melakukan analisa inversi seismik simultan, perlu diketahui terlebih dahulu hubungan sifat fisik batuan (Zp, Zs, VpVs, lamda-rho dan mhu-rho) dengan properti batuannya (densitas dan porositas). Studi kelayakan dilakukan dengan cara melakukan cross plot parameter fisik batuan untuk dapat mendefinisikan litologi dan fluida yang ada. Selanjutnya well-seismic tie dilakukan untuk mendapatkan korelasi dan koherensi antara data dari log sumur dengan data seismik. Interpretasi horison, struktur dan pembuatan model frekuensi rendah dilakukan untuk memahami keadaan geologi dari daerah penelitian. Pada akhirnya, inversi seismik simultan dapat dilakukan dengan tepat. Hasil dari analisa inversi seismik simultan adalah kisaran nilai Zp, Zs dan Dn untuk mengkarakterisasi reservoar. Selain itu, analisa mengenai LMR (lamda-mhurho) juga dilakukan untuk mendapatkan hasil yang lebih baik. Sehingga, persebaran reservoar pada daerah penelitian dapat diketahui.

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Seismic is one of the methods in geophysics that until now still reliable for sub-surface imaging and interpretation of a field. Seismic inversion is one of the methods to characterize the reservoir. Using simultaneous seismic inversion, analyzing the P-impedance, S-impedance and density can be more convenient and certain.

X Field, especially in the shallow zone is a promising production zone. Hence, development in this zone is very incentive. Unfortunately, miss prediction sometimes happens due to coal layer that abundant. Relationship between rock physic (Zp, Zs, Vp/Vs, lamda-rho and mhu-rho) and rock property (density and porosity) must be understood prior to simultaneous seismic inversion analysis. Feasibility study was conducted by cross plotting among some parameters to define the lithology and fluids.

Well-seismic tie was conducted to have a good correlation and coherency between well-log data and seismic data. Horizon, structural interpretation and low frequency model were performed to have geological understanding of research area. The result of series steps previously then analyzed to have a good quality data. Eventually, the simultaneous seismic inversion can be performed in a proper way.

Result of the simultaneous seismic inversion analysis is a value of Zp, Zs and Dn for reservoir characterization. Moreover, LMR (lamda-mhu-rho) analysis can be performed to give more preferable result. Eventually, the distribution of gas-sand reservoir can be understood."

"Karakterisasi reservoar hidrokarbon merupakan serangkaian proses yang meliputi interpretasi, analisis, serta evaluasi sebuah reservoar berdasarkan data geologi dan geofisika. Suatu reservoir hidrokarbon dapat diklasifikasikan sebagai suatu reservoar yang berkarakter ekonomis untuk eksplorasi dan produksi jika proses karakterisasi reservoir dilakukan dengan tepat secara kualitatif dan kuantitatif. Integrasi data geologi dan geofisika dapat bermanfaat bagi karakterisasi reservoar melalui pemanfaatan metode inversi seismik. Keberadaan hidrokarbon di Formasi Talang Akar, Cekungan Sumatra Selatan dianalisis menggunakan inversi seismik yang menggunakan data full-stack seismic secara model-based. Implementasi metode inversi model-based menggunakan properti seismik, yaitu impedansi akustik. Dengan mengintegrasi data sumur, dapat dihasilkan properti fisika batuan, seperti impedansi akustik gelombang-P (Zp) dan kecepatan gelombang-P (Vp). Pemanfaatan impedansi akustik dengan memperhatikan hasil analisis wavelet yang tepat untuk melaksanakan proses inversi dapat bermanfaat untuk melakukan prediksi litologi bawah permukaan penyusun reservoar hidrokarbon. Hasil inversi impedansi akustik dapat dielaborasikan untuk mendelineasi litologi sand dan shalesecara umum pada lingkungan pengendapan berupa delta-fluvial. Prediksi litologi melalui ketersediaan data Sumur BUDAPEST, CANNES, dan DEBRECEN pada reservoar pada studi penelitian ini berhasil memprediksi litologi berupa sand (Class 1) sebesar 40.89%, sand (Class 2) sebesar 38.08%, shale sebesar 37.20%, serta karbonat sebesar 53.34%.

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Hydrocarbon reservoir characterization is a series of processes that include interpretation, analysis, and evaluation of a reservoir based on geological and geophysical data. A hydrocarbon reservoir can be classified as a reservoir with economical characteristics for exploration and production if the reservoir characterization process is carried out qualitatively and quantitatively. The integration of geological and geophysical data can be useful for reservoir characterization through the use of the seismic inversion method. The presence of hydrocarbons in the Talang Akar Formation, South Sumatra Basin was analyzed using seismic inversion which uses model-based, from full-stack seismic data. The implementation of the model-based inversion method uses acoustic impedance as the property. By integrating well data, rock physics properties can be generated, such as P-wave acoustic impedance (Zp) and P-wave velocity (Vp). Utilization of acoustic impedance by taking into account the results of the appropriate wavelet analysis to carry out the inversion process can be useful for predicting subsurface lithology making up hydrocarbon reservoirs. The results of acoustic impedance inversion can be elaborated to delineate sand and shale lithologies in general in delta-fluvial depositional environments. The lithology prediction through the availability of data on the BUDAPEST, CANNES, and DEBRECEN wells in the reservoir of research in this study succeeded in predicting lithology in the form of 40.89% sand (Class 1), 38.08% sand (Class 2), 37.20% shale, and 53.34% carbonate."

"Karakterisasi Reservoar pada Lapangan Migas ?Boonsville? telah dilakukan menggunakan metode inversi seismik dan metode geostatistik. Kedua teknik tersebut saling melengkapi dimana metode inversi seismik mengacu pada data seismik sedangkan metode geostatistik mengacu pada data sumur. Dengan mengintegrasikan konsep inversi seismik dan geostatistik dapat dipetakan distribusi reservoar secara lateral. Pada studi ini, teknik inversi seismik yang digunakan adalah teknik inversi "Model Based" sedangkan teknik geostatistik yang digunakan adalah teknik "Kriging" dan "Co-Kriging". Teknik integrasi ini diaplikasikan pada data seismik 3D yang memiliki cakupan 133 inline (74 - 206), dan 97 xline (105 - 201). Data sumur yang digunakan adalah tujuh sumur yang memiliki log densitas dan log sonic. Hasil integrasi kedua teknik tersebut memperlihatkan pola persebaran reservoar dengan trend berarah dari barat daya ke timur laut.

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Reservoir characterization of ?Boonsville? Oil and Gas field has been carried out using seismic inversion and geostatistic method. These methods are completing each other, in which seismic inversion method is referring to seismic data, while geostatistic method is referring to well data. By integrating both seismic inversion and geostatistic methods, lateral reservoir distribution map could be generated.

In this study, the seismic inversion is performed by using "Model Based" inversion algorithm, while the geostatistic is carried out by using "Kriging" and "Co- Kriging" technique. This integrating technique is applied to 3D seismic data, which consists of 133 inline (74 - 206), and 97 xline (105 - 201). The well data set consists of seven wells, which is completed by sonic and density log. The result of both methods are showing reservoir distribution trend on south-west to north-east direction."

"Lapangan ‘B’ merupakan lapangan prospek hidrokarbon yang berlokasi di offshorecekungan Kutai, Kalimantan Timur. Untuk mengetahui karakterisasi reservoir lapangan‘B’, dilakukan pemodelan porositas dan saturasi air menggunakan inversi AI, multiatributseismik dan probabilistic neural network. Penelitian ini menggunakan data seismik 3DPSTM dan data sumur (AND-1, AND-2, AND-3 dan AND-4). Pada data seismik dan datasumur dilakukan inversi AI untuk mengetahui sifat litologi area penelitian. Kemudian,hasil AI ditransformasikan untuk mendapatkan model porositas. Metode multiatributseismik menggunakan beberapa atribut untuk memprediksi model porositas dan saturasiair. Setelah itu, diaplikasikan sifat non-linear dari probabilistic neural network sehinggamenghasilkan model porositas dan saturasi air hasil probabilistic neural network (PNN).Model porositas dan saturasi air transformasi AI, multiatribut seismik dan PNN divalidasidengan nilai porositas dan saturasi air data sumur untuk mengetahui apakah modelporositas dan saturasi air tersebut merepresentatifkan nilai data sumur. Validasi dilakukanpada sumur AND-1 dan AND-2. Nilai porositas dan saturasi air data sumur untuk AND-1 adalah 25.3 – 35.9% dan 45 – 60%, dan nilai porositas dan saturasi air AND-2 adalah11 – 35% dan 15 – 82%. Nilai porositas AND-1 hasil transformasi AI sekitar 16 – 67%,multiatribut seismik sekitar 11.5 – 27% dan PNN sekitar 11.5 – 27%. Nilai saturasi airAND-1 hasil multiatribut seismik sekitar 4 – 63% dan PNN sekitar 18 – 63%. Nilaiporositas AND-2 hasil transformasi AI sekitar 52 – 72%, multiatribut seismik sekitar 11– 21.5% dan PNN sekitar 11 – 21.5%. Nilai saturasi air AND-2 hasil multiatribut seismiksekitar 63 – 85% dan PNN sekitar 63 – 85%. Kemudian, metode multiatribut seismik danPNN didapatkan nilai korelasi antara parameter target dengan parameter prediksi. Modelporositas multiatribut seismik memiliki korelasi 0.840836 dan PNN memiliki korelasi0.936868. Model saturasi air multiatribut seismik memiliki korelasi 0.915254 dan PNNmemiliki korelasi 0.994566. Model porositas transformasi AI memiliki rentang yanglebih tinggi dibandingkan dengan data sumur. Model porositas dan saturasi air metodePNN memiliki rentang nilai yang cukup dekat dengan data sumur dan memiliki korelasiyang lebih tinggi dibandingkan dengan metode multiatribut seismik. Oleh sebab itu,model porositas dan saturasi air metode PNN merupakan model prediksi terbaik.Berdasarkan model PNN, reservoir zona target lapangan ‘B’ memiliki nilai impedansiakustik 25384 – 26133 ((ft/s)*(g/cc)), porositas sekitar 15 – 27% dan nilai saturasi airsekitar 11 – 63%.

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The 'B' field is a hydrocarbon prospect field located in the offshore Kutai Basin, East

Kalimantan. To determine the characterization of the ‘B’ field reservoir, porosity and

water saturation modeling was carried out using AI inversion, seismic multiattribute and

probabilistic neural network. This study uses 3D PSTM seismic data and wells data

(AND-1, AND-2, AND-3 and AND-4). In seismic data and wells data, AI inversion was

carried out to determine the lithological characteristics of the research area. Then, the AI

results were transformed to obtain a porosity model. The seismic multiattribute method

uses several attributes to predict the porosity and water saturation model. After that, the

non-linear properties of the probabilistic neural network were applied to produce the

porosity and water saturation model of the probabilistic neural network (PNN). The

porosity and water saturation model of AI transformation, seismic multiattribute and PNN

were validated with the porosity and water saturation values of the wells data to determine

whether the porosity and water saturation models represent the wells data values.

Validation was carried out on AND-1 and AND-2 wells. The porosity and water

saturation value of the well data for AND-1 around 25.3 - 35.9% and 45 - 60%, and the

porosity and water saturation value of AND-2 around 11 - 35% and 15 - 82%. The

porosity value of AND-1 as a result of AI transformation is around 16 - 67%, the seismic

multiattribute about 11.5 - 27% and the PNN about 11.5 - 27%. The water saturation value

of AND-1 resulted from seismic multiattribute around 4 - 63% and PNN around 18 - 63%.

The porosity value of AND-2 transformed by AI around 52 - 72%, the seismic

multiattribute around 11 - 21.5% and the PNN around 11 - 21.5%. The water saturation

value of AND-2 result from the seismic multiattribute around 63 - 85% and PNN around

63 - 85%. Then, the multiattribute seismic and PNN methods obtained the correlation

value between the target parameter and the predicted parameter. The seismic

multiattribute porosity model has a correlation of 0.840836 and PNN has a correlation of

0.936868. The multiattribute seismic water saturation model has a correlation of 0.915254

and PNN has a correlation of 0.994566. The AI transformation porosity model has a

higher range than the wells data. The PNN method of porosity and water saturation model

has a fairly close range of values to wells data and has a higher correlation than the

multiattribute seismic method. Therefore, the porosity and water saturation model of the

PNN method is the best prediction model. Based on the PNN model, the field target zone

reservoir 'B' has an acoustic impedance value about 25384 – 26133 ((ft/s) * (g/cc)), a

porosity of 15 - 27% and a water saturation of 11 - 63%."

"Simultaneous inversion is one of the seismic method which can be used to characterize reservoirs that may also serve as a rock source. In this research, the characterization of shale reservoir is done on the field TAF, in North Sumatra basin with Lower Baong formation as the target formation. A P impedance parameter on the simultaneous inversion method is used to identify the existence of fluids while S Impedance parameter is used to identify the lithology of the target zone. The analysis of the simultaneous inversion is done using partial angle stack method, that which consists of the near angle stack 1 19, the mid angle stack 19 36 and the far angle stack 36 53. The result of the analysis of the gas chromatography of the well data states that there are 2 layers of lithologies on the Baong Formation that which have the indications of hydrocarbon with each layer having the thickness of less than 5 meters. The result of the simultaneous inversion is obtained, with the value of P impedance ranging from 4000 8000 m s gr cc, the value of S impedance ranging from 1500 3000 m s gr cc and the value of density ranging from 2.2 2.5 g cc. These three values are assumed to correlate with the layer that is dominated by shale. The value of P impedance ranging from 8000 12000 m s gr cc, the value of S impedance ranging from 3000 5700 m s gr cc and the density value ranging from 2.5 2.75 g cc are also obtained that which are situated on the bottom of the Lower Baong formation near the top Belumai and are assumed to correlate with the other lithology that which is dominated by sandstone and carbonate. However, the result of the inversion of P Impedance and the Lambda Rho transformation, as well as the crossplot analysis of AI vs SI and the crossplot of LMR, has no indication of hydrocarbon fluids."