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Fauziah Anggraeni

Analisa zona low resistivity pada zona reservoir Lapangan Delta Di South Kutai Basin, Kalimantan Timur = Petrophysics and chemical analysis at low resistivity zone in Delta Field, South Kutai Basin, East Kalimantan

"Lapangan Delta di Mahakam cekungan lower Kutai yang sekarang dioperasikan oleh Chevron Indonesia Company telah berproduksi sejak tahun 1975. Produksi dari lapangan ini mencapai puncak produksi sebesar 31 MBO pada tahun 1991, kontribusi terbesar dari produksi tersebut berasal dari zona low resistivity. Berdasarkan data log, zona yang menghasilkan hidrokarbon biasanya terdapat pada zona yang menunjukkan nilai resistivitas yang tinggi, tetapi pada lapangan Delta yang menjadi area penelitian ini sebagian besar produksi didominasi dari zona yang mempunyai nilai resistivitas yang rendah. Berdasarkan hasil analisa menunjukkan bahwa nilai tersebut dipengaruhi oleh beberapa faktor, diantaranya keberadaan mineral pyrite (Fes2), dominasi persentase volume clay dan ketebalan pay zone, dan nilai salinitas yang lebih tinggi dibandingkan dengan zona hidrokarbon yang mempunyai nilai resistivitas yang lebih tinggi pada lapangan ini.

Persentase nilai pyrite yang terdapat pada zona low resisivity ini hanya sebesar 1.2% - 3% dari volume batuan, tetapi nilai tersebut sudah bisa menurunkan nilai resistivitas sebesar 65% lebih rendah dibandingkan dengan zona hidrokarbon yang mempunyai nilai resistivitas yang tinggi pada formasi Deltaic dan Formasi Yakin. Persentase volume clay dan ketebalan juga mempengaruhi, dominasi mineral illite pada shale dan ketebalan kurang dari 5ft akan mempengaruhi penurunan nilai resistivity sebesar 10% dibandingkan high resistivity pay zone pada formasi Deltaic dan formasi Yakin. Dari analisa laboratorium pada air formasi menunjukkan bahwa pada zona low resistivity mempunyai nilai salinitas lebih tinggi 2000ppm diandingkan formasi Deltaic dan Formasi Yakin.

Sepinggan Field in Lower Kutai Basin which is in Mahakam Block and operated by Chevron Pacific Indonesia has been produced since 1975. Hydrocarbon pay zone generally has high resistivity. Nevertheless, Sepinggan Field production is primarily from low resistivity zone which is the most contributors even for its peak production at 31 MBO in 1991. Analysis result shows that the low resistivity value of the zone is influenced by some factors. These factors are pyrite content (FeS2), clay volume percentage domination and pay zone thickness, and more saline than high resistivity pay zone salinity. Pyrite volume percentage in this low resistivity zone ranges from 1.2 to 3 %.
This value can reduce 65 % from the normal resistivity value of hydrocarbon zones from Deltaic and Yakin Formation in this field. Illite domination in clay mineral content and less than 5 ft thickness also can reduce 10 % from the normal resistivity value of Deltaic and Yakin. Formation pay zones Laboratory analysis of formation water shows that salinity of low resistivity zone has 2000 ppm higher than Deltaic and Yakin water formation salinities."

Depok: Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Indonesia, 2019

T54172

UI - Tesis Membership Universitas Indonesia Library

Ganjar Satria Putra

Metode migrasi dalam kawasan depth untuk menghilangkan efek pull up dan push down pada struktur karbonat = Pre stack depth migration method in to remove full up and push down effect in carbonat structure

Jakarta: Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Indonesia, 2014

T46012

UI - Tesis Membership Universitas Indonesia Library

Wiryasumantri

Pemodelan dan karakterisasi reservoar batupasir formasi namur di lapangan meranji cekungan Eromanga Australia = Reservoir modeling and characterization in namur sandstone of Eromanga basin Australia

"Pada lapangan Meranji terdapat tiga sumur yang ketiganya menembus formasi Namur, tetapi hanya sumur Meranji-1 yang mengalirkan hidrokarbon minyak dari formasi Namur. Kebutuhan mengenai informasi geologi regional menjadi dasar atau batasan berpikir penulis sekaligus acuan dalam memetakan persebaran fasies pada lapangan ini. Sebagai dasar dalam pembuatan model properti batuan, perkembangan fasies perlu diketahui secara rinci dengan menggunakan pendekatan data geologi regional, data seismik, data sumur, dan juga data pendukung lainnya. Pemodelan dan karakterisasi reservoar di lapangan Meranji pada formasi Namur meliputi distribusi fasies dan distribusi properti reservoar di formasi tersebut. Persebaran batupasir dan persebaran properti reservoar Namur secara lateral dipandu oleh atribut seismik dan impedansi akustik hasil inversi seismik. Hasil pemodelan menunjukkan bahwa unit batupasir yang paling tebal, morfologi chanel yang terpotong atau tidak menerus atau tidak berkembang ke sumur Cooba-1 dan Pelican-5, arah pengendapan chanel fasies batupasir dari timur laut menuju ke barat daya berkumpul ke sumur Meranji-1 dan persebaran lateral AI yang rendah membentuk suatu lensa yang menipis, kemungkinan tidak berkembang ke arah dua sumur lainnya, analisis ini mendukung hipotesa mengapa hanya pada sumur Meranji-1 mengalir hidrokarbon.

On Meranji field there are three wells penetrated Namur Formation, but only Meranji-1 well that drain oil hydrocarbons from the Namur Formation. The needs of the regional geological informations as author references or limitations to map the distribution of facies in this field. As a basis for modeling properties of rocks, facies development needs to be known in detail by using a regional geological data, seismic data, well data, as well as other supporting data. Modeling and reservoir characterization in Meranji field in Namur formations include the distribution of facies and reservoir properties distribution in Namur formation. Distribution of sandstones facies and reservoir properties laterally guided by seismic attributes and seismic acoustic impedance inversion results. Modeling results indicate that the unit sandstone thickest, morphology channels are truncated or not continuous or does not develop into a well Cooba-1 and Pelican-5, direction of deposition of sandstone facies channel from the northeast toward southwest converge into well Meranji-1 and distribution of lower AI laterally forming a lens thinning, may not evolve towards two other wells, this analysis supports the hypothesis why only on Meranji-1 well flowed hydrocarbons."

Depok: Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Indonesia, 2018

T52047

UI - Tesis Membership Universitas Indonesia Library

Siagian, Hendra Benny

Metoda elastic impedance dan simultaneous inversion untuk karakterisasi properti batuan reservoir suatu studi pada formasi X Gulf of Mexico = Elastic impedance and simultaneous inversion methods for reservoir rock properties characterization a study at X formation Gulf of Mexico

"Formasi X merupakan target utama di Lapangan Marlin, yang merupakan lapangan gas, berlokasi di Viosca Knoll, lepas pantai Louisiana, Gulf of Mexico. Reservoar yang utama adalah lapisan batupasir tebal, berumur Miosen Tengah, memiliki ciri amalgamated sheet, seperti endapan turbidit pada intraslope basin. Untuk karakterisasi properti batuan di lapangan ini, apabila hanya dengan mengaplikasikan analisis AVO dan impedansi akustik (P-impedansi) saja akan memberikan ketidakpastian yang besar pada hasilnya. Oleh karena itu, Elastic Impedance (EI) dan Simultaneous Inversion diaplikasikan pada interval formasi X ini.

Aplikasi metoda inversi EI digunakan untuk memprediksi zona batupasir yang mengandung gas, dengan menggunakan sumur UI-1 dan UI-3 sebagai referensi untuk memprediksi properti reservoir di sumur UI-2, dilanjutkan dengan menganalisis penyebarannya dengan menggunakan partial post stack 3D seismic data. Metoda simultaneous inversion juga telah diaplikasikan sebagai metoda alternatif untuk memprediksi pore gas (Lambda-Rho) dan distribusi porositas, dengan menggunakan partial pre stack 3D seismic data yang diinversi secara simultan; dan dengan menggunakan sumur UI-1 dan UI-3 sebagai referensi untuk memprediksi properti reservoar di sumur UI-2 pada Lapangan Marlin.

Kedua metoda tersebut memberikan hasil yang saling mendukung satu sama lainnya. EI dapat memprediksi wet zone pada sumur UI-2 seperti juga halnya simultaneous inversion. Kombinasi hasil kedua metoda tersebut akan mendapatkan perpotongan zona lapisan batupasir, maka zona dengan tingkat kepastian tertinggi atau yang paling mungkin memiliki reservoir batupasir gas dapat dipetakan. Porositas and prediksi pore gas diperkirakan sebesar 20 sampai 30 persen dan 5 sampai 15 GPa*g/cc di dalam lapangan tersebut. Dari hasil studi ini, dapat disimpulkan bahwa kedua metode ini dapat digunakan sebagai alternatif untuk memprediksi karakter reservoar formasi X di lapangan Marlin dan lapangan lainnya yang memiliki kondisi geologi yang mirip untuk mengurangi ketidakpastian dalam eksplorasi hidrokarbon.

X formation is the main target of Marlin field, a gas field, situated in Viosca Knoll area, offshore Louisiana, Gulf of Mexico. Main reservoir sands are thick, middle Miocene amalgamated sheet-like turbidite sands deposited in an intraslope basin. The use of AVO analysis and acoustic impedance (P-impedance) only to characterize rock properties in this field will lead us into large uncertainty. Therefore, to overcome that issue, elastic impedance (EI) inversion and simultaneous inversion are introduced and applied within X formation interval.
EI inversion is applied to predict gas sand area, using well UI-1 and UI-3 as the reference to predict reservoir properties in UI-2 well, then delineate the area using partial post stack 3D seismic data. Simultaneous inversion is also applied as an alternative method to predict the pore gas (Lambda-Rho) and porosity distribution, using partial pre stack 3D seismic data which are inverted simultaneously; then UI-1 and UI-3 well data which will be used as a reference well for predicting reservoir properties in UI-2 at Marlin field.
The results from both methods are supported each other. EI inversion result can predict wet zone in well UI-2 as well as simultaneous inversion result. By combining the two methods and drawing the intersection of the good gas sandstone reservoir from both methods, the maximum confident or the most likely of gas sandstone reservoir area can be delineated. Porosity and pore gas prediction suggested around 20 to 30 percent and 5 to 15 GPa*g/cc respectively, throughout the field. Hence, this combined method could be used as an alternative to predict X reservoir properties in Marlin field or could be applied to other fields with similar geological condition to reduce exploration uncertainty."

Depok: Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Indonesia, 2013

T31342

UI - Tesis Membership Universitas Indonesia Library

Muhammad Thurisina Choliq

Klasifikasi facies litoseismik berdasarkan inversi deterministik untuk memprediksi sebaran batupasir pada zona utama Lapangan Coki cekungan Kutai = Lithoseismic facies classification based on deterministic inversion to predict sand extension in main zone Coki Field Kutai basin

"Inversi seismik deterministik telah dilakukan dengan menggunakan data PSTM di Lapangan Coki, Cekungan Kutai. Konsentrasi dari studi ini adalah zona Utama dengan kedalaman kurang lebih 3 km yang merupakan zona dengan akumulasi gas terbanyak. Tujuan utama dari penelitian ini adalah untuk mengidentifikasi ekstensi dari batupasir di Zona Utama dengan menggunakan metode klasifikasi lithoseismic berdasarkan input dari hasil inversi seismik deterministik mengingat kontribusi seismik untuk pengembangan zona Utama sangat kecil sebelumnya dikarenakan resolusi yang terbatas. Studi kelayakan fisika batuan menunjukkan bahwa untuk Zona Utama, kandungan fluida gas dan air sudah tidak bisa dipisahkan lagi di crossplot P-Impedance vs Poisson’s Ratio. Sedangkan untuk pemisahan litologi batupasir dan batulempung secara umum masih bisa dipisahkan terutama untuk batupasir dengan kualitas bagus. Dengan menggunakan cube P-Impedance dan Poisson’s Ratio hasil seismik inversi sebagai input, klasifikasi lithoseismic dilakukan untuk memisahkan batupasir dan batulempung. Hasil akhir dari proses ini adalah sand probability cube. Sand probability cube ini selanjutnya diinterpretasi dan digunakan untuk memprediksi ekstensi dari sand di zona Utama. Hasil interpretasi menemukan beberapa target baru di daerah dimana tidak ada kontrol dari sumur dan amplitudo seismic tidak menunjukkan karakteristik khusus. Berdasarkan hasil interpretasi ini optimalisasi trayektori dan desain beberapa sumur dilakukan.

Deterministic seismic inversions were performed using PSTM (Pre-stack time migration) data in the Coki field, Kutai Basin. The study concentrated on the Peciko Main Zone (~3 km burial depth) which is the main gas producing interval of the field. The main objectives of this project were to identify and map sand and possibly to define new targets for future development wells. Until 2012, seismic data had little contribution to well planning for this interval since their resolutions are poor and the seismic images only show the thick packages of stacked reservoirs. A rock physics feasibility study on P-impedancevs. Poisson’s Ratio crossplot showed that water and gas sands overlap each other significantly, meanwhile sand are discriminated from shale in particular for good quality sand. Lithoseismic classification is done using inverted P-impedance and Poisson’s Ratio to discriminate sand from shale. The final result is sand probability cube. Sand probability cube is then interpreted and used to define possible extension of sand limit for Main Zone.The final interpretation discovered several new targets where there is no well control and the seismic amplitudes didn’t show any distinctive characteristics. Then well trajectories are optimized using defined sand extension in order to better target the reservoir."

Depok: Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Indonesia, 2014

T43394

UI - Tesis Membership Universitas Indonesia Library

Liyanto

Prediksi penyebaran lithofluid dengan menggunakan inversi simultan, studi kasus zona dangkal lapangan alia cekungan Kutai delta Mahakam Kalimantan Timur = Lithofluid prediction using simultenous inversion attribute study case shallow zone alia field Mahakam delta Kutai basin East Kalimantan

"Lapangan ALIA yang berada di Delta Mahakam, Cekungan Kutai, Kalimantan Timur terdiri lebih dari 550 akumulasi reservoar yang secara struktur saling menumpuk dan terkompartemenkan. Lapangan ini sudah menghasilkan minyak kurang lebih selama 40 tahun. Terdapat lebih dari 400 sumur yang sudah di bor pada lapangan ini. Selama ini eksplorasi mengandalkan data sumur dan baru pada tahun 2011 dilakukan survey seismik 3D. Berdasarkan hasil survey seismik 3D tersebut, tesis ini memanfaatkan data seismik untuk karaktrerisasi reservoar lebih detail dengan menggunakan metode AVO dan Inversi Simultan.

Metode AVO dan Inversi Simultan digunakan untuk mengetahui pola dan anomali hidrokarbon dari penampang seismik. Metode ini akan menghasilkan beberapa sifat fisika properti reservoar seperti Impedansi gelombang P, Impedansi Gelombang S, densitas Dn, dan Lamda-rho.

Hasil analisa pada lapangan ALIA menunjukan bahwa pada zona reservoar target yaitu Top R0-35 memiliki anomali pada Attribute AVO Intercept/A (-), Gradient/B (-), Product/A*B (+). Selain zona reservoar target, Zona reservoar lain juga memiliki pola anomali yang sama yaitu pada Top Horizon R0-1. Hasil analisa Inversi simultan juga menunjukan bahwa zona reservoar tersebut memiliki anomali hidrokarbon dengan nilai Impedansi P (Zp) antara 2000 - 4000 ms-1gcc-1, nilai Impedansi S (Zs) berkisar antara 900 - 2050 ms-1gcc-1, dan Densitas (Dn) berkisar antara 1.7-2.11 gcc. Lambda Rho juga memiliki anomali yang sama dengan nilai berkisar antara 8.8-14.6 Gpa*g/cc.

ALIA field is located in Kutai basin, Mahakam Delta East Kalimantan, comprises of over 550 unconnected accumulations/reservoirs in structurally stacked and compartementalized deltaic sands. It has produced oil and gas for 40 years and more than 400 wells have been drilled in the field. Exploration and Development of this field was rely on well data and 3D seismic survey just conducted on 2011. Based on 3D seismic result, this thesis utilize seismic data for reservoar characterization by using AVO analyses and Simultaneous Inversion to get more detail of results.
Simultaneous inversion and AVO analyses is novel method in reservoir characterization. The method will produce several physical properties of reservoir such as P-wave Impedance, S-wave Impedance, density, Vp/Vs ratio, Lamda-rho and mu-rho. These physical properties could be used to estimate the type and content of reservoir lithology. Simultaneous AVO inversion needs P-wave sonic log, S-wave sonic log and density as input.
Analyses result from ALIA field at reservoar target zone, at Top R0-35 having the anomaly AVO Intercep/ A (-), Gradient B (-) and Product A*B (+). Another reservoar zone also having the same anomaly at Top Horizon R0-1. Simultaneous Inversion result also showed hydrocarbon anomaly with Impedance P (Zp) value around 2000 - 4000 ms-1gcc-1, Impedance S (Zs) around 900 - 2050 ms-1gcc-1, and Density (Dn) around 1.7-2.11 gcc. Lambda Rho showed hydrocarbon anomaly with value around 8.8-14.6 Gpa*g/cc"

Depok: Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Indonesia, 2015

T44191

UI - Tesis Membership Universitas Indonesia Library

Anggara Putra

Pemodelan numerik reservoar dikonstrain oleh analisis avo studi kasus zona dangkal lapangan Brian, Kalimantan Timur = Numerical reservoir modeling constrained by avo analysis case studies of shallow zone Brian field East Kalimantan

"[Lapangan Brian terletak pada bagian selatan Delta Mahakam dengan struktur geologi antiklin dengan sesar. Setelah 40 tahun diproduksi, lapangan ini memerlukan strategi pengembangan lapangan yang baru untuk meningkatkan produksi. Zona dangkal merupakan kandidat kuat untuk target produksi selanjutnya. Untuk merencanakan strategi pengembangan lapangan selanjutnya, diperlukan pemahaman karakterisasi reservoir & cadangan estimasi yang baik, penelitian ini

mengusulkan metode yang mengintegrasikan geofisika, petrofisika dan

pemodelan reservoar. Langkah-langkah penelitian yang telah dilakukan antara lain; 1) rekonstruksi struktur geologi bawah permukaan sebagai referensi pemodelan struktur 3 dimensi, 2) rekonstruksi distribusi facies dan zona prospek hidrokarbon menggunakan atribut RMS dan Analisis AVO, (3) perhitungan volume hidrokarbon. Hasil dari analisis AVO dapat menunjukkan respon gas yang cukup jelas pada reservoar E10-3, selanjutnya peta penyebaran facies batupasir channel di

interpretasi dengan menggunakan atribut RMS seismik. Dengan pemodelan numerik reservoar pada reservoar E10-3 didapatkan cadangan gas yang ekonomis. Berdasarkan analisis AVO & pemodelan numerik reservoar, optimalisasi target sumur baru dapat dilakukan pada reservoar E10-3 di kedalaman -1000 mdpl agar dapat meningkatkan produksi hidrokarbon Lapangan Brian khususnya zona

dangkal.;Brian Field is located in the southern part of the Mahakam Delta with geological structure of anticline with fault. After 40 years of production, this field requires field development of new strategies to improve production. Shallow Zone is a strong candidate for the next production targets. To plan a strategy of further field development, reservoir characterization and understanding required reserve estimates are good, this study proposes a method that integrates geophysical, petrophysical and reservoir modeling. The steps of

research that has been conducted, among others; 1) reconstruction of the subsurface geological structure as the reference for the 3-dimensional modelling, 2) reconstruction of the facies distribution and hydrocarbon prospects Zone using RMS attributes and RMS AVO analysis, (3) calculation of hydrocarbon volumes. The results of the AVO analysis can show quite clearly that the gas response on the E10-3 reservoir, and then channel sandstone facies map distribution interpreted by using RMS seismic attributes. With reservoir numerical modeling in reservoir E10-3, resulting an economical gas reserves.

Based on AVO analysis and numerical reservoir modeling, optimization targets new well can be done on Reservoir E10-3 in depth -1000mTVDSS in order to increase the production of hydrocarbons, especially Shallow Zone Brian Fields, Brian Field is located in the southern part of the Mahakam Delta with geological

structure of anticline with fault. After 40 years of production, this field requires

field development of new strategies to improve production. Shallow Zone is a

strong candidate for the next production targets.

To plan a strategy of further field development, reservoir characterization and

understanding required reserve estimates are good, this study proposes a method

that integrates geophysical, petrophysical and reservoir modeling. The steps of

research that has been conducted, among others; 1) reconstruction of the

subsurface geological structure as the reference for the 3-dimensional modelling,

2) reconstruction of the facies distribution and hydrocarbon prospects Zone using

RMS attributes and RMS AVO analysis, (3) calculation of hydrocarbon volumes.

The results of the AVO analysis can show quite clearly that the gas response on

the E10-3 reservoir, and then channel sandstone facies map distribution

interpreted by using RMS seismic attributes. With reservoir numerical modeling

in reservoir E10-3, resulting an economical gas reserves.

Based on AVO analysis and numerical reservoir modeling, optimization targets

new well can be done on Reservoir E10-3 in depth -1000mTVDSS in order to

increase the production of hydrocarbons, especially Shallow Zone Brian Fields]"

Universitas Indonesia, 2015

T44238

UI - Tesis Membership Universitas Indonesia Library

Agung Kurniawan

Prediksi sebaran porositas menggunakan probabilitas neural network: studi kasus lapangan-x Cekungan Kutai = Prediction of porosity distribution using probability neural network: x-field cekungan kutei case study

"[ABSTRAK

Lapangan-X merupakan lapangan gas di Cekungan Kutai yang dikembangkan sejak tahun 1986. Reservoar lapangan-X merupakan endapan delta Miosen akhir yang berlapis, dimana dikarakterisasikan oleh formasi yang didominasi oleh lempung. Perselingan antara batupasir dan batuserpih menghasilkan heterogenitas porositas yang cukup tinggi. Salah satu metode yang efektif dalam mengatasi tingkat heterogenitas yang tinggi adalah dengan metode Artificial Neural Network (ANN). ANN menggunakan algoritma Probabilistic Neural Network (PNN) mampu mendiskriminasikan daerah yang memiliki sebaran porositas yang tinggi dan rendah dengan baik pada zona Fresh Water Sand (FWS) lapangan-X dibanding dengan metode Multiatribut linier yang cenderung merupakan nilai sebaran porositas rata-rata. Nilai korelasi hasil prediksi terhadap target menggunakan metode PNN mencapai 0.8610 dengan rata-rata kesalahan (average error) sebesar 0.0283, sementara nilai korelasi hasil metode Multiatribut linier hanya sebesar 0.7098 dengan rata-rata kesalahan (average error) sebesar 0.0398. Hasil PNN pada sayatan waktu +10 ms dari horizon FS33 berhasil mengkarakterisasikan sebaran porositas batupasir yang bersih dari lempung di bagian selatan daerah penelitian, dimana fasies pengendapan batupasir tersebut diinterpretasikan berasal dari dataran delta. Sementara sayatan waktu -10 ms dari horizon FS42, menunjukan sebaran porositas batugamping dengan fasies pengendapannya diinterpretasikan berasal dari lingkungan neritik (shelf). Dari penelitian ini, dapat disimpulkan bahwa metode PNN berhasil menggambarkan sebaran porositas batuan di zona Fresh Water Sand (FWS) lapangan-X dengan baik sehingga hasil prediksi penyebaran yang dilakukan mampu mendekati data- data sumuran.

ABSTRACT

X-field is a gas field in Kutai Basin and it has been developed since 1986. Reservoir of X-field is a multi layered upper Miocene deltaic deposits and characterized by a shaly formation. A highly intercalation between sand & shale unit in X-field has been contributed to the heterogeneity of porosity in the area. One of the effective methods to spatially quantify such heterogeneity of porosity is by using Artificial Neural Networks (ANN). ANN with Probability Neural Network (PNN) algorithm has been successfully retained more dynamic range, high and low frequency porosity content, compare to the Multiattributes linear which is tend to show a smoothed, or more averaged prediction. The correlation value from PNN methods can be up to 0.8610 with average error is 0.0283, while correlation value from Multiattribute linear only up to 0.7098 with average error is 0.0398. The time slice of PNN result at +10ms from horizon FS33 has been clearly figured out an accumulation of high porosity in the southern area of the interval target which is indicated as a clean sand lithology based on sensitivity analysis. And such accumulation has formed a distributaries channel trend which is interpreted as delta plain deposits. Meanwhile, the time slice of PNN result at - 10 ms from horizon FS42 has indicated a carbonate lithology which is interpreted as shelf deposits. From this study, it?s concluded that PNN algorithm as a nonlinear function has been successfully showed a better porosity distribution in the Fresh Water Sand (FWS) zone of X-field.;X-field is a gas field in Kutai Basin and it has been developed since 1986. Reservoir of X-field is a multi layered upper Miocene deltaic deposits and characterized by a shaly formation. A highly intercalation between sand & shale unit in X-field has been contributed to the heterogeneity of porosity in the area. One of the effective methods to spatially quantify such heterogeneity of porosity is by using Artificial Neural Networks (ANN). ANN with Probability Neural Network (PNN) algorithm has been successfully retained more dynamic range, high and low frequency porosity content, compare to the Multiattributes linear which is tend to show a smoothed, or more averaged prediction. The correlation value from PNN methods can be up to 0.8610 with average error is 0.0283, while correlation value from Multiattribute linear only up to 0.7098 with average error is 0.0398. The time slice of PNN result at +10ms from horizon FS33 has been clearly figured out an accumulation of high porosity in the southern area of the interval target which is indicated as a clean sand lithology based on sensitivity analysis. And such accumulation has formed a distributaries channel trend which is interpreted as delta plain deposits. Meanwhile, the time slice of PNN result at - 10 ms from horizon FS42 has indicated a carbonate lithology which is interpreted as shelf deposits. From this study, it?s concluded that PNN algorithm as a nonlinear function has been successfully showed a better porosity distribution in the Fresh Water Sand (FWS) zone of X-field.;X-field is a gas field in Kutai Basin and it has been developed since 1986. Reservoir of X-field is a multi layered upper Miocene deltaic deposits and characterized by a shaly formation. A highly intercalation between sand & shale unit in X-field has been contributed to the heterogeneity of porosity in the area. One of the effective methods to spatially quantify such heterogeneity of porosity is by using Artificial Neural Networks (ANN). ANN with Probability Neural Network (PNN) algorithm has been successfully retained more dynamic range, high and low frequency porosity content, compare to the Multiattributes linear which is tend to show a smoothed, or more averaged prediction. The correlation value from PNN methods can be up to 0.8610 with average error is 0.0283, while correlation value from Multiattribute linear only up to 0.7098 with average error is 0.0398. The time slice of PNN result at +10ms from horizon FS33 has been clearly figured out an accumulation of high porosity in the southern area of the interval target which is indicated as a clean sand lithology based on sensitivity analysis. And such accumulation has formed a distributaries channel trend which is interpreted as delta plain deposits. Meanwhile, the time slice of PNN result at - 10 ms from horizon FS42 has indicated a carbonate lithology which is interpreted as shelf deposits. From this study, it’s concluded that PNN algorithm as a nonlinear function has been successfully showed a better porosity distribution in the Fresh Water Sand (FWS) zone of X-field., X-field is a gas field in Kutai Basin and it has been developed since 1986. Reservoir of X-field is a multi layered upper Miocene deltaic deposits and characterized by a shaly formation. A highly intercalation between sand & shale unit in X-field has been contributed to the heterogeneity of porosity in the area. One of the effective methods to spatially quantify such heterogeneity of porosity is by using Artificial Neural Networks (ANN). ANN with Probability Neural Network (PNN) algorithm has been successfully retained more dynamic range, high and low frequency porosity content, compare to the Multiattributes linear which is tend to show a smoothed, or more averaged prediction. The correlation value from PNN methods can be up to 0.8610 with average error is 0.0283, while correlation value from Multiattribute linear only up to 0.7098 with average error is 0.0398. The time slice of PNN result at +10ms from horizon FS33 has been clearly figured out an accumulation of high porosity in the southern area of the interval target which is indicated as a clean sand lithology based on sensitivity analysis. And such accumulation has formed a distributaries channel trend which is interpreted as delta plain deposits. Meanwhile, the time slice of PNN result at - 10 ms from horizon FS42 has indicated a carbonate lithology which is interpreted as shelf deposits. From this study, it’s concluded that PNN algorithm as a nonlinear function has been successfully showed a better porosity distribution in the Fresh Water Sand (FWS) zone of X-field.]"

Jakarta: Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Indonesia, 2014

T44753

UI - Tesis Membership Universitas Indonesia Library

Martin Krisnomurti

Diskriminasi gas/wet-sand dengan menggunakan kombinasi impedansi poisson (impedansi litologi dan impedansi ) study kasus Lapangan Zhezet = Gas/Wet-Sand discrimination by using combination of Poisson-Impedance (lithology impedance and fluid impedance) case study of Zhezet Field

"[ABSTRAK

Identifikasi keberadaan hidrokarbon di bawah permukaan bumi merupakan

salah satu tujuan utama dalam eksplorasi lapangan minyak bumi dalam usaha

mengidentifikasi keberadaan hidrokarbon. Impedansi-poisson yang merupakan

salah satu metoda yang digunakan untuk mendiskriminasi sifat fisis batuan

terhadap fluida dengan cara mengamati sensitivitas dari rasio poisson telah

diterapkan lebih lanjut untuk menghasilkan suatu metoda turunan yang lebih baik.

Pendekatan sifat fisika batuan antara impedansi-poisson dengan log sumuran yang

merepresentasikan properti batuan menghasilkan suatu metoda turunan yang

dinamakan impedansi-litologi. Sedangkan pendekatan sifat fisis fluida yang

terkandung didalam batuan terhadap impedansi-poisson menghasilkan diskriminasi

kandungan fluida didalam batuan yang kemudian dinamakan impedansi-fluida.

Metoda TCCA – Target Coeffisien Corellation Analysis – yang digunakan

untuk mencari koefisien korelasi tertinggi dari sifat fisis batuan terhadap

impedansi-poisson telah digunakan dalam penelitian ini untuk menghasilkan log

sumuran impedansi-litologi dan impedansi-fluida yang kemudian di propagasi

dengan neural network. Hasil propagasi impedansi-litologi digunakan sebagai

input untuk kalkulasi atribut koherensi yang diperkuat dengan hasil propagasi

impedansi-fluida untuk menghasilkan prediksi sebaran batuan reservoar.

Dari hasil penelitian pada horison FS33 terlihat pola channel yang

terbentuk dan tervalidasi dengan data sumur. Demikian juga pada sayatan horison

FS37, pola channel batuan reservoar terlihat dengan jelas dan tervalidasi terhadap

dua sumur yang dilalui. Sedangkan pada sayatan horison FS42 selain

teridentifikasi pola channel reservoar yang terbentuk, teridentifikasi juga batuan

karbonat yang divalidasi dengan data sumur dan data batuan inti

ABSTRACT

Hydrocarbon identification in subsurface is one of main goals in petroleum

exploration so that the litho-fluid content discriminations are a part of hydrocarbon

identifications which have been widely applied today. Poisson-impedance which is

one of the new methods that are used to discriminate rocks by examining the

sensitivity of physical rock properties of poisson-ratio has been further developed

to produce derivatives method. Physical properties approaches between poissonratio

and a well-log which represents rock properties can be used to get highest

correlation to produce a new derivative well-log named lithology-impedance. As a

fluid-rock properties approach between poisson-ratio and a well-log represents

litho-fluid content properties produces a new derivative well-log named fluidimpedance.

TCCA method –Target Coeffisien Corellation Analyst– is used to find the

highest correlation coefficient of the physical properties of rock fluid on the

poisson ratio has been used in this study to generate two new derivatives well-log

which would be propagated by means of neural-networks. The result of lithologyimpedance

propagation is further proceed with seismic coherence attribute as a

reflection of geology and stratigraphy forms which are then combined with fluidimpedance

propagation result to emphasize reservoir prediction distribution

laterally.

The study results of FS33 slicing discovers sand channels pattern and

validated by well-log. Similarly with horizon slicing of FS37, patterns of sand

channels reservoir are clearly visible and validated against two well-logs that

passed. While on horizon slicing of FS42 besides discovering sand channels,

carbonate rocks is also identified which is validated by well-log and core sample

analyst.;Hydrocarbon identification in subsurface is one of main goals in petroleum