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
Martin Krisnomurti;
Supriyanto, supervisor; Abdul Haris, examiner; Agus Guntoro, examiner; Tavip Setiawan, examiner
(Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Indonesia, 2014)
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[ABSTRAK Identifikasi keberadaan hidrokarbon di bawah permukaan bumi merupakansalah satu tujuan utama dalam eksplorasi lapangan minyak bumi dalam usahamengidentifikasi keberadaan hidrokarbon. Impedansi-poisson yang merupakansalah satu metoda yang digunakan untuk mendiskriminasi sifat fisis batuanterhadap fluida dengan cara mengamati sensitivitas dari rasio poisson telahditerapkan lebih lanjut untuk menghasilkan suatu metoda turunan yang lebih baik.Pendekatan sifat fisika batuan antara impedansi-poisson dengan log sumuran yangmerepresentasikan properti batuan menghasilkan suatu metoda turunan yangdinamakan impedansi-litologi. Sedangkan pendekatan sifat fisis fluida yangterkandung didalam batuan terhadap impedansi-poisson menghasilkan diskriminasikandungan fluida didalam batuan yang kemudian dinamakan impedansi-fluida.Metoda TCCA – Target Coeffisien Corellation Analysis – yang digunakanuntuk mencari koefisien korelasi tertinggi dari sifat fisis batuan terhadapimpedansi-poisson telah digunakan dalam penelitian ini untuk menghasilkan logsumuran impedansi-litologi dan impedansi-fluida yang kemudian di propagasidengan neural network. Hasil propagasi impedansi-litologi digunakan sebagaiinput untuk kalkulasi atribut koherensi yang diperkuat dengan hasil propagasiimpedansi-fluida untuk menghasilkan prediksi sebaran batuan reservoar.Dari hasil penelitian pada horison FS33 terlihat pola channel yangterbentuk dan tervalidasi dengan data sumur. Demikian juga pada sayatan horisonFS37, pola channel batuan reservoar terlihat dengan jelas dan tervalidasi terhadapdua sumur yang dilalui. Sedangkan pada sayatan horison FS42 selainteridentifikasi pola channel reservoar yang terbentuk, teridentifikasi juga batuankarbonat yang divalidasi dengan data sumur dan data batuan inti ABSTRACT Hydrocarbon identification in subsurface is one of main goals in petroleumexploration so that the litho-fluid content discriminations are a part of hydrocarbonidentifications which have been widely applied today. Poisson-impedance which isone of the new methods that are used to discriminate rocks by examining thesensitivity of physical rock properties of poisson-ratio has been further developedto produce derivatives method. Physical properties approaches between poissonratioand a well-log which represents rock properties can be used to get highestcorrelation to produce a new derivative well-log named lithology-impedance. As afluid-rock properties approach between poisson-ratio and a well-log representslitho-fluid content properties produces a new derivative well-log named fluidimpedance.TCCA method –Target Coeffisien Corellation Analyst– is used to find thehighest correlation coefficient of the physical properties of rock fluid on thepoisson ratio has been used in this study to generate two new derivatives well-logwhich would be propagated by means of neural-networks. The result of lithologyimpedancepropagation is further proceed with seismic coherence attribute as areflection of geology and stratigraphy forms which are then combined with fluidimpedancepropagation result to emphasize reservoir prediction distributionlaterally.The study results of FS33 slicing discovers sand channels pattern andvalidated by well-log. Similarly with horizon slicing of FS37, patterns of sandchannels reservoir are clearly visible and validated against two well-logs thatpassed. While on horizon slicing of FS42 besides discovering sand channels,carbonate rocks is also identified which is validated by well-log and core sampleanalyst.;Hydrocarbon identification in subsurface is one of main goals in petroleumexploration so that the litho-fluid content discriminations are a part of hydrocarbonidentifications which have been widely applied today. Poisson-impedance which isone of the new methods that are used to discriminate rocks by examining thesensitivity of physical rock properties of poisson-ratio has been further developedto produce derivatives method. Physical properties approaches between poissonratioand a well-log which represents rock properties can be used to get highestcorrelation to produce a new derivative well-log named lithology-impedance. As afluid-rock properties approach between poisson-ratio and a well-log representslitho-fluid content properties produces a new derivative well-log named fluidimpedance.TCCA method –Target Coeffisien Corellation Analyst– is used to find thehighest correlation coefficient of the physical properties of rock fluid on thepoisson ratio has been used in this study to generate two new derivatives well-logwhich would be propagated by means of neural-networks. The result of lithologyimpedancepropagation is further proceed with seismic coherence attribute as areflection of geology and stratigraphy forms which are then combined with fluidimpedancepropagation result to emphasize reservoir prediction distributionlaterally.The study results of FS33 slicing discovers sand channels pattern andvalidated by well-log. Similarly with horizon slicing of FS37, patterns of sandchannels reservoir are clearly visible and validated against two well-logs thatpassed. While on horizon slicing of FS42 besides discovering sand channels,carbonate rocks is also identified which is validated by well-log and core sampleanalyst.;Hydrocarbon identification in subsurface is one of main goals in petroleumexploration so that the litho-fluid content discriminations are a part of hydrocarbonidentifications which have been widely applied today. Poisson-impedance which isone of the new methods that are used to discriminate rocks by examining thesensitivity of physical rock properties of poisson-ratio has been further developedto produce derivatives method. Physical properties approaches between poissonratioand a well-log which represents rock properties can be used to get highestcorrelation to produce a new derivative well-log named lithology-impedance. As afluid-rock properties approach between poisson-ratio and a well-log representslitho-fluid content properties produces a new derivative well-log named fluidimpedance.TCCA method –Target Coeffisien Corellation Analyst– is used to find thehighest correlation coefficient of the physical properties of rock fluid on thepoisson ratio has been used in this study to generate two new derivatives well-logwhich would be propagated by means of neural-networks. The result of lithologyimpedancepropagation is further proceed with seismic coherence attribute as areflection of geology and stratigraphy forms which are then combined with fluidimpedancepropagation result to emphasize reservoir prediction distributionlaterally.The study results of FS33 slicing discovers sand channels pattern andvalidated by well-log. Similarly with horizon slicing of FS37, patterns of sandchannels reservoir are clearly visible and validated against two well-logs thatpassed. While on horizon slicing of FS42 besides discovering sand channels,carbonate rocks is also identified which is validated by well-log and core sampleanalyst., Hydrocarbon identification in subsurface is one of main goals in petroleumexploration so that the litho-fluid content discriminations are a part of hydrocarbonidentifications which have been widely applied today. Poisson-impedance which isone of the new methods that are used to discriminate rocks by examining thesensitivity of physical rock properties of poisson-ratio has been further developedto produce derivatives method. Physical properties approaches between poissonratioand a well-log which represents rock properties can be used to get highestcorrelation to produce a new derivative well-log named lithology-impedance. As afluid-rock properties approach between poisson-ratio and a well-log representslitho-fluid content properties produces a new derivative well-log named fluidimpedance.TCCA method –Target Coeffisien Corellation Analyst– is used to find thehighest correlation coefficient of the physical properties of rock fluid on thepoisson ratio has been used in this study to generate two new derivatives well-logwhich would be propagated by means of neural-networks. The result of lithologyimpedancepropagation is further proceed with seismic coherence attribute as areflection of geology and stratigraphy forms which are then combined with fluidimpedancepropagation result to emphasize reservoir prediction distributionlaterally.The study results of FS33 slicing discovers sand channels pattern andvalidated by well-log. Similarly with horizon slicing of FS37, patterns of sandchannels reservoir are clearly visible and validated against two well-logs thatpassed. While on horizon slicing of FS42 besides discovering sand channels,carbonate rocks is also identified which is validated by well-log and core sampleanalyst.] |
T44383-Martin Krisnomurti.pdf :: Unduh
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No. Panggil : | T44383 |
Entri utama-Nama orang : | |
Entri tambahan-Nama orang : | |
Entri tambahan-Nama badan : | |
Subjek : | |
Penerbitan : | Jakarta: Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Indonesia, 2014 |
Program Studi : |
Bahasa : | ind |
Sumber Pengatalogan : | LibUI ind rda |
Tipe Konten : | text |
Tipe Media : | unmediated ; computer |
Tipe Carrier : | volume ; online resources |
Deskripsi Fisik : | xiii, 77 pages : illustration ; 28 cm + appendix |
Naskah Ringkas : | |
Lembaga Pemilik : | Universitas Indonesia |
Lokasi : | Perpustakaan UI, Lantai 3 |
No. Panggil | No. Barkod | Ketersediaan |
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T44383 | 15-23-56965643 | TERSEDIA |
Ulasan: |
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