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"ABSTRAKSetelah berproduksi selama 10 tahun kemampuan alir tujuh sumur gas di Lapangan B berkurang secara alamiah dengan turunnya laju alir dan tekanan. Penurunan setiap sumur tidak seragam dipengaruhi oleh jenis reservoir dan kondisi sub-surface, akibatnya produksi gas tidak maksimal. Permasalahan diatasi dengan menurunankan tekanan abandonment sumur untuk mengurangi back pressure dari surface facility. Metode ini diaplikasikan dengan cara merekayasa skema produksi sumur. Simulasi untuk memprediksikan laju alir, tekanan dan menghitung kumulatif produksi serta Recovery Factor selama tahun 2018-2028 pada tiga skenario yaitu : Skenario 1, base case, yaitu gas diproduksikan dengan initial deliverability sumur hingga mencapai tekanan abandonment pertama pada 600 psi ; Skenario 2, header case, yaitu memasang header baru dengan operating pressure yang lebih rendah dari existing header ; Skenario 3, low pressure case, yaitu melakukan penurunan tekanan abandonment sampai sebesar 250 psi setara dengan suction presure Gas Compressor. Hasil simulasi diperoleh total kumulatif produksi Gp dan Recovery Factor RF masing-masing adalah sebagai berikut ; Skenario 1 Gp = 415 BCF, RF = 65,5 ; Skenario 2 Gp = 493 BCF, RF = 77,9 ; Skenario 3 Gp = 495 BCF, RF = 78,2 . Skenario 3 mampu menghasilkan produksi gas dan financial income paling maksimal karena dapat meningkatkan kemampuan alir gas semua sumur di Lapangan B sehingga dapat disimpulkan bahwa Skenario 3 direkomendasikan untuk diimplementasikan.

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ABSTRACTAfter producing for 10 years the deliverability of seven gas wells in Field B is naturally declined with a decrease in flow rate and pressure. The decrease in each well is not uniformly influenced by the reservoir type and sub surface conditions that caused gas production is not maximal. The problem is solved by lowering the well abandonment pressure to reduce the back pressure effect of the surface facility. This method is applied by modifying the well operating scheme. Simulations were performed to predict gas flow rates, pressures, cumulative gas production and Recovery Factor during 2018 2028 on three scenarios which is Scenario 1 , base case, that gas is naturally produced according to the well initial deliverability until it reaches the first abandonment pressure at 600 psi 2 , header case, ie installing a new header with operating pressure lower than the existing header 3 , low pressure case, ie lowering abandonment pressure down to 250 psi. Simulation resulted as follows Scenario 1 Gp 415 BCF RF 65.5 Scenario 2 Gp 493 BCF RF 77.9 Scenario 3 Gp 495 BCF RF 78.2 . Since Scenario 3 is able to produce maximum gas production and financial income due to improving all gas well deliverability in Field B, it can be concluded that Scenario 3 is recommended to be implemented."

"ABSTRAKIndonesia memiliki cadangan gas non konvensional berupa shale gas yangcukup besar yaitu sebesar 574 Tcf (hypothetical resources), yang belumdiexplorasi hingga saat ini. Potensi shale gas ini perlu untuk segera dimanfaatkanuntuk memenuhi kebutuhan gas dalam negeri yang diperkirakan akan meningkatdengan pesat di masa akan datang. Data-data biaya CAPEX dan OPEX akandiambil dari contoh pengembangan shale gas di Marcellus basin sebagaibenchmark. Profil produksi gas diestimasi dengan menggunakan modelpersamaan exponensial menurun.Dari hasil analisa keekonomian diketahui bahwa pengembangan shale gas diSumatera Selatan akan potensial menguntungkan secara komersial apabila salesgas dijual pada harga awal 10 USD/MMBTU, FTP (first trance petroleum)sebesar 0% dan profil produksi sedang atau tinggi. Sedangkan bila sales gas dijualdengan harga awal 6 USD/MMBTU akan kurang menguntungkan bahkan padaprofil produksi tinggi sekalipun. Hasil analisa sensitivitas menunjukkan bahwaperubahan besaran harga gas dan produksi gas memberikan pengaruh positifterhadap IRR dan BEP, sedangkan perubahan besaran CAPEX memberikanpengaruh sebaliknya. Perubahan besaran harga gas memberikan pengaruh yanglebih besar baik terhadap IRR maupun BEP dibandingkan perubahan produksigas. Pemberian insentif berupa penetapan FTP sebesar 0% (dibandingkan dengankondisi normal FTP sebesar 20%) memberikan pengaruh yang relatif kecilterhadap IRR dan BEP. Apabila gas dijual pada harga awal 10 USD/MMBTU danFTP sebesar 0%, maka pada recovery factor sebesar 10% dari potensi kandunganshale gas di Sumatera Selatan, dapat diperoleh potensi pemasukan buatpemerintah Indonesia sebesar 352 trilyun rupiah.

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ABSTRACTIndonesia has hypothetical resources of unconventional shale gas about 574tcf that has not been explored yet. The potential of shale gas resources should beutilized to fulfill the fast growing demand of natural gas expected in the future.CAPEX and OPEX cost will be adopted from example of shale gas developmentof Marcellus shale as a benchmark. Gas production profile will be estimated byusing declining exponential model of equation.The economic analysis result shows that shale gas development in SouthSumatera will be feasible if initial price of sales gas is 10 USD/MMBTU, FTP is0% and gas production profile is medium or high type. On the other hand if initialsales gas price is at 6 USD/MMBTU then it will not be feasible even at highproduction profile. Sensitivity analysis result shows that sales gas price andproduction profile will give positive impact to IRR and BEP. In contrary, CAPEXwill give negative impact. Sales gas price will give higher impact than gasproduction. Government incentive like FTP at 0% (instead of 20% at normalcondition) will give insignificant impact to IRR and BEP. In case sales gas is at 10USD/MMBTU and FTP at 0%, with recovery factor of 10% from hypotheticalshale gas resources in South Sumatera, it is estimated that the potential income toIndonesian Government is about 352 trillion rupiah."

"Penelitian ini terletak di lapangan X, tepatnya di Jambi. Reservoar gas pada lapangan ini merupakan bagian dari sub cekungan Jambi, dimana litologinya berupa sandstone pada Formasi Air Benakat. Metoda Atribut Dekomposisi Spektral sangat baik untuk mengidentifikasi lapisan tipis berdasarkan parameter frekuensi. Pada penelitian ini menggunakan CWT (Continuous Wavelet Transform) dengan menggunakan wavelet Mexican Hat sebagai wavelet input. Frekuensi dominan dari reservoar gas ditunjukan pada 30 Hz. Metode lain yang digunakan adalah Spectral Ratio yang berfungsi untuk menghitung besar Q Factor. Berdasarkan hasil perhitungan, analisis nilai Q Factor menunjukan nilai yang kecil yaitu 140,75 , pada zona M, 184,89 pada zona N, dan 89,10 pada zona O relatif terhadap zona referensi. Nilai Q Factor yang kecil pada zona reservoar menunjukan koefisien atenuasi yang besar.

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This research is located in Field X, the South side of Sumatra. Gas Reservoirs in the field were formed at Air Benakat Formation. The spectral decomposition method is very good tool to identify the thin layers based on frequency parameters. In this research, the author using CWT (Continuous Wavelet Transform) with respect to Mexican Hat wavelet type as wavelet. From gas reservoir, it was found the frequency dominant around 30 Hz. Spectral Ratio method is used to estimate Q Factor value. Based on calculation, Q Factor values is 140,75 for M zone, 184,89 for N zone, and 89,10 for O zone, relative to reference zone. Q factor that is small in reservoir, represent a large attenuation."

"Reservoar gas batu pasir pada formasi Arang telah berhasil di karakterisasi dengan mengintegrasikan ketiga metode dari inversi simultan, analisis LMR dan analisis AVO. Karakterisasi difokuskan dalam dua hal yaitu identifikasi litologi dan kandungan fluidanya. Pada studi ini masing-masing metode akan menghasilkan parameter fisis yang sensitif terhadap karakter dari reservoar.Inversi simultan menghasilkan tiga parameter fisis berupa impedansi P (Zp), impednasi S (Zs), dan rasio Vp/Vs. Sementara transformasi LMR akan menghasilkan dua parameter fisis yaitu Mu-rho dan Lamda-rho. Identifikasi litologi dilakukan melalui analisis parameter fisis Mu-rho dan impedansi S sedangkan identifikasi kandungan fluida melalui analisis parameter Lamda-rho, impedansi P, dan rasio Vp/Vs. Analisis AVO dilakukan untuk mengetahui tipe kelas anomali dari gas yang mengisi reservoar melalui analisis gradien. Hasil studi menunjukan parameter Mu-rho dan lamda rho berhasil menggambarkan persebaran reservoar gas batu pasir secara 3D. Hasil impedansi S, impedansi P, dan Vp/Vs juga menujukan indikasi dari reservoar batu pasir di daerah yang sama. Terakhir berdasarkan analisis AVO tipe gas dalam reservoar adalah kelas IIp.

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Gas sand resrvoir at Arang formation has been characterized by integrating three method from simultaneous inversion, LMR analysis, and AVO analysis.Characterization is focused on two things, litologi identification and fluid content. Each method in this study will produce parameter which sensitive to reservoar character. Simultaneous inversion results three physical parameters P-impedance, S-impedance, and ratio Vp/Vs. Whereas LMR transformation results two parameters, Lamda-rho and Mu-rho. Litology identification is done with Mu-rho and S-impedance analysis while fluid content identification is done with Lamda-rho, P-impedance, and ratio Vp/Vs. AVO analysis has purpose to know anomaly type from gas in reservoar through gradient analysis. This study shows that Mu-rho and Lamda-rho analysis can deliniate Gas Sand Reservoar in 3D form. While S-impdance, P-impedance, and Vp/Vs also indicate gas sand reservoar in the same spot. Finally based on AVO analysis, gas type in reservoar is class IIp."

"[ABSTRAKIdentifikasi 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

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ABSTRACTHydrocarbon 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.]"

"Metode inversi EEI dapat mengkarakterisasi reservoar batuan, baik litologi maupun kandungan fluida pengisi pori. Metode EEI diharapkan dapat mengkarakterisasi reservoar di lokasi penelitian yang memiliki perselingan batuan pasir dan lempung dengan ketebalan kurang dari 60 ft. Parameter-parameter yang digunakan untuk melakukan inversi EEI pada penelitian ini adalah parameter yang memiliki koefisien korelasi yang tinggi antara log target dan log parameter pada sudut tertentu best chi angle . Parameter yang digunakan untuk melakukan inversi EEI pada penelitian ini adalah impedansi P AI , Vp/Vs, porositas total PHIT , dan volum lempung VCL.Hasil dari penelitian menunjukkan bahwa Formasi Lower Sihapas memiliki batuan pasir yang lebih dominan dibandingkan dengan Formasi Upper Sihapas. Pada batuan pasir di Formasi Lower Sihapas terdapat konten minyak yang ditandai dengan nilai volume lempung rendah, Vp/Vs rendah, dan saturasi air bernilai 25 - 60.

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EEI inversion method can characterize reservoir rock, either lithology and fluid content. EEI method hopefully can characterize reservoir in research area that have lithology of sand and shale which have less than 60 ft thickness. Parameters that are used in EEI inversion are parameters that have high value of correlation coefficient Parameters that are used in this research are P impedance, Vp Vs, total porosity PHIT , and volume of clay VCL.

The results show that lithology in Lower SIhapas Formation have more dominant sandstone than Upper Sihapas Formation. Sandstone in Lower Sihapas Formation have oil content which is identified by low value of VCL, low value of Vp Vs, and water saturation value range from 25 60."