Hasil Pencarian  ::  Simpan CSV :: Kembali

Abstrak :
[ABSTRAK
Lapangan AAA merupakan salah satu lapangan gas terbesar di Indonesia yang terletak di delta mahakam, Kalimantan Timur. Karakteristik reservoir bagian dangkal lapangan ini berupa batuan pasir dengan lingkungan pengendapan deltaic distributary channel. Cadangan gas merupakan faktor jaminan pasokan gas selama kontrak, akan terus dimonitor baik pada kondisi ekplorasi (metoda perhitungan cadangan secara analog, volumetrik) hingga saat produksi (material balance) dengan tujuan untuk memperkirakan cadangan yang lebih pasti selaras dengan cara memproduksinya dan tindakan apa yang perlu dilakukan dalam memperpanjang usia produksi lapangan gas. Model statik digunakan untuk perhitungan cadangan volumetrik serta data produksi kumulatif sebagai validator. Kumulatif produksi reservoir tersebut sudah melebihi ekspektasi IGIP awal pada saat proposal pengeboran dengan metode perhitungan gas in place menggunakan metode seismik. Oleh karena itu perlu dilakukan analisa dan evaluasi reservoir tersebut dari analisa statik model geologi maupun dinamik. Berdasarkan analisa statik dan dinamis pada reservoir tersebut masih terdapat potensi gas yang dapat di produksikan. Dinamik sintesis menggunakan pendekatan material balance dengan aquifer model. Pada reservoar ini dominan tenaga dorong aktif adalah strong wáter drive. Dari analisa dinamik material balance menyebutkan bahwa sisa potensi gas (remaining reserves) yang dapat diproduksikan sebesar 8% untuk reservor A166, dan 24% untuk reservoar A181. Prediksi produksi gas juga menggunakan model sumur dengan bantuan PROSPERTM yaitu analisa aliran gas didalam lubang sumur, prediksi PROSPERTM produksi awal akan berkisar 7MMscf pada A166 dan 4MMscf pada A181 dan akan secara gradual turun sepanjang penurunan tekanan. Dengan perolehan recovery factor (RF) berkisar 65-70%.

---

ABSTRACT
AAA field is one of the largest gas fields in Indonesia, which is located in the Mahakam delta, East Kalimantan. Reservoir characteristics of these shallow zone is sandstone with deltaic distributary channel depositional environment. Gas reserves are the main factors for gas supply during the contract , will continue to be monitored both exploration conditions (analogous calculation methods, volumetric) until the time of production (material balance) with the aim of estimating reserves is more definitely aligned in a way to produce it and what action needs to be extend the life of the production is done in the gas field. The static model used for the calculation of volumetric reserves and cumulative production data as a validator. The reservoir cumulative production has exceeded initial expectations of IGIP during drilling proposal with calculating gas in place using seismic methods. It is therefore necessary to analyze and evaluate the reservoir with geological model static analysis and dynamic analysis. Based on static and dynamic analysis on the reservoir there is still potential gas can be produced. Dynamic synthesis approach using material balance with aquifer model. In this reservoir drive mechanism dominant is strong water drive. Dynamic analysis of Material balance concluded that the gas reserves (remaining reserves) which can be produced by 8 % for A166 reservoir, and 24 % for A181 reservoir. Prediction of gas production also use the well model using PROSPERTM to analized gas flow analysis in the wellbore, PROSPERTM prediction initial production will range 7MMscf on the A166 and A181 with 4MMscf will gradually declind along the pressure drop. With the acquisition of the ultimate recovery factor (RF) ranges from 65-70 %., AAA field is one of the largest gas fields in Indonesia, which is located in the Mahakam delta , East Kalimantan . Reservoir characteristics of these shallow zone is sandstone with deltaic distributary channel depositional environment. Gas reserves are the main factors for gas supply during the contract , will continue to be monitored both exploration conditions (analogous calculation methods, volumetric) until the time of production (material balance) with the aim of estimating reserves is more definitely aligned in a way to produce it and what action needs to be extend the life of the production is done in the gas field . The static model used for the calculation of volumetric reserves and cumulative production data as a validator. The reservoir cumulative production has exceeded initial expectations of IGIP during drilling proposal with calculating gas in place using seismic methods. It is therefore necessary to analyze and evaluate the reservoir with geological model static analysis and dynamic analysis . Based on static and dynamic analysis on the reservoir there is still potential gas can be produced. Dynamic synthesis approach using material balance with aquifer model. In this reservoir drive mechanism dominant is strong water drive . Dynamic analysis of Material balance concluded that the gas reserves (remaining reserves) which can be produced by 8 % for A166 reservoir , and 24 % for A181 reservoir . Prediction of gas production also use the well model using PROSPERTM to analized gas flow analysis in the wellbore, PROSPERTM prediction initial production will range 7MMscf on the A166 and A181 with 4MMscf will gradually declind along the pressure drop. With the acquisition of the ultimate recovery factor (RF) ranges from 65-70 %.]

Abstrak :
Tantangan yang dihadapi mobile robot pada operasi search and rescue adalah otomatisasi. Dalam mewujudkan mobile robot yang benar-benar otomatis, terdapat 3 permasalahan yang perlu dipecahkan. Permasalahan tersebut adalah lokalisasi, pemetaan, dan perencanaan rute. Di antara ketiga permasalahan tersebut, permasalahan paling fundamental yang harus dipecahkan adalah lokalisasi. Salah satu algoritma yang dapat digunakan untuk melakukan lokalisasi adalah Extended Kalman Filter (EKF). Kelebihan algoritma ini antara lain dapat diterapkan pada sistem mikrokontroler 8 bit sekalipun. Pada beberapa penelitian, implementasi algoritma ini membutuhkan banyak sensor. Implementasi algoritma ini pada sistem dengan sumber daya sensor minimal membutuhkan strategi khusus. Penelitian ini akan menguji performa dua metode yang digunakan untuk implementasi lokalisasi berbasis Extended Kalman Filter, yaitu landmark detection dan line extraction. Implementasi dilakukan dengan menggunakan strategi khusus untuk menyesuaikan dengan keadaan robot yang memiliki sumber daya sensor minimal. Untuk landmark detection, strategi yang dilakukan adalah mempartisi dinding area uji, kemudian hasil partisi tersebut dianggap sebagai landmark. Untuk line extraction, proses ekstraksi baru dilakukan setelah robot bergerak maju tiga kali dan mendapat tiga titik. Hasil yang didapat menunjukkan bahwa strategi landmark detection memiliki performa yang lebih baik daripada strategi line extraction, dengan error posisi x dan y dibawah 3 cm dan error orientasi dibawah 5 derajat.

---

A challenge that must be overcome by a mobile robot used in a search-and-rescue operation is automation. To realize truly autonomous mobile robot, there are three problems that need to be solved. Those problems are localization, mapping, and path- planning. Among those three problems, the problem of localization is the most fundamental problem that need to be solved. One of the algorithm that can be used to localize a mobile robot is Extended Kalman Filter. The advantage of applying Extended Kalman Filter (EKF) for localization is that this algorithm can be implemented even on 8-bit microcontroller based system. On some research, implementation of the EKF needs many sensors. Implementation of this algorithm on a system with minimum sensor resource needs a special strategy. This research will test the performance of two methods used to implement EKF-based localization, namely landmark detection and line extraction. The method is implemented using a special strategy to cope with the minimal sensor resource provided. To implement landmark detection method, the wall of testing environment is partitioned and then each partition is treated as an individual landmark. To implement the line extraction method, the extraction process is done after the robot moves forward three times and detect three points. The result gotten shows that landmark detection strategy gives better performance than line extraction strategy with the error of x and y position below 3 cm and orientation error below 5 degrees.