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ITS » Paper and Presentation » S2 - Teknik Fisika
Posted by tondoindra@gmail.com at 07/03/2016 15:50:37  •  692 Views


PERANCANGAN ESTIMATOR KANDUNGAN CRUDE OIL GAS OIL WATER PADA WELLHEAD PLATFORM BERBASIS JARINGAN SYARAF TIRUAN JST

ESTIMATOR DESIGN CRUDE OIL CONTENT GAS OIL WATER AT WELLHEAD PLATFORM BASED ON ARTIFICIAL NEURAL NETWOR

Author :
BUDI, AGUS SULISTYO ( 2412201703 )




ABSTRAK

Pengukuran crude oil gas oil water saat ini menggunakan vessel separator dan indikator di lokal yang mana digunakan untuk mengetahui flow rate dari masingmasing fase nya. Kelemahan dari sistem ini adalah biaya instalasi dan pemeliharaan yang tinggi serta operator lambat dalam mengetahui kandungan crude oil dari sumur karena harus mendatangi platform untuk bisa mengetahui kandungan crude oil tersebut. Dalam penelitian ini digunakan perancangan model Jaringan Syaraf Tiruan JST untuk mengestimasi kandungan crude oil. Variabel masukan yang digunakan pada JST ini adalah flowrate total Q total tekanan masukan 1 P1 separator tekanan masukan 2 P2 separator dan temperatur T sedangkan variabel pada keluaran adalah flowrate gas Qg flowrate oil Qo dan flowrate water Qw. Metode perancangan ini menggunakan struktur Multi Layer Perceptron MLP dengan alogaritma pembelajaran Lavenberg Marquardt serta menggunakan 3 layer yaitu untuk layer pertama adalah layer masukan terdiri dari 4 node layer kedua adalah layer tersembunyi terdiri dari 4 layer tersembunyi dan ketiga yaitu layer keluaran terdiri dari 3 node. Hasil simulasi dari perancangan pemodelan JST ini menghasilkan nilai MSE Mean Square Error sebesar 3.29E-10 dan nilai VAF Variance Accounted For yaitu 98.8.


ABSTRACT

Measurement of crude oil gas oil water is currently using the separator vessel and local indicators which are used to determine the flow rate of each of its phases. The downside of this system is the cost of installation and high maintenance as well as slow the operators know the content of crude oil because they have to come to the platform without the occupant to be able to know the content of the crude oil. In this study the design model of Artificial Neural Network ANN to estimate the content crude oil. Input variables used in this ANN is the flowrate total Q total input pressure 1 P1 separator input pressure 2 P2 separator and temperature T while the output variables are flowrate gas Qg flowrate oil Qo and flowrate water QW. This design method using Multi Layer Perceptron structure MLP with Lavenberg Marquardt learning algorithm and using 3 layers namely for the first layer is the input layer consists of 4 nodes the second layer is a hidden layer consisting of four hidden layer and the third layer is the output consists of 3 nodes. The simulation result of the design of the ANN modeling is to produce a value of MSE Mean Square Error is 3.29E-10 and the value of VAF Variance Accounted For is 98.8 .



Keywordsseparator, Jaringan Syaraf Tiruan (JST), multi layer perceptron, Lavenberg Marquadt
 
Subject:  Jaringan Komputer
Contributor
  1. Dr. Ir. Aulia Siti Aisjah, M.T.
  2. Totok Ruki Biyanto, S.T. ,M.T.,Ph.D
Date Create: 07/03/2016
Type: Text
Format: PDF
Language: Indonesian
Identifier: ITS-paper-24121150008628
Collection ID: 24121150008628
Call Number: RTF 006.32 Bud p


Source
Paper And Presentation Of Physics Engineering RTF 006.32 Bud p, 2016

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