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Optimization of Vertical Well Placement for Oil Field Development Based on Basic Reservoir Rock Properties using a Genetic Algorithm Ariadji, Tutuka; Sukarno, Pudjo; Sidarto, Kuntjoro Adji; Soewono, Edy; Riza, Lala Septem; David, Kenny
Journal of Engineering and Technological Sciences Vol 44, No 2 (2012)
Publisher : ITB Journal Publisher, LPPM ITB

Comparing the quality of basic reservoir rock properties is a common practiceÂ toÂ locateÂ newÂ infillÂ orÂ developmentÂ wellsÂ forÂ optimizingÂ oilÂ field development using reservoir simulation. The conventional technique employs a manualÂ trial-and-errorÂ processÂ toÂ findÂ newÂ wellÂ locations,Â whichÂ provesÂ toÂ be time-consuming, especially for large fields. Concerning this practical matter, an alternative in the form of a robust technique is introduced in order to reduce time andÂ effortÂ inÂ findingÂ newÂ wellÂ locationsÂ capableÂ ofÂ producingÂ theÂ highestÂ oil recovery. The objective of this research was to apply a genetic algorithm (GA) for determining well locations using reservoir simulation, in order to avoid the conventionalÂ manualÂ trial-and-errorÂ method.Â ThisÂ GAÂ involvedÂ theÂ basicÂ rock properties,Â i.e.Â porosity,Â permeability,Â andÂ oil Â saturation,Â ofÂ eachÂ gridÂ block obtained from a reservoir simulation model, to which a newly generated fitness function was applied, formulated by translating common engineeringÂ practice in reservoirÂ simulationÂ intoÂ aÂ mathematicalÂ equationÂ andÂ thenÂ intoÂ aÂ computer program. The maximum fitness value indicates the best grid location for a new well. In order to validate the proposed GA method and evaluate the performance of the program, two fields with different production profile characteristics were used, fields X and Y. The proposed method proved to be a robust and accurate method to find the best new well locations for oil field development. The key to the success of the proposedÂ GA method lies in the formulation of the objective functions.

Leak Detection Modeling and Simulation for Oil Pipeline with Artificial Intelligence Method Sukarno, Pudjo; Sidarto, Kuntjoro Adji; Trisnobudi, Amoranto; Setyoadi, Delint Ira; Rohani, Nancy; Darmadi, Darmadi
Journal of Engineering and Technological Sciences Vol 39, No 1 (2007)
Publisher : ITB Journal Publisher, LPPM ITB

Leak detection is always interesting research topic, where leak location and leak rate are two pipeline leaking parameters that should be determined accurately to overcome pipe leaking problems. In this research those two parameters are investigated by developing transmission pipeline model and the leak detection model which is developed using Artificial Neural Network. The mathematical approach needs actual leak data to train the leak detection model, however such data could not be obtained from oil fields. Therefore, for training purposes hypothetical data are developed using the transmission pipeline model, by applying various physical configuration of pipeline and applying oil properties correlations to estimate the value of oil density and viscosity. The various leak locations and leak rates are also represented in this model. The prediction of those two leak parameters will be completed until the total error is less than certain value of tolerance, or until iterations level is reached. To recognize the pattern, forward procedure is conducted. The application of this approach produces conclusion that for certain pipeline network configuration, the higher number of iterations will produce accurate result. The number of iterations depend on the leakage rate, the smaller leakage rate, the higher number of iterations are required. The accuracy of this approach is clearly determined by the quality of training data. Therefore, in the preparation of training data the results of pressure drop calculations should be validated by the real measurement of pressure drop along the pipeline. For the accuracy purposes, there are possibility to change the pressure drop and fluid properties correlations, to get the better results. The results of this research are expected to give real contribution for giving an early detection of oil-spill in oil fields.

Determination of Gas Pressure Distribution in a Pipeline Network using the Broyden Method Sidarto, Kuntjoro Adji; Kania, Adhe; Mucharam, Leksono; Darmadi, Darmadi; Widhymarmanto, R. Arman
Journal of Engineering and Technological Sciences Vol 49, No 6 (2017)
Publisher : ITB Journal Publisher, LPPM ITB

A potential problem in natural gas pipeline networks is bottlenecks occurring in the flow system due to unexpected high pressure at the pipeline network junctions resulting in inaccurate quantity and quality (pressure) at the end user outlets. The gas operator should be able to measure the pressure distribution in its network so the consumers can expect adequate gas quality and quantity obtained at their outlets. In this paper, a new approach to determine the gas pressure distribution in a pipeline network is proposed. A practical and user-friendly software application was developed. The network was modeled as a collection of node pressures and edge flows. The steady state gas flow equations Panhandle A, Panhandle B and Weymouth to represent flow in pipes of different sizes and a valve and regulator equation were considered. The obtained system consists of a set of nonlinear equations of node pressures and edge flowrates. Application in a network in the field involving a large number of outlets will result in a large system of nonlinear equations to be solved. In this study, the Broyden method was used for solving the system of equations. It showed satisfactory performance when implemented with field data.

Model of Deposit and Loan of A Bank Using Spiral Optimization Algorithm Ansori, Moch Fandi; Sidarto, Kuntjoro Adji; Sumarti, Novriana
Journal of the Indonesian Mathematical Society Volume 25 Number 3 (November 2019)
Publisher : IndoMS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22342/jims.25.3.826.292-301

Nowadays, the study of financial stability of banking is important, which is to observe the behavior of the bank in the future. In this paper, a simple model of deposit and loan of a bank is solved analytically and numerically, and then it is implemented into data of four groups of commercial banks in Indonesia based on their capitals. From the data for each group of banks, the parameters will be estimated using the Spiral Optimization Algorithm. The results show that the algorithm gives satisfactory solutions in terms of closeness between the analytical and numerical solutions. In the long run, the deposit and loan volumes will be stable at their equilibrium points which showing the good condition of the future of the banks based on current state.

Optimasi Fungsi Multimodal Menggunakan Flower Pollination Algorithm Dengan Teknik Clustering Rahmat Karim; Kuntjoro Adji Sidarto; Suharsono Bantun
Techno.Com Vol 19, No 2 (2020): Mei 2020
Publisher : LPPM Universitas Dian Nuswantoro

Optimasi fungsi multimodal merupakan permasalahan yang banyak dijumpai dalam bidang teknik, sains, ilmu sosial dan ekonomi. Tujuan utama dari permasalahan multimodal adalah untuk melokalisir semua solusi yang tersedia baik optimum lokal maupun optimum global dalam sekali running. Flower Pollination Algorithm yang umum digunakan untuk optimasi global perlu dimodifikasi dan dikembangkan agar dapat menyelesaiakan tantangan dalam optimasi fungsi multimodal. Pada penelitian ini kami mengkombinasikan Flower Pollination Algorithm dengan teknik Clustering untuk mengoptimasi fungsi multimodal. Dalam uji coba terhadap 5 fungsi bencharmk multimodal yaitu Second minima, Six hump camel back, Rastrigin, Vincent dan Shubert diperoleh hasil bahwa metode yang disusulkan (FPAC) sukses menemukan semua solusi dari masing-masing fungsi multimodal dalam sekali running baik untuk kasus dimensi rendah maupun dimensi tinggi.

Leak Detection Modeling and Simulation for Oil Pipeline with Artificial Intelligence Method Pudjo Sukarno; Kuntjoro Adji Sidarto; Amoranto Trisnobudi; Delint Ira Setyoadi; Nancy Rohani; Darmadi Darmadi
Journal of Engineering and Technological Sciences Vol. 39 No. 1 (2007)
Publisher : Institute for Research and Community Services, Institut Teknologi Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5614/itbj.eng.sci.2007.39.1.1

Leak detection is always interesting research topic, where leak location and leak rate are two pipeline leaking parameters that should be determined accurately to overcome pipe leaking problems. In this research those two parameters are investigated by developing transmission pipeline model and the leak detection model which is developed using Artificial Neural Network. The mathematical approach needs actual leak data to train the leak detection model, however such data could not be obtained from oil fields. Therefore, for training purposes hypothetical data are developed using the transmission pipeline model, by applying various physical configuration of pipeline and applying oil properties correlations to estimate the value of oil density and viscosity. The various leak locations and leak rates are also represented in this model. The prediction of those two leak parameters will be completed until the total error is less than certain value of tolerance, or until iterations level is reached. To recognize the pattern, forward procedure is conducted. The application of this approach produces conclusion that for certain pipeline network configuration, the higher number of iterations will produce accurate result. The number of iterations depend on the leakage rate, the smaller leakage rate, the higher number of iterations are required. The accuracy of this approach is clearly determined by the quality of training data. Therefore, in the preparation of training data the results of pressure drop calculations should be validated by the real measurement of pressure drop along the pipeline. For the accuracy purposes, there are possibility to change the pressure drop and fluid properties correlations, to get the better results. The results of this research are expected to give real contribution for giving an early detection of oil-spill in oil fields.

Optimization of Vertical Well Placement for Oil Field Development Based on Basic Reservoir Rock Properties using a Genetic Algorithm Tutuka Ariadji; Pudjo Sukarno; Kuntjoro Adji Sidarto; Edy Soewono; Lala Septem Riza; Kenny David
Journal of Engineering and Technological Sciences Vol. 44 No. 2 (2012)
Publisher : Institute for Research and Community Services, Institut Teknologi Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5614/itbj.eng.sci.2012.44.2.2

Comparing the quality of basic reservoir rock properties is a common practice to locate new infill or development wells for optimizing oil field development using reservoir simulation. The conventional technique employs a manual trial-and-error process to find new well locations, which proves to be time-consuming, especially for large fields. Concerning this practical matter, an alternative in the form of a robust technique is introduced in order to reduce time and effort in finding new well locations capable of producing the highest oil recovery. The objective of this research was to apply a genetic algorithm (GA) for determining well locations using reservoir simulation, in order to avoid the conventional manual trial-and-error method. This GA involved the basic rock properties, i.e. porosity, permeability, and oil saturation, of each grid block obtained from a reservoir simulation model, to which a newly generated fitness function was applied, formulated by translating common engineering practice in reservoir simulation into a mathematical equation and then into a computer program. The maximum fitness value indicates the best grid location for a new well. In order to validate the proposed GA method and evaluate the performance of the program, two fields with different production profile characteristics were used, fields X and Y. The proposed method proved to be a robust and accurate method to find the best new well locations for oil field development. The key to the success of the proposed GA method lies in the formulation of the objective functions.

Determination of Gas Pressure Distribution in a Pipeline Network using the Broyden Method Kuntjoro Adji Sidarto; Adhe Kania; Leksono Mucharam; Darmadi Darmadi; R. Arman Widhymarmanto
Journal of Engineering and Technological Sciences Vol. 49 No. 6 (2017)
Publisher : Institute for Research and Community Services, Institut Teknologi Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5614/j.eng.technol.sci.2017.49.6.4

A potential problem in natural gas pipeline networks is bottlenecks occurring in the flow system due to unexpected high pressure at the pipeline network junctions resulting in inaccurate quantity and quality (pressure) at the end user outlets. The gas operator should be able to measure the pressure distribution in its network so the consumers can expect adequate gas quality and quantity obtained at their outlets. In this paper, a new approach to determine the gas pressure distribution in a pipeline network is proposed. A practical and user-friendly software application was developed. The network was modeled as a collection of node pressures and edge flows. The steady state gas flow equations Panhandle A, Panhandle B and Weymouth to represent flow in pipes of different sizes and a valve and regulator equation were considered. The obtained system consists of a set of nonlinear equations of node pressures and edge flowrates. Application in a network in the field involving a large number of outlets will result in a large system of nonlinear equations to be solved. In this study, the Broyden method was used for solving the system of equations. It showed satisfactory performance when implemented with field data.

A Singular Perturbation Problem for Steady State Conversion of Methane Oxidation in a Reverse Flow Reactor Aang Nuryaman; Agus Yodi Gunawan; Kuntjoro Adji Sidarto; Yogi Wibisono Budhi
Journal of Mathematical and Fundamental Sciences Vol. 44 No. 3 (2012)
Publisher : Institute for Research and Community Services (LPPM) ITB

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5614/itbj.sci.2012.44.3.7

The governing equations describing methane oxidation in a reverse flow reactor are given by a set of convective-diffusion equations with a nonlinear reaction term, where temperature and methane conversion are dependent variables. In this study, the process is assumed to be a one-dimensional pseudohomogeneous model and takes place with a certain reaction rate in which thewhole process ofthereactor is still workable. Thus, the reaction rate can proceed at a fixed temperature. Under these conditions, we can restrict ourselves to solving the equations for the conversion only. From the available data, it turns out that the ratio of the diffusion term to the reaction term is small. Hence, this ratio is considered as a small parameter in our model and this leads to a singular perturbation problem. Numerical difficulties will be found in the vicinity of a small parameter in front of a higher order term. Here, we present an analytical solutionby means of matched asymptotic expansions. The result shows that, up to and including the first order of approximation, the solution is in agreement with the exact and numerical solutions of the boundary value problem.

Some Problems on the Making of Mathematical Modelling of a Profit-Loss Sharing Scheme Using Data Simulation Novriana Sumarti; Kuntjoro Adji Sidarto; Muhammad Syamsuddin; Vina Fitriyani Mardiyyah; Abu Rizal
Journal of Mathematical and Fundamental Sciences Vol. 47 No. 1 (2015)
Publisher : Institute for Research and Community Services (LPPM) ITB

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5614/j.math.fund.sci.2015.47.1.1

The mathematical model for a profit-loss sharing scheme is formulated in order to see how this scheme can replace the traditional practice of lending money against high interest by usurers. It is sourced from the musyarakah method in Islamic Syariah law and implemented for small-scale investments of traditional-market traders. They are the common target of usurers, so they may end up poorer than they were before. The main goal of the model is to find the appropriate portion of profit share, so the investment is profitable not only for the investor but also for the trader. There are three main problems in the process of formulating the mathematical model and finding optimized results. The first problem is providing the appropriate amount of data to be implemented in the model. The second problem is determining the objective function for the optimization of the portion of profit share. The last problem is determining the appropriate values of the parameters for certain types of traders. We found a significant result in determining the appropriate values of the parameters that explain the potential capability of the traders in handling larger amounts of capital to be invested in order to achieve our main goal.

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