DEVELOPMENT OF ENSEMBLE KALMAN FILTER (ENKF) FOR SOME RESERVOIR DIFFUSIVITY MODELS

The decline of oil production depends on reservoir characteristics such as permeability and porosity. The Arps model involves the flow rate of oil production, but it <br /> <br /> does not consider these characteristics yet. The relation between the characteristics and the flow rate is d...

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Main Author: FITRIYATI (NIM: 30109001), NINA
Format: Dissertations
Language:Indonesia
Online Access:https://digilib.itb.ac.id/gdl/view/23497
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Institution: Institut Teknologi Bandung
Language: Indonesia
id id-itb.:23497
spelling id-itb.:234972017-12-15T16:14:26ZDEVELOPMENT OF ENSEMBLE KALMAN FILTER (ENKF) FOR SOME RESERVOIR DIFFUSIVITY MODELS FITRIYATI (NIM: 30109001), NINA Indonesia Dissertations INSTITUT TEKNOLOGI BANDUNG https://digilib.itb.ac.id/gdl/view/23497 The decline of oil production depends on reservoir characteristics such as permeability and porosity. The Arps model involves the flow rate of oil production, but it <br /> <br /> does not consider these characteristics yet. The relation between the characteristics and the flow rate is described by the diffusivity equation. Since solution of diffusivity <br /> <br /> equation in term of reservoir characteristics is nonlinear, the EnKF state-space is used to estimate the reservoir characteristics. This dissertation presents the development of EnKF for some reservoir diffusivity <br /> <br /> models i.e. line source, cylindrical source, interacting two production wells and interacting two production-injection wells. The diffusivity equation is solved by <br /> <br /> the Laplace transform and its inverse is found analytically or numerically using the Gaver-Stehfest Algorithm. In EnKF, the permeability or porosity estimation <br /> <br /> processes is calculated through the updating processes. The validation of EnKF is analyzed using convergence in probability which is visualized by using the statistical <br /> <br /> quality control methodology where the limit of the chart is calculated based on the Chebyshev inequality. <br /> <br /> The result shows that the EnKF can be used to estimate the reservoir parameters using diffusivity equation. The simulation study shows that the estimate converges to the true value. Application of the EnKF depend on the solution complexity of the diffusivity equation. The proposed method has not yet been applied for a real data due to the difficulties of fitting appropriate diffusivity equation. text
institution Institut Teknologi Bandung
building Institut Teknologi Bandung Library
continent Asia
country Indonesia
Indonesia
content_provider Institut Teknologi Bandung
collection Digital ITB
language Indonesia
description The decline of oil production depends on reservoir characteristics such as permeability and porosity. The Arps model involves the flow rate of oil production, but it <br /> <br /> does not consider these characteristics yet. The relation between the characteristics and the flow rate is described by the diffusivity equation. Since solution of diffusivity <br /> <br /> equation in term of reservoir characteristics is nonlinear, the EnKF state-space is used to estimate the reservoir characteristics. This dissertation presents the development of EnKF for some reservoir diffusivity <br /> <br /> models i.e. line source, cylindrical source, interacting two production wells and interacting two production-injection wells. The diffusivity equation is solved by <br /> <br /> the Laplace transform and its inverse is found analytically or numerically using the Gaver-Stehfest Algorithm. In EnKF, the permeability or porosity estimation <br /> <br /> processes is calculated through the updating processes. The validation of EnKF is analyzed using convergence in probability which is visualized by using the statistical <br /> <br /> quality control methodology where the limit of the chart is calculated based on the Chebyshev inequality. <br /> <br /> The result shows that the EnKF can be used to estimate the reservoir parameters using diffusivity equation. The simulation study shows that the estimate converges to the true value. Application of the EnKF depend on the solution complexity of the diffusivity equation. The proposed method has not yet been applied for a real data due to the difficulties of fitting appropriate diffusivity equation.
format Dissertations
author FITRIYATI (NIM: 30109001), NINA
spellingShingle FITRIYATI (NIM: 30109001), NINA
DEVELOPMENT OF ENSEMBLE KALMAN FILTER (ENKF) FOR SOME RESERVOIR DIFFUSIVITY MODELS
author_facet FITRIYATI (NIM: 30109001), NINA
author_sort FITRIYATI (NIM: 30109001), NINA
title DEVELOPMENT OF ENSEMBLE KALMAN FILTER (ENKF) FOR SOME RESERVOIR DIFFUSIVITY MODELS
title_short DEVELOPMENT OF ENSEMBLE KALMAN FILTER (ENKF) FOR SOME RESERVOIR DIFFUSIVITY MODELS
title_full DEVELOPMENT OF ENSEMBLE KALMAN FILTER (ENKF) FOR SOME RESERVOIR DIFFUSIVITY MODELS
title_fullStr DEVELOPMENT OF ENSEMBLE KALMAN FILTER (ENKF) FOR SOME RESERVOIR DIFFUSIVITY MODELS
title_full_unstemmed DEVELOPMENT OF ENSEMBLE KALMAN FILTER (ENKF) FOR SOME RESERVOIR DIFFUSIVITY MODELS
title_sort development of ensemble kalman filter (enkf) for some reservoir diffusivity models
url https://digilib.itb.ac.id/gdl/view/23497
_version_ 1821121090841214976