Record Details

Title Uncertainty Quantification by Using Stochastic Approach in Pore Volume Calculation, Wayang Windu Geothermal Field, W. Java, Indonesia
Authors M. Asrizal, J. Hadi, A. Bahar, J.M. Sihombing
Year 2006
Conference Stanford Geothermal Workshop
Keywords Wayang Windu, stochastic modeling
Abstract This paper presents the application of a stochastic approach and Experimental Design techniques to a volcanic geologic system in order to quantify the uncertainty of Pore Volume estimations for Wayang Windu geothermal field in West Java, Indonesia. The Pore Volume is a key element when defining the total resource available in the field. The uncertainties being addressed include (i) Geometry (top of reservoir, intrusions and base of reservoir), (ii) Reservoir Continuity (rock type and facies distribution) and (iii) Petrophysical Properties (porosity). The range of uncertainty for each of the parameters was developed using information from varying sources, including data from 30 wells, comparable geothermal fields, Micro Earth Quake (MEQ) measurements, MT/TDEM surveys, etc. Facies groups were modeled based on distance of deposition from the volcanic center, i.e., Central-Proximal, Proximal-Medial and Medial-Distal. The model was controlled by the locations of present day volcanic centers, XRF, age dating, etc. Each facies group consists of different proportions of 5 rock types; lavas, breccias, tuff breccias, lapilli tuffs, and tuffs. Porosity consistent with the rock type and facies distribution was generated within the 3D static model comprised of approximately 26 millions cells using Petrel. The uncertainty was quantified by evaluating the results of multiple realizations through the Plackett-Burmann experimental design technique. The results were then used to generate a range of theoretical pore volumes via Monte Carlo simulation. From this distribution, low, medium and high cases were extracted. The selected cases were upscaled and are currently being evaluated through rigorous dynamic flow simulation modeling. The results show that the pore volume was most sensitive to the following parameters (in order); base of reservoir, porosity values, rock type proportions, top of reservoir, intrusions and facies distribution.
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