Print Email Facebook Twitter Probability distribution functions for geomechanical properties from well log data Title Probability distribution functions for geomechanical properties from well log data Author De Gast, T. Contributor Vardon, P.J. (mentor) Hicks, M.A. (mentor) Faculty Civil Engineering and Geosciences Department Geoscience & Engineering Programme Geo-engineering Date 2013-11-15 Abstract Reliability based calculations and the identification of uncertainties in geomechanical calculations are receiving an increasing amount of attention to evaluate risk. This poses multiple challenges, of which one is the variability of input parameters such as geomechanical properties, geological structures and distribution of material properties. In this thesis, the use of reliability geomechanical analysis in oil and gas reservoirs is investigated. The focus lies on obtaining PDF from well log data, to investigate the effect of stochastic material properties on geomechanical analysis and to identify important uncertainties other than material properties in geomechanical analyses e.g. geometry and depletion pressure distribution. A method of deriving stochastic material properties from well log data is presented and stochastic material properties are described using PDF. A test is introduced to select the most appropriate PDF in terms of best fit. The most appropriate PDF can be obtained by comparing a PDF to the histogram of a set of well log data. In addition to this, it was observed that removing linear depth trends reduce the uncertainty in most observed material properties. Stochastic material properties have been used as input for a series of probabilistic geomechanical analyses. The main geomechanical reliability response studied in this thesis is large scale subsidence caused by pressure changes in a reservoir. Large scale subsidence has also been compared to a small scale SCU response. The effects of stochastic material properties on subsidence are compared to SCU in geomechanical reliability response. For subsidence it was found that, increasing the resolution of uncertainty, i.e. increasing the amount of layers, reduces the variation of results. For SCU geomechanical reliability, increasing the resolution of uncertainty The results increases the variation of results. For the geomechanical analyses, example real reservoir data are used to study uncertainties in geomechanical reliability analyses. Data from a real case were used to illustrate the effects of reservoir geometry and depletion pressure distribution on the calculated subsidence above a depleting reservoir. The different geomechanical analyses demonstrate the need to include spatial variation of the reservoir, i.e. the variation of the pressure distribution and both vertical and lateral variation in material properties. Subject PDFsubsidence To reference this document use: http://resolver.tudelft.nl/uuid:9717d012-bcdb-4c53-ac69-3de2ba18e7ee Part of collection Student theses Document type master thesis Rights (c) 2013 De Gast, T. Files PDF 131110_Final_MSc_thesis_T ... e_Gast.pdf 9.82 MB Close viewer /islandora/object/uuid:9717d012-bcdb-4c53-ac69-3de2ba18e7ee/datastream/OBJ/view