Multiple attribute fusion based on fuzzy logic in oil-gas prediction

There is no obviously corresponding relationship between seismic attributes and reservoir parameters, which inevitably gives rise to uncertainty of reservoir characterization when rely upon single attribute. During the process of reservoir prediction, it is fuzzy whether single or integral attributes are capable of indicating oil and gas or not. To solve the problems above, we propose a multiattributes fusion method based on fuzzy logic, applying fuzzy theory to attributes fuzzy, with the help of membership function to quantify the fuzzy problem, calculating weight factor through fuzzy nearness matrix, eventually obtaining a quantitative comprehensive result. During the process of fusion, the calculation of weight factor of each attributes is completely data driven which could reduce the subjectivity. This method has been tested on synthetic and real data in order to prove its feasibility and effectiveness. Results of the test show that, the fusion results are in accordance with well data. Consequently, the proposed multi-attributes fusion method based on fuzzy logic used for oil and gas prediction is effective and available.