Oil and Gas Identification Based on Bright Spot Technology Using Matching Pursuit and RGB Attribute Blending

The matching pursuit algorithm decomposes wavelets based on the best signal matching. It cannot only extract accurate frequency information, but also can pick up the strong amplitude of possible bright spot adaptively according to the threshold control combining the well data. While RGB blending technology of spectral bands data can make full use of the information of all frequency bands, which can reduce the interpretation ambiguity. In order to improve the precision of interpretation based on bright spot technology, the authors take both the amplitude and frequency into account and choose the wavelets (which are decomposed by the matching pursuit algorithm) related to the oil and gas to predict the possible bright spot, so as to remove the effect of strong amplitude of non-reservoirs first. Then RGB blending technology is used to the three spectral bands of the possible bright spot to predict the oil and gas. Finally, the validity of the method is verified through the tests of model and real data. It demonstrates that this method can improve the precision of identification of bright spot, and reduce the interpretation ambiguity of the reservoir.