A genetic algorithm for filter design to enhance features in seismic images |
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| Authors: | MG Orozco‐del‐Castillo C Ortiz‐Alemán J Urrutia‐Fucugauchi R Martin A Rodriguez‐Castellanos PE Villaseñor‐Rojas |
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| Institution: | 1. Instituto Mexicano del Petróleo, , México, DF, 07730 México;2. Instituto de Geofísica, Universidad Nacional Autónoma de México, , México DF, 04510;3. Laboratoire GET – UMR CNRS 5563 – Université de Toulouse 3 Paul Sabatier – Observatoire Midi‐Pyrénées, , France |
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| Abstract: | We present a novel method to enhance seismic data for manual and automatic interpretation. We use a genetic algorithm to optimize a kernel that, when convolved with the seismic image, appears to enhance the internal characteristics of salt bodies and the sub‐salt stratigraphy. The performance of the genetic algorithm was validated by the use of test images prior to its application on the seismic data. We present the evolution of the resulting kernel and its convolved image. This image was analysed by a seismic interpreter, highlighting possible advantages over the original one. The effects of the kernel were also subject to an automatic interpretation technique based on principal component analysis. Statistical comparison of these results with those from the original image, by means of the Mann‐Whitney U‐test, proved the convolved image to be more appropriate for automatic interpretation. |
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| Keywords: | Interpretation Seismics Signal processing Inverse problem |
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