Research On High-resolution Cascade Attribute Analysis Technology Reservoir Prediction

Extracting multiple attribute data interpretation method focuses on individualtechnology, such as root-mean-square amplitude, autocorrelation,, three instantaneoustechnology. How after extraction of the property based on the characteristics of eachattribute itself, further processing and to get new seismic attributes, still need todifferent work area for further research. Reference signal theory knowledge, putsforward the composite, difference, product and cascade, physical meaning is simple,and sensitive data match and display of the new seismic attributes, namely compositeproperties, cascade attribute the compound attribute is different from the above, it is aprocess of seismic attributes of seismic attributes to calculate step by step. Cascadeattribute to many basic attribute, through the study of different3D lock in NorthOrdos work area, based on high resolution of time-frequency analysis of cascadeattributes tend to have very good geological effect.Multi-attribute analysis and the time-frequency analysis is an important step inseismic data interpretation, through the application of the conventional multi-attributeanalysis methods shows that low resolution in thin reservoir prediction has the verybig limitations, for the thin reservoir is necessary to improve the resolution of seismicdata, the high time-frequency resolution, on the basis of time-frequency analysis,according to the analysis of the obtained parameters of spectrum decompositionprocess, then carries on the multiple attribute analysis and frequency division basedon the wave impedance inversion, it can effectively improve the prediction ability,reflects the meaning of cascade attribute. This article reviewed the seismic spectrumdecomposition technique, multiple attribute analysis technology, and cascade attributeanalysis technology development history, summarizes the research significance andresearch ideas.This paper studies the low frequency of time-frequency analysis technology,through the study of theory is not at the same time frequency analysis method and testcalculation, compares the application effect of several time-frequency analysismethods, the Gabor transform, and the improved generalized S transform, smoothWigner Ville distribution spectrum decomposition technique applied in thin reservoirin North Ordos area. Using Gabor transform. Generalized S transform, eliminate smooth Wigner Ville after the cross terms of2D post-stack data is calculated, thefrequency of different frequency section, due to the strong interference purpose layerin coal seam, in order to find oil and gas resources of the low-frequency shadow, thena coal seam has the characteristics of high energy strong reflection is used, you needto predict sand bodies distribution, high frequency information supplied a technicalguarantee for the progress of the reservoir prediction.Combined with workers in Northern Ordos basin regional geologicalcharacteristics and reservoir characteristics, this paper predict the difficulty of3Dwork area is presented, and the region of low resolution reservoir geology, thelimitations of the multiple attribute analysis technology, use based on spectraldecomposition after dealing with the reservoir prediction, fracture description,constrained sparse pulse coherent wave impedance inversion, and inversion predictionafter frequency division processing, to illustrate the advantage of cascade attribute.In order to reflect the advantage of cascade attribute, we study the sparse pulseinversion, coherent algorithm, etc. First using sparse pulse inversion characteristics, tosparse formation processing, to extract the corresponding real reflection coefficient offormation, the result of inversion is more close to real information; Secondly,horizontal and vertical seismic data information is very rich, we are using thespectrum decomposition after processing, inclination, curvature of coherentcomprehensive properties to detect micro fracture, enriched the contents of theattributes of the seismic coherence and better improve the horizontal and verticalresolution of seismic data; Again, in order to further illustrate based on high-precisiontime-frequency analysis of the spectral decomposition of cascade data foridentification of thin reservoir has better sensitivity, sliced the spectral decompositionof high frequency data at the well point values in the region and the locationinformation of the thin layer of sand body thickness in correlation analysis, cascadeattribute slice amplitude with the drilling in sand body formed the obvious positivecorrelation between features. This means that after dealing with the spectraldecomposition of cascade high frequency attribute slices can be predicted more than4meters and sand bodies in the region, the precision than the conventionalmulti-attribute analysis method can achieve accuracy.