Waveform Structure Analysis And Its Application To Reservoir Characterization

Today, the most relatively simple geological structure of hydrocarbon reservoirs have been discovered. Our hydrocarbon exploration has entered a period of complex lithologic traps exploration. With the progress of seismic interpretation technology for more and more complicated oil and gas exploration, seismic prediction technology is toward to the fine and practical period. Seismic reservoir prediction such as calculation of seismic attributes, inversion, etc. often lost two basic information: 1, the overall changes of seismic signals in the work area are unclear; 2, what is the distribution of this change? So it is difficult to give a reliable assessment of the change of seismic signal in the well location and it is also difficult to extrapolate reliable information. In order to improve the accuracy of forecasting hydrocarbon, the choice of the parameters to describe the seismic signal characteristics and the accuracy of using these parameters to divide the seismic facies will directly affect the results of the reliability of hydrocarbon exploration. Now, seismic facies analysis techniques are becoming more diverse, seismic facies analysis method can solve some of the seismic reservoir prediction problems well. Structure of seismic waveform and its variation are important seismic parameters.Seismic waveform classification technique is the extension and the development of seismic facies analysis technique with following the same basic principles of seismic stratigraphy. In the seismic reservoir prediction, the results of seismic attribute analysis along the layer or from interval have practical significance to predict the complex lithology and distribution of it. The change of sedimentary facies always corresponds with the total change of the seismic reflection structure which is related to the amplitude, phase, frequency, etc. while the overall changes in seismic waveform can reflect changes of the seismic reflection structure. Seismic waveform analysis and classification can identify the general law of the changes of seismic signal to understand the Variation of sedimentary facies and the facies variation.The dolomitic reservoir in Feng1 formation is major reservoir of lithologic hydrocarbon reservoir with structural setting in the area Permian system of Northwestern Margin of Junggar Basin. There are matrix porosity, cracks and holes exist in reservoir of Fengcheng formation, and the relationship of hydrocarbon and water is complex. Although the rock pores develop in the lithologic reservoir, but the connectivity is poor. Only under the conditions of the strong fragmentation in the rock and the fractures are well developed, non-continuous pore can form a good storage space. The heterogeneity of lithologic reservoir and the restriction of seismic resolution cause a lot of difficulty in such lithologic reservoir prediction. Therefore, the key issue of the reservoir study in this region is effectively to identify and to predict the fractured dolomitic reservoirs.Through the analysis of the factors which influence the wave structure, this paper discusses the description methods of waveform shape, using neural network analysis to classify lithology based on the change of waveform structure and dividing the lithology and making the reservoir prediction by using seismic facies analysis. Combining with drilling information, logging data and seismic data on the northwestern margin of Junggar Basin, the good quality dolomitic reservoirs in Permian period Fengcheng formation are identified and predicted, and the results of the waveform structure responses of oil and gas facies and hydrocarbon bearing traps are provided for drill sites selection.