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The Study On Seismic Attribute And Its Application To Reservoir Forecasting Of Fulin Subsag, Shengli Oil Field

Posted on:2009-02-01Degree:MasterType:Thesis
Country:ChinaCandidate:W Y YaoFull Text:PDF
GTID:2120360242493142Subject:Earth Exploration and Information Technology
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This dissertation discusses seismic attributes' application in predicting turbidite fan reservoir. It firstly summarizes the development of seismic attribute, and the algorithms and geophysical significance of some common seismic attributes are systematically illuminated. Then the paper discusses the method of seismic attributes optimalization and interpretation. Based on these studies, the method of seismic attribute is applied to reservoir forecasting of the third member of Shahejie Formation in Fulin Subsag, Shengli Oil Field.The interval of interest located in lacustrine basin in geological history, and the turbidite fan that shows no clear reflection event on seismic image is the main exploration object. In this dissertation, the whole skeleton is as the follows: firstly, analyzing the sedimentary facies; secondly, tracking the sandstone body in the favourable zones; finally, forecasting the distribution of hydrocarbons.The main study is as follows:1. We make a statistic of sediment charge through cores, and summarize the area's lithofacies and the sedimentary facies.2. We analyze the algorithms of impedance and coherency. Then, we apply time slices in impedance data cube to describe the reservoir's sedimentary environment and track the sandstone body. With the analysis of palaeotopography and provenance, we use time slices in coherency data cube which has a sensitively response to the seismic traces' variance to subtly depict the reservoir's sedimentary environment.3. We use the neural networks to classify the seismic facies. As a special seismic attribute, seismic facies is often defined by multi-attribute utility, and it can be applied to study the subtle sedimentary facies and the endogenous event of reservoir. There are two types of nets:unsupervised net(SOM) and supervised net. By SOM, We analyze the area's seismic facies through single attribute, and the result is similar to the area's lithofacies in high range. Moreover, we use 3 volumn-based attribute that include amplitude, impedance and coherency to classify seismic facies, and get a better result than single seismic attribute. In this course, an algrothms called PCA is used to reduce the dimensions of seismic attributes space. On the other hand, we discuss the use of supervised net. There are two key problems: how to define the model traces, and how to analyze the geological significance of the seismic facies classification. Compared with the result of classification by SOM,the result of seismic facies classification by supervised net has more geological significance, but it is a little less comprehensive.4. Optimizing seismic attributes to forecast the oil-bearing sandstone. Firstly, we use the crossplot maps to analyze the correlation among the attributes.Secondly, we choose the best seismic attribute according to the values of correlation. Finally, we choose the root-mean-square amplitude to predict the hydrocarbon in sandstone body, and suggest three boreholes referring to the sandstone bodies' structure map.In brief, the dissertation applies the theory of seismic attribute to guide the practical application,and developing the study of theory in practice at the same time. Closely connecting the theory of seismic attribute with its application, we study the method to fit to the exploration of reservior in Fulin Sabsag. The result demonstrates that the method of seismic attribute is an effective tool to predict the reservoir in turbidite fan.
Keywords/Search Tags:Seismic attribute, Turbidite fan, Impedance, Coherency, Seismic facies, Cross multi-attribute analysis
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