| With the exploration and development technology for oil field being improved,most of the oil fields in China are in the middle-later development or mature phase.Therefore,how to establish a three-dimensional reservoir geological model with higher resolution to guide the exploration and development of the remaining oil has become particularly important.The critical issue is how to make full use of the data in different scales such as geological?seismic and well logging data in the process of modeling.The seismic driven modeling method has been proposed as a modeling method to integrate logs and seismic data in recent years.It makes full use of the spatial information from seismic data,at the same time,it avoids the calculation of variogram which rely on well data in geostatistics modeling.The seismic driven modeling method provides a way to estimate cross-well petrophysical properties in some conditions such as sparse or large well spacing reservoirs.The fluvial sands are very important oil and gas reservoirs in continental basins of China.Sedimentary sequence analysis are generally based on outcrop and core data rather than the spatial superposition patterns of sands.Therefore,it is important to combine seismic data with sedimentary facies in the process of constraining reservoir modeling and detailed characterization.This work improves the recognition algorithm of the sand superposition patterns under multi-horizon constraints.In this process,the zone involved in pattern recognition are constrained by single horizon.It combines the correlation analysis of sand superposition pattern template and target sand.This improves the accuracy of sand pattern recognition.Then,the method is applied to modeling methods such as seismic driven modeling?Bayesian modeling and sequential Gaussian modeling for comparison.The models are verified by seismic forward modeling.Finally,the modeling methods and model is further evaluated. |
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