Fluvial facies low-sand-factor reservoir prediction method

Abstract

The invention provides a fluvial facies low-sand-factor reservoir prediction method. The method includes the following steps that: 1, synthetic seismogram fine calibration is performed so as to clarify the depth range of a fluvial facies low-sand-factor reservoir; 2, a variety of attributes are extracted, the macroscopic distribution characteristics of the main body of a river channel are jointlyanalyzed; 3, rock electric analysis is performed so as to optimally select a reservoir indication sensitivity curve; and 4, inversion is performed by using the sensitivity curve, the distribution condition of the reservoir in a longitudinal direction is predicted. According to the fluvial facies low-sand-factor reservoir prediction method of the invention, based on geophysics means and rock electric analysis, a practical and effective identification method is established. With the method adopted, the distribution of the fluvial facies low-sand-factor reservoir can be determined accurately; a potential target region can be revealed; and oil and gas exploration can better guided. The method can provide guidance and reference for other sand body reservoir prediction.

Description

technical field [0001] The invention relates to the technical field of oil field exploration, in particular to a method for predicting fluvial reservoirs with low sand content. Background technique [0002] Fluvial sand bodies are one of the main reservoir types of oil and gas reservoirs, and how to predict the reservoirs of fluvial sand bodies with low sand content is a difficult point in oil and gas field exploration at present. How to comprehensively use logging data and 3D seismic data to predict fluvial reservoirs with low sand content is a key technology to improve the exploration effect of oil and gas fields. Taking geophysical exploration as an example, foreign countries started the application of seismic attribute technology earlier. Seismic attribute technology emerged in the late 1960s, mainly focusing on seismic processing and imaging. Since the 1990s, seismic attribute and multi-attribute analysis methods represented by coherent volume attribute technology have...

AI Technical Summary

Problems solved by technology

Taking a certain oil field exploration area as an example, the Guantao Formation is a fluvial sand body, and the sand content of the 5th sand formation in the lower section of Guantao is low, only 15%-25%. Uncertainty in structure, distribution and characteristics brings difficulties to exploration and deployment

However, it is difficult to accurately predict the distribution range of reservoirs only by relying on a single seismic attribute analysis method

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