Dessert reservoir forecasting method and forecasting device

Abstract

The invention provides a dessert reservoir forecasting method and forecasting device. The method includes the steps: delineating the distribution range of a favorable sedimentary facies belt of a target layer based on ancient landform restoration technology of seismic sequence stratigraphic interpretation; forecasting the spreading range of main channel sand within the distribution range of the favorable sedimentary facies belt based on seismic attribute quantitative analysis technology of forward modeling; forecasting reservoir physical property distribution within the spreading range of the main channel sand based on CRP (common reflection point) gather optimization pre-stack elastic impedance inversion technology. Multiplicity caused by directly forecasting reservoir physical properties by the aid of three-dimensional seismic data in the prior art is reduced, so that low-permeability clastic rock reservoir forecasting accuracy is improved.

Description

Technical field [0001] The invention relates to the technical field of reservoir prediction, in particular to a prediction method and a prediction device of a sweet reservoir. Background technique [0002] Since the US Geological Survey put forward the concept of sweet reservoir in 1999, the prediction technology of sweet reservoir in low permeability clastic rock reservoir has been developed rapidly. Sweet-sweet reservoirs refer to relatively well-developed high-quality reservoirs under the background of low porosity and low permeability. Because of the small difference in geophysical response between sweet-sweet reservoirs and non-sweet-sweet reservoirs, it is difficult to identify with seismic data. In seismic reservoir prediction, physical property prediction is a difficult point. For reservoir porosity prediction, it is generally necessary to establish a velocity-porosity relationship. This relationship, whether linear or non-linear, changes with time and space with changes...

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Problems solved by technology

For reservoir porosity prediction, it is generally necessary to establish a velocity-porosity relationship. Whether this relationship is linear or nonlinear, it varies with time and space with changes in longitudinal compaction and lateral deposition. Therefore, the existing It is difficult to establish an accurate petrophysical model of low-permeability clastic rock reservoirs, resulting in poor prediction accuracy when converting seismic parameters into porosity

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