A fluvial facies three-dimensional sedimentary facies model deterministic modeling method

Abstract

The invention provides a fluvial facies log facies rapid interpretation method and a fluvial facies three-dimensional sedimentary facies model deterministic modeling method. The fluvial facies three-dimensional sedimentary facies model deterministic modeling method comprises the steps of based on single layer interpretation data of each well, firstly performing log facies identification by using thickness and oil bearing property data and then performing log facies rapid correction based on the shape, amplitude and top / bottom contact relations of a natural gamma or natural potential curve of each single layer; by using the synthetic seismogram calibration technology, determining the seismic horizon corresponding to each single layer and extracting the corresponding root mean square attributes in a certain time window of the seismic horizons; by using the obtained log facies of each single layer and the corresponding root mean square attribute of each single layer, drawing a fluvial facies sedimentary facies map; inputting the sedimentary facies boundaries of fluvial facies river channels in the digital sedimentary facies map into geologic modeling software and establishing a three-dimensional sedimentary facies model by directly using the assignment method. The log facies interpretation is more efficient and rapid and sedimentary facies maps are more accurate; nondeterminacy of sedimentary facies models caused by random modeling is prevented; sedimentary facies models established by using the method can be used for constraining three-dimensional geologic model modeling such as porosity and permeability.

Description

technical field [0001] The invention relates to the field of oil field development geology, in particular to a deterministic modeling method for a fluvial three-dimensional sedimentary facies model. Background technique [0002] Traditional logging facies interpretation must first identify sand bodies, and then mainly rely on the experience of geologists to judge based on the shape, amplitude, top-bottom contact relationship of natural gamma ray curves, etc., which is very inefficient; Modeling mainly uses object-based stochastic modeling methods or multi-point statistical modeling methods, but these methods are difficult to reproduce the spatial distribution and complex connectivity attributes of the channel. Contents of the invention [0003] In order to solve the above problems, the present invention provides a method for rapid logging facies interpretation and correction using oilfield sublayer data and a deterministic modeling method for a three-dimensional sedimentar...

AI Technical Summary

Problems solved by technology

[0002] The traditional logging facies interpretation must first identify the sand body, and then mainly rely on the experience of geologists to make judgments based on the shape, amplitude, top-bottom contact relationship of the natural gamma ray curve, etc., which is very inefficient; the traditional fluvial facies 3D sedimentary facies Modeling mainly uses object-based stochastic modeling methods or multi-point statistical modeling methods, but these methods are difficult to reproduce the spatial distribution and complex connectivity attributes of the channel

Images