Sedimentation process based river facies reservoir random modeling method

Abstract

The invention discloses a sedimentation process based river facies reservoir random modeling method, comprising the following specific steps: step 1, gridding of a geologic model; step 2, statistics of original sedimentary body lithofacies distribution; step 3, simulation of a sedimentation process and sedimentation recording; and step 4, monitoring, termination condition and adjustment methods for the simulation process. According to the method, firstly, the simulation of the river facies sedimentation process is completer and an evolutionary process for each sedimentation element of a river facies reservoir can be represented more finely; secondly, hierarchical restriction is adopted for satisfying an on-well statistical result to the maximum extent, and river facies ratio is adopted for restricting the whole simulation process; and finally, restriction is performed again according to bank facies and overbank facies, so that a simulation result can be closest to on-well data, a representation result is more accurate and fine and is closer to a real underground condition, and better services are provided for fine description of the reservoir.

Description

technical field [0001] The invention relates to the technical field of oil and gas exploration and development, in particular to a stochastic modeling method for fluvial reservoirs based on sedimentation process. Background technique [0002] Fluvial facies reservoirs are important oil and gas reservoirs in my country. Due to their small scale, fast lateral changes and serious reservoir heterogeneity, it is difficult to quantitatively characterize them by conventional methods. After more than 20 years of development, stochastic reservoir modeling technology has obvious advantages in describing reservoir heterogeneity, integrating various information, and evaluating uncertainty, and provides methods and technologies for fluvial reservoir modeling . The current stochastic modeling methods mainly include object-based methods, pixel-based methods, multi-point geostatistical methods and sedimentary process-based modeling methods. Compared with the other three modeling methods, ...

AI Technical Summary

Problems solved by technology

[0003] However, there are two problems in the current stochastic modeling method of fluvial facies reservoirs based on the sedimentary process: first, it only simulates the sedimentary process of the ch...

Images