Modelling method of reservoir space physical property parameters

Abstract

The invention relates to a modelling method of reservoir space physical property parameters, comprising the steps of: 1) digitalizing a deposition phase diagram of a reservoir space to be simulated, and performing integer coding identification, so as to obtain the coordinates of each grid node and the deposition phase identification parameter corresponding to the coordinates; 2) analyzing the correlation between the physical property parameters of the reservoir space to be simulated and the seismic data acting as the constraint data, and regarding the seismic data having the closest correlation with the physical property parameters as 'a second variable' for simulation; 3) performing variation function analysis of the known data by regarding the deposition phase identified in the step 1) and the seismic attributes on the reservoir space obtained in the step 2) as the constraints; 4) performing two-dimensional physical property modelling by regarding the deposition phase identified in the step 1) and the spatial seismic attributes as the constraints; and 5) building a three-dimensional model of the reservoir space physical property parameters according to various two-dimensional physical property models obtained in the step 4).

Description

technical field [0001] The invention belongs to the field of geostatistical modeling for petroleum exploration and development, and in particular relates to a method for calculating reservoir space physical property parameters (including porosity, permeability, mud quality, etc.) content, etc.) modeling method. Background technique [0002] At present, the use of seismic data and sedimentary facies to carry out constrained modeling is the mainstream direction of current research, whether abroad or at home. Modeling using sedimentary facies constraints is also known as "two-step modeling". The first step refers to modeling the large-scale heterogeneity caused by different sedimentary facies with a discrete variable modeling method, that is, "facies modeling"; the second step refers to, on the basis of the simulation results of the first step , that is, under the control of different sedimentary facies, use appropriate geostatistical algorithms to model various physical para...

AI Technical Summary

Problems solved by technology

Since the process of establishing a facies model or generating a "training image" belongs to the modeling method of discrete variables in the stochastic modeling of geostatistics, the two methods have one thing in common that they use the known data in the entire work area to participate in the simulation calculation. Therefore, it is impossible to describe a single phase in detail, so that the data distribution characteristics of a single phase cannot be highlighted, and multiple realizations will be generated for researchers to choose. Therefore, the physical property model generated on this basis has uncertainty and multiple solutions. However, manual interpretation and analysis is based on the realization generated by the algorithm, which is subsequent, so the accuracy cannot be guaranteed, and the second step of physical property simulation based on this will continue this uncertainty, making the simulation effect not good.

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