Relationship between well pattern density and variation function of stochastic modelling and database establishment

Jinkai Wang,Kai Zhao,Jun Xie,Zhaoxun Yan,Yuxiang Fu

doi:10.2516/ogst/2020077

Abstract

For 3D geological modelling of oil and gas reservoirs, well pattern density is directly related to the number of samples involved in the calculation, which determines the variation function of stochastic modelling and has great impacts on the results of reservoir modelling. This paper focuses on the relationship between well pattern density and the variogram of stochastic modelling, selects the large Sulige gas field with many well pattern types as the research object, and establishes a variogram database of stochastic models for different well pattern densities. First, the well pattern in the study area is divided into three different types (well patterns A, B, and C) according to well and row space. Several different small blocks (model samples) are selected from each type of well pattern to establish the model, and their reasonable variogram values (major range, minor range and vertical range) are obtained. Then, the variogram values of all model samples with similar well pattern densities are analysed and counted, and the variogram database corresponding to each type of well pattern is established. Finally, the statistical results are applied to the modelling process of other blocks with similar well pattern density to test their accuracy. The results show that the reservoir model established by using the variation function provided in this paper agrees well with the actual geological conditions and that the random model has a high degree of convergence. This database has high adaptability, and the model established is reliable.

Highlights

Stochastic modelling is a commonly used geological modelling method
The main technical ideas are as follows (Fig. 2): 1. The large study area is divided into three types according to well pattern density, and several different model samples are established in each type to ensure that the well pattern density in each model sample is approximately the same
By comparing the variogram values of all model samples in areas A, B and C, it can be found that with increasing well space, the reasonable variogram range value increases; when the well space increases from 600 m to 1100 m, the major range increases by 55%, and the minor range increases by nearly 50%

Summary

Introduction

Stochastic modelling is a commonly used geological modelling method. Its basic idea is to generate a series of optional and equal probability geological models based on the analysis of known points, which can be used to predict the attribute values of unknown areas between control points (known points) [1,2,3]. A stochastic geological model should have many sister models (random realization) that exist at the same time. The random realizations of the same model generated under the same conditions may differ greatly from each other due to the variation function, and these differences merely reflect the geological uncertainty contained in the random model [6,7,8].

Methods

Findings

Discussion

Conclusion