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Rapid particle swarm method for reservoir history matching

A technology of history matching and particle swarm, applied in the field of oil extraction, which can solve problems such as long time

Active Publication Date: 2014-12-17
PETROCHINA CO LTD +1
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] However, at present, both manual trial calculation and software-assisted history matching require a large number of reservoir numerical simulators
Therefore, even software-assisted history fitting still takes a long time to complete the evaluation of model parameters

Method used

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  • Rapid particle swarm method for reservoir history matching
  • Rapid particle swarm method for reservoir history matching
  • Rapid particle swarm method for reservoir history matching

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0068] Taking a block oil layer in an oilfield as an example, the number of model nodes in this block is 400,000, the simulation time is 17 years, and the number of simulated wells is 92, including 54 oil wells and 38 water wells. Initially, this block was only fitted with block indicators, and the initial water content of the whole area was simulated to be low. After analysis, it was considered that the surrounding blocks of this block were developed earlier, resulting in high water content at the initial stage of development of this block. The moisture content is between 5-15 mD. In this embodiment, the goal is to further fit the water content of a single well, and the specific implementation methods are as follows:

[0069] The water cut of the 16 oil wells in the center of the block was selected as the fitting index, the permeability around the perforation layer and the relative permeability corresponding to each grid in the block were selected as the uncertain parameters ...

Embodiment 2

[0081] Under the framework of Embodiment 1, the process of particle grouping can be adjusted as follows:

[0082] The k-means clustering method is still used to complete the grouping of particles. However, when the number of particles in a certain group exceeds 5, they are arranged in descending order according to the distance to the representative particles, and only the first 5 particles are taken as members of the group, and the particles with larger distances behind are assigned larger ones. group. This grouping method ensures the consistency of the number of particles in each group, and can avoid the situation that the number of particles in each group is uneven.

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Abstract

The invention discloses a rapid particle swarm method for reservoir history matching. According to the method, the particle swarms initiated by the Latin Hypercube are clustered and grouped through a clustering algorithm, the particle which is closest to the clustering center in each group is named as the representative particle, other particles are named as non-representative particles, and a response parameter of the representative particle is obtained by calling a numerical reservoir simulator so as to obtain a fitness value of the representative particle; then, the similarity between the non-representative particles and the representative particle is taken as a basis, the response parameter of the representative particle is weighted to be taken as the response parameter of the non-representative particles; and the fitness value of the non-representative particles is further regulated through a special coding mode of the screened representative particle. The method provided by the invention can reduce the times of calling the numerical reservoir simulator when obtaining the response parameter of the non-representative particles, and improve the history matching efficiency to more than 60%.

Description

technical field [0001] The invention relates to a parameter optimization method of a reservoir model capable of reducing the number of calls of a reservoir numerical simulator in the field of petroleum exploitation, and belongs to a fast particle swarm method that can be used for reservoir history fitting. Background technique [0002] Reservoir history matching is an indispensable link in the process of oilfield production design and planning. It is of great significance for making production plans, maximizing the development of existing oil and gas resources, and avoiding the waste of oil and gas resources caused by improper development methods. The traditional reservoir history matching method is to adjust the parameters of the reservoir model by the reservoir engineer based on experience, and then verify the effect of one or more sets of model parameters manually set by the reservoir numerical simulator to check the manual settings. Whether the model parameters can mat...

Claims

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Application Information

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IPC IPC(8): G06N3/00G06F17/50
Inventor 安艳明吴春国赵国忠石亮贺联勤孙文静匡铁李椋楠何鑫
Owner PETROCHINA CO LTD
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