A Method and System for Intelligent Recognition of Oil and Gas Reservoir Damage Based on Factor Representation

Abstract

The invention discloses an intelligent identification method and system for damage of an oil-gas bed based on factor expression. The method comprises the following steps that (a) damage factors of different reservoir types, conditions and reservoir characteristics are represented qualitatively and quantitatively in a unified manner by using a factor expression method; (b) a prerequisite classification tree of oil-gas bed damage identification is established by combining oil-gas bed damage factors with semantic transformation; (c) the prerequisite classification tree is used to establish a damage identification database with an intermediate conclusion node; and (d) different sensitive data via factor expression is used to calculate proportion of a condition component, accuracy and a threshold in the damage identification database, the intermediate conclusion node is analyzed and determined, and a two-layer knowledge tree is used to obtain data of different damage types and degrees of the oil-gas bed. The method and system have the advantages that data expression is unified, the inference complexity is low, the inference efficiency is high and the conclusion accuracy is high.

Description

technical field [0001] The invention relates to the field of protection of oil and gas reservoirs, more precisely, relates to an intelligent system and identification method applied to prediction and decision-making of oil and gas reservoir damage. Background technique [0002] In the process of exploration and development of new and old oilfields, it was found that a large number of oil and gas wells have been damaged in different forms and in different degrees. From the actual production situation, the outstanding performance is that it is easy to cause damage to the reservoir during the well completion and operation process. Such as sensitive damage in well completion, calcium sulfate and calcium carbonate scaling in the production process, well flushing fluid in the low-pressure well operation process enters the formation and causes no liquid, etc. These damages lead to a decline in the production of oil and gas wells or even no production . The causes of reservoir dama...

AI Technical Summary

Problems solved by technology

However, in practical applications, the recognition rate of reservoir damage is not high, and the effect is not good, specifically manifested in:

[0004] (1) Oil and gas reservoir damage reasoning involves a large amount of input data, many types, many data sources, many types of data values, data inconsistency, and large uncertainties in input data;

[0005] (2) The amount of knowledge is large, there are many rules, and there are many relationships between rules, and the traversal reasoning time is too long;

[0006] (3) The accuracy of reasoning is not high. The same kind of reservoir damage has various conditions, and each condition leads to different conclusions of reservoir damage.

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